Building standardized and secure mobile health services based on social media

elec onics A icle Building S anda dized and Secu e Mobile Heal h Se ices Based on Social Media Jesús D. T igo 1,* , Ósca J. Rubio 2, Miguel Ma ínez-Esp onceda 1,Ál a o Alesanco 3, JoséGa cía3and Luis Se ano-A iezu 1 1Depa men o Elec ical, Elec onic and Communica ions Enginee ing, Public Uni e si y o Na a a, Ins i u e o Sma Ci ies (ISC), Na a a Ins i u e o Heal h Resea ch (IdiSNA), 31006 Pamplona, Spain; [email p o ec ed] (M.M.-E.); [email p o ec ed] (L.S.-A.) 2E e is Asse s, 50009 Za agoza, Spain; [email p o ec ed] 3Depa men o Elec onics Enginee ing and Communica ions, Uni e si y o Za agoza, A agón Ins i u e o Enginee ing Resea ch (I3A), 50018 Za agoza, Spain; alesanco@uniza .es (Á.A.); joga mo@uniza .es (J.G.) *Co espondence: [email p o ec ed] Recei ed: 20 Oc obe 2020; Accep ed: 18 Decembe 2020; Published: 21 Decembe 2020   Abs ac : Mobile de ices and social media ha e been used o c ea e empowe ing heal hca e se ices. Howe e , p i acy and secu i y conce ns emain. Fu he mo e, he in eg a ion o in e ope abili y biomedical s anda ds is a s a egic ea u e. Thus, he objec i e o his pape is o build enhanced heal hca e se ices by me ging all hese componen s. Me hodologically, he cu en mobile heal h elemoni o ing a chi ec u es and hei limi a ions a e desc ibed, leading o he iden i ica ion o new po en iali ies o a no el a chi ec u e. As a esul , a s anda dized, secu e/p i a e, social-media-based mobile heal h a chi ec u e has been p oposed and discussed. Addi ionally, a echnical p oo -o -concep ( wo And oid applica ions) has been de eloped by selec ing a social media (Twi e ), a secu i y en elope (open P e y Good P i acy (openPGP)), a s anda d (Heal h Le el 7 (HL7)) and an in o ma ion-embedding algo i hm (modi ying he anspa ency channel, wi h wo e sions). The es s pe o med included a small-scale and a bounda y scena io. Fo he o me , wo sizes o images we e es ed; o he la e , he wo e sions o he embedding algo i hm we e es ed. The esul s show ha he sys em is as enough (less han 1 s) o mos mHeal h elemoni o ing se ices. The a chi ec u e p o ides use s wi h iendly (images sha ed ia social media), s aigh o wa d ( as and inexpensi e), secu e/p i a e and in e ope able mHeal h se ices. Keywo ds: mHeal h; p i acy; secu i y; social media; s anda diza ion 1. In oduc ion In he las decade, he usage o mobile and sma phones has g own exponen ially. Acco ding o a mid-2019 epo [ 1 ], he as majo i y o Ame icans (96%) own a cellphone o some kind, while he sha e o Ame icans ha own sma phones is 81%. This ac has spu ed he scena io o mobile heal h (also e e ed o as mHeal h), which, as s a ed by he Wo ld Heal h O ganiza ion, is he “medical and public heal h p ac ice suppo ed by mobile de ices” [ 2 ]. The co e age o mHeal h includes se e al aspec s, such as he acquisi ion, manipula ion, classi ica ion and ansmission o heal h- ela ed in o ma ion [ 3 ]. Thus, he use s become he cen e o he ac ion, being p oduce s and owne s o hei own biomedical da a and signals, which can be ubiqui ously ga he ed wi h hei own pe sonal heal h de ices and ansmi ed by means o hei pe sonal mobile de ices. Fu he mo e, he use s can analyze hei biomedical da a locally and sha e hem wi h bo h o mal and in o mal ca egi e s. Ul ima ely, such da a can be ei he s o ed in pe sonal da a aul s o u u e consul a ions o sen o o he sys ems o se ices, depending on he mHeal h applica ion. Elec onics 2020,9, 2208; doi:10.3390/elec onics9122208 www.mdpi.com/jou nal/elec onics Elec onics 2020,9, 2208 2 o 26 All said, al hough he easibili y and a ailabili y o adi ional elemoni o ing mHeal h se ices ha e been ho oughly desc ibed in he li e a u e [ 4 , 5 ], he e a e s ill challenges o be sol ed, mainly ela ed o secu i y and p i acy conce ns. Mo eo e , he ixed s uc u es o such cen alized a chi ec u es adi ionally p omo ed by manu ac u e s could lead o lack o engagemen , mo i a ion o connec ions among hei use s, who may decide o c ea e hei own solu ions [ 6 ]. Indeed, many pa ien s and communi ies oday a e demanding o become co-p oduce s and, in he end, holde s o hei own da a. I hey do no ge o ha e con ol, hey may ake o e and c ea e he necessa y ools o gain sel -empowe men hemsel es. An epi ome he eo is he Nigh scou mo emen [ 7 ], an open-sou ce, Do-I -You sel p ojec allowing eal- ime access o a glucose moni o , as well as da a pe sis ence in he cloud. This p ojec can be seen as an illus a ion o he di e ence be ween “pa ien -cen e ed ca e” and “ eal pa ien con olled ca e”, whe e i is he pa ien s, he ela i es and he communi ies hey li e in who inally “make sense” o hings, de ine he goals and s ess cohe ence [8]. Al hough he Nigh scou p ojec has p o ided aluable lessons o he new pa adigm o empowe ed ci izens, one logical s ep o wa d is he use o social-media-based heal h sys ems, since hey could os e engagemen , empowe men and communi y building [ 9 ]. Besides he p edominan ly ludic cha ac e o social media, new uses in di e en domains a e being in es iga ed and de eloped nowadays. They a e d i en by he a ac ing ea u es o social media as well as hei ema kable mass o use s (e.g., as o Sep embe , 2020, Facebook claimed o ha e 3 billion use s [ 10 ], which ep esen nea ly one- hi d o he wo ld’s popula ion). Recip ocally, a ac ing new use s o social media, e.g., hose coming om mHeal h scena ios, would help social media o ea i m hei leading posi ion in oday’s in e ne pano ama. Indeed, social media p o ide a wide a ie y o ools ha enable use s o build communi ies a ound hem whe e hey can c ea e, sha e and exchange in o ma ion in di e en o ma s [ 11 ]. E e since he social media appea ed, he idea o combining social media and heal hca e has gained momen um. S udies ha e ound ha heal hca e o ganiza ions, clinicians, pa ien s and egula o y bodies could bene i om he use o social media [ 12 , 13 ]. Howe e , in spi e o he p omising bene i s o social-media-based heal hca e, he e a e some challenges s ill o be sol ed. Mos o hose issues a e linked o p i acy and secu i y conce ns, bu he e a e also open ques ions abou usabili y, manipula ion o iden i y, go e nance o con iden iali y, along wi h he a o emen ioned demo i a ion [9,14,15]. As i has been ma ked in he li e a u e, he e is limi ed e idence ela ed o he e icacy and e ec i eness o social media in heal hca e [ 9 ]. Mos p ojec s combining heal hca e and social media so a use da a mining o analyze sha ed heal h- ela ed da a and ex ac aluable in o ma ion [ 16 – 18 ]. To da e, howe e , he e is li le e o in he li e a u e owa ds social-media-based mHeal h sys ems whe e biomedical da a a e sen h ough social media while aking in o accoun secu i y and s anda diza ion. An example ha pa ially accomplish such a goal was p esen ed in [ 19 ]. This sys em le e ages Twi e o send he main da a o a back-end eposi o y using a web based app oach, while o e ing he possibili y o sha ing heal h- ela ed messages cons uc ed acco ding o pa icula s a us desc ip o s using a medical nomencla u e. None heless, as ega ds o p i acy and secu i y, hey only make use o he buil -in secu i y policies implemen ed by Twi e (open au hen ica ion and p i a e lis s). Rela ed o his, he au ho s p esen ed a echnical p oo -o -concep sys em o ollowing up ca dio ascula pa ien s using Twi e and Heal h Le el 7 (HL7) [ 20 ], which can be conside ed an imp o emen he eo . Ne e heless, no u he secu i y and p i acy measu es we e implemen ed. Thus, adequa e p o ec ion policies shall be implemen ed in social-media-based, mHeal h applica ions o achie e secu i y and p i acy le els in line wi h he demands o use s and he egula ions applicable. Examples o such egula ions a e he Heal h Insu ance Po abili y and Accoun abili y Ac (HIPAA) in he Uni ed S a es o he Gene al Da a P o ec ion Regula ion (GDPR) in Eu ope, e ec i e since 2018. The use o HIPAA as a means o achie ing s anda dized da a secu i y and p i acy in mHeal h scena ios has al eady been p oposed in he li e a u e [ 21 ]. A common objec i e o hese egula ions is o gua an ee In o ma ion Assu ance and Secu i y (IAS). T adi ionally, con iden iali y, in eg i y and a ailabili y—also e e ed o as he CIA- iad—we e he elemen s modelling IAS. Nowadays, he Elec onics 2020,9, 2208 3 o 26 CIA- iad has e ol ed o a mo e comp ehensi e IAS-oc a e (con iden iali y, in eg i y, a ailabili y, accoun abili y, audi abili y, au hen ici y, non- epudia ion and p i acy) [ 22 ]. Such egula ions also en o ce p e en ion and eac ion o da a b eaches as well as esponsibili y and sanc ions o hose ha do no ho oughly add ess he a o emen ioned measu es. Social media se ices mus comply wi h egula o y equi emen s o he coun ies hey a e wo king in. Howe e , uploading unp o ec ed da a o social media could sow suspicion o mis us among use s. The e o e, he design and implemen a ion o an addi ional obus secu i y laye , being complemen a y o he measu es al eady implemen ed by social media, would help o gua an ee independence om hei p i acy policies and aise he us o he po en ial use s. Addi ionally, i is ue ha any ad-hoc secu e, p i a e, social-media-based, mHeal h solu ion is able o exchange biomedical in o ma ion wi hou he need o a common in o ma ion model. Howe e , his may no su ice i pe asi e, dis ibu ed, in eg a ed biomedical ecosys ems a e o be achie ed [ 23 ]. In o de o accomplish a leas seman ic in e ope abili y—acco ding o he model p oposed by Tu ni sa e al. [ 24 ]— he con en o he in o ma ion exchange eques s mus be unambiguously de ined. Hence, biomedical in e ope abili y s anda ds a e highly ecommended. Wi hin he heal hca e domain, ini ia i es like HL7 o Digi al Imaging and Communica ion in Medicine (DICOM) a e obus , widesp ead examples o his s anda diza ion e o . The elemen s p esen ed in he pa ag aphs abo e— o wi , mHeal h, social media, secu i y/p i acy and s anda diza ion—a e usually ea ed as sepa a e, o , a leas , loosely in eg a ed ields. The exis ing li e a u e o e s p elimina y examples desc ibing sys ems ha pa ially co e some o hese ields combined, being he mos comple e so a he wo k conduc ed by T ian a yllidis e al. [ 19 ] and a p e ious wo k by he au ho s [ 20 ]. Thus, he unde lying hypo hesis o his pape is ha all hese componen s could be seamlessly me ged o build enhanced heal hca e se ices ( his is co e ed in Sec ion 2). As a esul , he main objec i e o his wo k is o p opose a gene ic a chi ec u e o building s anda dized, secu e, p i a e, social-media-based mHeal h se ices (Sec ion 3.1). Fo he sake o simplici y and con enience, we in oduce he e he ac onym mH3S (a e mHeal h, s anda dized, secu e and social). Secondly, a p oo o concep o he p oposed mH3S a chi ec u e will be also p esen ed (Sec ion 3.2). I is composed o (a) Twi e as he social media, (b) e sion 2 o HL7 as a means o in e ope abili y, (c) openPGP as secu i y en elope and (d) a pa icula embedding algo i hm. Thi d, bo h he gene ic a chi ec u e p oposed and he echnical p oo -o -concep implemen a ion a e discussed in Sec ion 4. Conclusions a e d awn in Sec ion 5. Table 1p o ides a lis o he ac onyms used h oughou he pape . Table 1. Ac onyms and hei meaning. Ac onym Meaning AES Ad anced Enc yp ion S anda d API Applica ion P og amming In e ace CA Ce i ica ion Au ho i y CIA Con iden iali y, In eg i y and A ailabili y CDSS Clinical Decision Suppo Sys ems CMS C yp og aphic Message Syn ax DICOM Digi al Imaging and Communica ion in Medicine ECG Elec oCa dioG am EHR Elec onic Heal h Reco d GDPR Gene al Da a P o ec ion Regula ion GZIP GNU ZIP HIPAA Heal h Insu ance Po abili y and Accoun abili y Ac HIS Heal h In o ma ion Sys em HL7 Heal h Le el 7 HS Hos Sys em HTTPS Hype ex T ans e P o ocol Secu e IAS In o ma ion Assu ance and Secu i y IEEE Ins i u e o Elec ical and Elec onics Enginee s Elec onics 2020,9, 2208 4 o 26 Table 1. Con . Ac onym Meaning IETF In e ne Enginee ing Task Fo ce IHE In eg a ing he Heal hca e En e p ise ISO In e na ional O ganiza ion o S anda diza ion JPEG Join Pho og aphic Expe s G oup LOINC Logical Obse a ion Iden i ie s Names and Codes mH3S S anda dized, secu e/p i a e, social-media-based mobile heal h a chi ec u e OAu h Open Au ho iza ion openPGP open P e y Good P i acy ORU Obse a ion Resul Unsolici ed PHD Pe sonal Heal h De ice PHR Pe sonal Heal h Reco d PKI Public Key In as uc u e PNG Po able Ne wo k G aphics QR Quick Response RGBA/ARGB Red G een Blue +Alpha RSA Ri es , Shami and Adleman S/MIME Secu e/Mul ipu pose In e ne Mail Ex ensions SCP-ECG S anda d Communica ions P o ocol o compu e assis ed Elec oCa dioG aphy SNOMED-CT Sys ema ized Nomencla u e o Medicine—Clinical Te ms TLS T anspo Laye Secu i y TPM T us ed Pla o m Modules UCUM Uni ied Code o Uni s o Measu e UMLS Uni ied Medical Language Sys em 2. Ma e ials and Me hods The me hodology p oposed in his pape consis s o wo s eps. Fi s , he cu en mHeal h a chi ec u es— ocused on elemoni o ing a chi ec u es—a e illus a ed, co e ing he adi ional usage and hei e olu ion. Second, he limi a ions o he a chi ec u es composing such e olu ion a e desc ibed h ough a comp ehensi e e iew o he exis ing li e a u e, which ul ima ely will lead o he iden i ica ion o new po en iali ies o a no el app oach. 2.1. Analysis o T adi ional Telemoni o ing mHeal h A chi ec u es A gene ic mHeal h a chi ec u e acili a es he implemen a ion o mHeal h applica ions, usually g ouped in h ee majo —and in e ela ed— ields: heal h and i ness, independen li ing and disease managemen . Al hough o he mHeal h applica ions a e possible—e.g., medical e e ence, nu i ion o wellness applica ions–, he scope o his pape is ocused in applica ions ha a e able o epo medical s a us upda es o o mal o in o mal ca egi e s. Such applica ions demand a eliable and e icien acquisi ion o pe sonal biomedical in o ma ion, i s adequa e s o age and a pe asi e, ubiqui ous and con olled access o he use s ha need o consul his in o ma ion. To cope wi h he equi emen s o he heal h scena ios desc ibed abo e, di e en mHeal h a chi ec u es ha e been p oposed and de eloped in he li e a u e [ 4 , 5 ]. Re e ence [ 4 ], published in 2015, e iews mHeal h se ices and shows a ypical a chi ec u e he eo . Re e ence [ 5 ] pe o ms a su ey on he a chi ec u es o elemoni o ing esea ch p ojec s in 2014 and, om ha knowledge, de i es a common a chi ec u e o elemoni o ing sys ems, which can be summa ized in h ee dis inc ie s: senso s, ga eway and emo e se e . Based on such e iews, a gene ic mHeal h a chi ec u e is illus a ed in Figu e 1, which is u he de ailed as ollows. The mos basic end- o-end mHeal h a chi ec u e is comp ised by wo elemen s. Fi s , a Pe sonal Heal h De ice (PHD) o , mo e gene ically, a sensing uni , which collec s and sends he use ’s biomedical in o ma ion. Second, a Hos Sys em (HS), which s o es he collec ed in o ma ion, o example a Heal h In o ma ion Sys em (HIS) wi h an Elec onic Heal h Reco d (EHR) o a Pe sonal Heal h Reco d (PHR), he la e also e e ed o as pe sonal da a aul s. In addi ion, he e a e usually Elec onics 2020,9, 2208 5 o 26 se e al PHDs a ound he pa ien /use , and hey seldom ha e he connec i i y o each he HS— o da e, ew PHDs a e In e ne - eady, al hough he pa adigm may be shi ing due o he In e ne o Medical Things [ 25 ]. Thus, mos mHeal h a chi ec u es oday include a hi d elemen , namely he concen a o de ice, a mobile de ice, e.g., cell phone o able , which ga he s he biomedical da a om he di e en PHDs and o wa ds hem o he HS. Fu he mo e, depending on he in ended mHeal h applica ion, a ious o he elemen s can be inco po a ed in o he end- o-end a chi ec u e. Fo example, se ice p o ide s and medical sys ems would be placed be o e and a e he da a a i e a he HS. Examples o medical sys ems a e ala m sys ems o Clinical Decision Suppo Sys ems (CDSS). They would pe o m di e en ope a ions included in he scope o he HS, such as he managemen , moni o ing, p ocessing o ollow-up he use ’s biomedical in o ma ion. Mo eo e , o he elemen s can connec wi h he HS o ei he sha e medical in o ma ion, such as hi d-pa y hos sys ems, o access ha in o ma ion, such as a consul a ion sys ems, he eby in e acing he ca egi e s and he use s wi h he HS (see Figu e 1). As ega ds o he pe sons in ol ed, gene ally, up o ou ypes can be dis inguished in a adi ional mHeal h a chi ec u e: •The pa ien s o use s: They eco d he biomedical measu emen s emo ely. • The o mal ca egi e s: Nu ses and physicians who e iew he in o ma ion and ollow up pa ien s/use s. • Resea che s: E en ually, a esea che would analyze he da a ga he ed om a pa ien /use o a g oup o hem o in es iga e in o a speci ic scena io o pa hology. • The echnicians: They a e in cha ge o ensu ing ha he hospi al de ices and he back-end se ices wo k p ope ly. In he mos basic a chi ec u e, he pa ien /use is he only ac o in ol ed, who moni o s hemsel es using a mobile applica ion (synch onized o no wi h a se e ac ing as PHR), becoming an in o mal ca egi e o hemsel es. Elec onics 2020, 9, x FOR PEER REVIEW 5 o 26 biomedical da a om he di e en PHDs and o wa ds hem o he HS. Fu he mo e, depending on he in ended mHeal h applica ion, a ious o he elemen s can be inco po a ed in o he end- o-end a chi ec u e. Fo example, se ice p o ide s and medical sys ems would be placed be o e and a e he da a a i e a he HS. Examples o medical sys ems a e ala m sys ems o Clinical Decision Suppo Sys ems (CDSS). They would pe o m di e en ope a ions included in he scope o he HS, such as he managemen , moni o ing, p ocessing o ollow-up he use ’s biomedical in o ma ion. Mo eo e , o he elemen s can connec wi h he HS o ei he sha e medical in o ma ion, such as hi d-pa y hos sys ems, o access ha in o ma ion, such as a consul a ion sys ems, he eby in e acing he ca egi e s and he use s wi h he HS (see Figu e 1). As ega ds o he pe sons in ol ed, gene ally, up o ou ypes can be dis inguished in a adi ional mHeal h a chi ec u e: • The pa ien s o use s: They eco d he biomedical measu emen s emo ely. • The o mal ca egi e s: Nu ses and physicians who e iew he in o ma ion and ollow up pa ien s/use s. • Resea che s: E en ually, a esea che would analyze he da a ga he ed om a pa ien /use o a g oup o hem o in es iga e in o a speci ic scena io o pa hology. • The echnicians: They a e in cha ge o ensu ing ha he hospi al de ices and he back-end se ices wo k p ope ly. In he mos basic a chi ec u e, he pa ien /use is he only ac o in ol ed, who moni o s hemsel es using a mobile applica ion (synch onized o no wi h a se e ac ing as PHR), becoming an in o mal ca egi e o hemsel es. Figu e 1. Ac o s and communica ion lows in a adi ional mobile heal h a chi ec u e. 2.2. Limi a ions o he T adi ional App oach, Cu en E olu ion and Po en ial Fea u es As echnology e ol ed and mHeal h a chi ec u es we e becoming mo e pe asi e, addi ional p oblems we e de ec ed and highe a chi ec u al equi emen s we e conside ed necessa y. One o he i s issues iden i ied was he lack o in e ope abili y [26,27], which has been a common opic o deba e o da e. This issue has commonly been add essed by c ea ing medical e minologies and medical s anda ds. Wi hin he o me g oup, one o he mos p ominen is he Logical Obse a ion Iden i ie s Names and Codes (LOINC). The la e g oup comp ises a wide a ie y o examples. A p ominen e o would be he In e na ional O ganiza ion o S anda diza ion (ISO)/Ins i u e o Elec ical and Elec onics Enginee s (IEEE) 11073, in ended o he in e ope abili y o medical de ices. Ano he example is DICOM, in ended o medical images. Addi ionally, he S anda d Communica ions P o ocol o compu e assis ed Elec oCa dioG aphy (SCP-ECG) o he Figu e 1. Ac o s and communica ion lows in a adi ional mobile heal h a chi ec u e. 2.2. Limi a ions o he T adi ional App oach, Cu en E olu ion and Po en ial Fea u es As echnology e ol ed and mHeal h a chi ec u es we e becoming mo e pe asi e, addi ional p oblems we e de ec ed and highe a chi ec u al equi emen s we e conside ed necessa y. One o he i s issues iden i ied was he lack o in e ope abili y [ 26 , 27 ], which has been a common opic o deba e o da e. This issue has commonly been add essed by c ea ing medical e minologies and medical s anda ds. Wi hin he o me g oup, one o he mos p ominen is he Logical Obse a ion Elec onics 2020,9, 2208 6 o 26 Iden i ie s Names and Codes (LOINC). The la e g oup comp ises a wide a ie y o examples. A p ominen e o would be he In e na ional O ganiza ion o S anda diza ion (ISO)/Ins i u e o Elec ical and Elec onics Enginee s (IEEE) 11073, in ended o he in e ope abili y o medical de ices. Ano he example is DICOM, in ended o medical images. Addi ionally, he S anda d Communica ions P o ocol o compu e assis ed Elec oCa dioG aphy (SCP-ECG) o he ansmission o ECGs. To conclude wi h he examples, HL7 is a se o s anda ds o acili a ing he exchange o medical in o ma ion. A chi ec u ally, some o ganiza ions ha e p oposed a a ie y o echnical amewo ks o p omo e he use o such s anda ds. The mos p ominen is In eg a ing he Heal hca e En e p ise (IHE). I p o ides a se o p o iles ha desc ibe clinical in o ma ion needs o wo k low scena ios and ely on exis ing medical s anda ds o accomplish hem. The e has been e o in he li e a u e p esen ing some a chi ec u al p oposals o end- o-end s anda d-based mHeal h amewo ks [28,29]. Despi e he undeniable bene i s o s anda d-based mHeal h, he lack o p i acy and secu i y is s ill one o he majo conce ns [ 30 , 31 ]. As ega ds o consume s a i ude, ha ing con ol o e mHeal h p i acy and secu i y ea u es as well as us in p o ide s we e ecen ly iden i ied as key issues [ 32 ]. Mo eo e , he e a e na ional and in e na ional egula ions—as he a o emen ioned HIPAA o GDPR—which compel mHeal h a chi ec u e designe s o ake in o accoun aspec s such as con iden iali y, in eg i y, a ailabili y, accoun abili y, audi abili y, au hen ici y, non- epudia ion and p i acy. E o can be ound in he li e a u e aimed a p o iding secu e, s anda d-based mHeal h a chi ec u es. Fo example, Rubio e al. p oposed a lexible s uc u e ha p o ides ea u es ailo ed o he needs o di e en mHeal h applica ions, based on a mul i-laye ed, IHE-based ex ension o ISO/IEEE 11,073 [33]. In pa allel, while adi ional mHeal h a chi ec u es we e deployed by heal hca e au ho i ies, hey we e he eby ine i ably—albei no in en ionally—mainly ocused on medical s a and suppo ing clinical wo k. In such adi ional s uc u es, he co e o he se ice is loca ed a he HIS, and i is de eloped by he public o p i a e heal hca e o ganiza ion o e ing he mHeal h se ice. This si ua ion en ails an e o o main ain he so wa e upda ed and he da a a ailable. Cu en ends in da a managemen , howe e , indica e a pa adigm shi owa ds cloud compu ing, which enables designe s o consume di e en esou ces on-demand. Such esou ces include in as uc u e (compu a ion, s o age, ne wo king), componen s ha acili a e he c ea ion o applica ions and se ices (e.g., middlewa e), and hi d-pa y so wa e and/o da a. Se ices such as Amazon Web Se ices, Google Cloud Pla o m o Mic oso Azu e ha e gained no iceable g ound, due o hei wide ange o op ions and lexibili y. In his con ex , Rahimi e al. e iewed he s a e o he a o cloud compu ing in mobile en i onmen s and illus a ed hei applica ion o a ious domains, including heal h [ 34 ]. In he same epo , hey ale ha secu i y and p i acy a e c i ical aspec s wi h s ill open esea ch issues. None heless, e o owa ds mobile cloud compu ing in heal h en i onmen s aking in o accoun —albei o di e en deg ees—s anda diza ion and secu i y/p i acy conce ns can be ound in he li e a u e [ 35 – 37 ]. In 2012, Hsieh e al. p oposed cloud and pe asi e compu ing based 12-lead elec oca diog aphy se ice o ealize ubiqui ous 12-lead ECG ele-diagnosis. In such pape , hey selec ed he Mic oso Azu e cloud o p ocess and s o e he e ogeneous ECG o ma s (e.g., SCP-ECG o DICOM-ECG). They included some secu i y and p i acy ea u es. Fo example, au hen ica ion based on oles and in e ne p o ocol add ess ange, da a enc yp ion ( ia hype ex ans e p o ocol secu e (HTTPS)), sec e key p o ec ed s o age o ECG ile enc yp ion and e i ica ion while epo s a e e ie ed [ 35 ]. In 2013, Ribei o e al. desc ibed a solu ion o ou sou cing medical images o Amazon elas ic compu e cloud based on DICOM and a numbe o IHE p o iles, bu o emos on c oss-en e p ise documen sha ing o images. As ega ds o secu i y, hey p oposed an enc yp ion me hod which hides access pa e ns o a acke s, ye allows sea ches h ough he con en [ 36 ]. In 2016, Hanen e al. published a heal hca e sys em in mobile cloud compu ing en i onmen s. They used a cloud simula o o con ey DICOM-complian medical images conside ing some secu i y and p i acy issues, such as au hen ica ion, access con ol o da a enc yp ion [37]—al hough he eal implemen a ion has no been published so a . Elec onics 2020,9, 2208 7 o 26 While he cloud is a p omising echnology o mobile heal h ca e en i onmen s, i is mainly in ended o back-end pu poses—usually including compu ing load. In addi ion, cloud-compu ing echnologies a e no di ec ly connec ed o he use ’s pe sonal ne wo k. In con as , heal hca e amewo ks ha a e use - iendly, social, empowe ing, decen alized, echnically easy o deploy and sel -manageable could lead o a pa adigm shi . This can be achie ed by using social media, e.g., Twi e , Facebook, e c., which can be seen as a pa icula iza ion o clouds. A a echnical le el, his amewo k would be decen alized and highly lexible, designed o enable and p omo e con en s wi h global each and high equency. This would be achie ed hanks o inexpensi e means (gene ally, no mone a y cos is cha ged o he end use ) and p ac ical ools a ailable o anybody o publish, sha e and iew con en s wi hin sho delay. The e o e, he de elopmen o social-media-based mHeal h se ices has he po en ial o p omo e he ec ui men and ein o ce he engagemen o use s and hei communi ies. I could also enable as , lexible, use -o ien ed and use -con olled con igu a ion o mHeal h a chi ec u es and as and inexpensi e s uc u al deploymen . To do so, mHeal h apps ha use social media o manage and sha e pe sonal biomedical da a in an au oma ic way can be buil by means o he public Applica ion P og amming In e aces (APIs) exposed by social media companies. An associa ed issue ha mus be add essed when building social-media-based se ices is ha such APIs do no allow a high a io o da a sen pe pos (e.g., Twi e limi a ion o cha ac e s). Howe e , mo e impo an ly, in e ope abili y, secu i y and p i acy conce ns should no be o e looked. Conside ing all he abo e, o da e, he bes app oxima ion o an comp ehensi e sys em was conduc ed by T ian a yllidis e al. [ 19 ], who used a social media (Twi e ) o moni o pa ien da a. In o de o uni ocally desc ibe he symp oms o ale s wee ed by he pa ien , his p oposal makes use o he Sys ema ized Nomencla u e o Medicine—Clinical Te ms (SNOMED-CT) [ 38 ] and he Uni ied Medical Language Sys em (UMLS) [ 39 ] me a hesau us API. Ne e heless, he biomedical message is no o ma ed acco ding o any biomedical s anda d—lea ing aside he hesau us. Thus, i could no in e ope a e seamlessly wi h a HIS. Wi h espec o i s secu i y policy, i is s ic ly based on Twi e - ela ed ea u es. In pa icula , hey make use o lis s o use s o con ol he p i acy o people subsc ibing o a se ice. They also use Open Au ho iza ion (OAu h) [ 40 ] o au ho ize he au oma ed sending and ecei ing o wee s om a use accoun . Finally, hei sys em elies on de aul HTTPS o secu e communica ions. Ne e heless, his scheme does no implemen end- o-end secu i y, and hus he in o ma ion can be accessed in clea in he Twi e se e s. An enhancemen o such amewo k was p oposed by he au ho s in [ 20 ], whe e a p oo -o -concep sys em o ollowing up ca dio ascula pa ien s using Twi e and HL7 was implemen ed. Howe e , i was s ill es ic ed o a speci ic medical s anda d and he secu i y and p i acy measu es implemen ed we e jus hose buil -in by Twi e . Mo eo e , he sys em elied in a adi ional clien -se e a chi ec u e, which educed he possibili ies o use s c ea ing hei own sys ems and hus empowe hemsel es. E o s in he li e a u e ha e p oposed some speci ic amewo ks pa ially ul illing he equi emen s o mH3S se ices. To da e, howe e , he e is no p oposal in eg a ing all hese conce ns in a single sys em. The e o e, in his pape we p opose a gene ic a chi ec u e o easy- o-deploy mHeal h se ices based on social media, which con ey in o ma ion in compliance wi h medical s anda ds, while enhancing secu i y and p i acy o end use s. Thus, he a chi ec u e will enjoy he ad an ages ha a social media ne wo k p o ides, such as a use /pa ien social ne wo k, buil -in eliabili y and scalabili y, o up- o-da e GDPR-complian se e s, while con eying s anda dized biomedical da a wi h enhanced secu i y and p i acy measu es applied. 3. Resul s As a esul o he analysis pe o med in Sec ion 2, a gene ic mH3S a chi ec u e is p oposed wi hin his sec ion. The de ails o he p oposed pla o m and a p oo -o -concep he eo a e ho oughly desc ibed in he ollowing subsec ions. Elec onics 2020,9, 2208 8 o 26 3.1. P oposal o a Gene ic mH3S A chi ec u e The newly c ea ed a chi ec u e is illus a ed in Figu e 2. I depic s a sys em o s o ing, communica ing, and consul ing medical da a as well as gene a ing and dis ibu ing ala ms, while b idging he adi ional communica ion gap be ween use s, o mal and in o mal ca egi e s and esea che s. Elec onics 2020, 9, x FOR PEER REVIEW 8 o 26 Figu e 2. P oposal o he gene ic a chi ec u e. 3.1.1. Ac o s o he P oposed A chi ec u e The gene al a chi ec u e is comp ised o eigh ac o s (see Figu e 2): • Use /Pa ien : They will ga he he biomedical in o ma ion and use a mobile phone o able o pos hem. They could also ecei e eedback om o mal o in o mal ca egi e s. • PHDs: The medical de ices used o moni o he use ’s s a us. • In o mal ca egi e : A iend, a neighbo o a ela i e ha helps he use /pa ien o moni o and con ol hei biomedical da a wi hin he heal hy ange o alues. In o mal ca egi e s a e ypically in cha ge o a educed numbe o use /pa ien s. • Fo mal ca egi e : A heal hca e p o ide associa ed o a p o essional o mal sys em, e.g., physicians, nu ses o social wo ke s. They a e able o ake ca e o a ela i ely la ge numbe o pa ien s. • EHR/HIS: This ep esen s he adi ional EHR/HIS. A p oxy would be equi ed o ecei e he biomedical da a (by means o he social media API), dec yp , decode and send such in o ma ion—wi h an app op ia e o ma – o he ac ual EHR/HIS, which would s o e he in o ma ion. This may need u he policies in o de o ensu e he co ec iden i ica ion o he sende . • Cloud p o ide s: Such sys ems may be used o u he compu ing (e.g., signal p ocessing), edis ibu ion o massi e s o age. • Resea che : They would pe o m medical esea ch o e a po en ially high olume o anonymized biomedical in o ma ion ho ough app op ia e da a mining. The open lock in Figu e 2 means ha he con en has been dec yp ed—and anonymized— o esea ch pu poses. • Social media: The co e o he p oposed sys em, which is used as a backbone o communica ion and, o a ce ain ex en , s o age pu poses. I is wo h no ing howe e , ha in speci ic pa icula iza ions o he a chi ec u e, some o hem may no be p esen . Fo example, in a simple sys em, a use /pa ien and an in o mal ca egi e may use he social media o exchange biomedical in o ma ion. In a o mal scena io, a pa ien would communica e wi h a o mal ca egi e h ough he applica ion. The in ended a ge audience o he sys em depends on he scena io. In a scena io wi h a o mal ca egi e , hey should e alua e he si ua ion, he pa ien , and hei li e acy (bo h gene al and echnological). A e he assessmen , he o mal ca egi e would decide whe he o no p esc ibe he Figu e 2. P oposal o he gene ic a chi ec u e. 3.1.1. Ac o s o he P oposed A chi ec u e The gene al a chi ec u e is comp ised o eigh ac o s (see Figu e 2): • Use /Pa ien : They will ga he he biomedical in o ma ion and use a mobile phone o able o pos hem. They could also ecei e eedback om o mal o in o mal ca egi e s. •PHDs: The medical de ices used o moni o he use ’s s a us. • In o mal ca egi e : A iend, a neighbo o a ela i e ha helps he use /pa ien o moni o and con ol hei biomedical da a wi hin he heal hy ange o alues. In o mal ca egi e s a e ypically in cha ge o a educed numbe o use /pa ien s. • Fo mal ca egi e : A heal hca e p o ide associa ed o a p o essional o mal sys em, e.g., physicians, nu ses o social wo ke s. They a e able o ake ca e o a ela i ely la ge numbe o pa ien s. • EHR/HIS: This ep esen s he adi ional EHR/HIS. A p oxy would be equi ed o ecei e he biomedical da a (by means o he social media API), dec yp , decode and send such in o ma ion—wi h an app op ia e o ma – o he ac ual EHR/HIS, which would s o e he in o ma ion. This may need u he policies in o de o ensu e he co ec iden i ica ion o he sende . • Cloud p o ide s: Such sys ems may be used o u he compu ing (e.g., signal p ocessing), edis ibu ion o massi e s o age. • Resea che : They would pe o m medical esea ch o e a po en ially high olume o anonymized biomedical in o ma ion ho ough app op ia e da a mining. The open lock in Figu e 2means ha he con en has been dec yp ed—and anonymized— o esea ch pu poses. • Social media: The co e o he p oposed sys em, which is used as a backbone o communica ion and, o a ce ain ex en , s o age pu poses. Elec onics 2020,9, 2208 9 o 26 I is wo h no ing howe e , ha in speci ic pa icula iza ions o he a chi ec u e, some o hem may no be p esen . Fo example, in a simple sys em, a use /pa ien and an in o mal ca egi e may use he social media o exchange biomedical in o ma ion. In a o mal scena io, a pa ien would communica e wi h a o mal ca egi e h ough he applica ion. The in ended a ge audience o he sys em depends on he scena io. In a scena io wi h a o mal ca egi e , hey should e alua e he si ua ion, he pa ien , and hei li e acy (bo h gene al and echnological). A e he assessmen , he o mal ca egi e would decide whe he o no p esc ibe he use o he applica ion. In an in o mal scena io, bo h he use and he in o mal ca egi e should e alua e he ad an ages and d awbacks o he ool a hei disposal. I i is a hospi al de eloping he applica ion, p ope in o ma ion abou he implica ions could be published so ha use s could make an in o med decision. 3.1.2. Con igu a ion, Usage and Communica ion Flow The se -up equi es minimal con igu a ion. Use s will be asked o ins all a speci ic mobile applica ion (which should be de eloped o o e he mH3S se ice). Such applica ion shall ely in e nally on a social media API. Use s will he e o e need an accoun o his social media ne wo k. Since one o he main ea u es o he amewo k is i s secu i y and p i acy, i s o all, he use s—pa ien s, o mal and in o mal ca egi e s, a hospi al—willing o exchange in o ma ion need o gene a e a pai o public and p i a e keys. The public key has o be exchanged be o ehand. Fo secu i y easons, he public key mus be sen h ough a communica ions channel di e en han he one used o biomedical da a exchange. This could be done by a ious means, e.g., by scanning a Quick Response (QR) code. The de ails o he secu i y and p i acy scheme a e de ailed la e in Sec ion 3.1.4. Once he public keys ha e been exchanged, he communica ion can begin. Howe e , depending on he social media chosen and on how hei accoun s a e con igu ed, he use s may be equi ed o be iend each o he be o ehand. This can also be done inside o ou side he main applica ion. Wi hin he applica ion howe e , he ecei e has o in oduce he name o he sende in he social media ne wo k. This will wo k as a subsc ip ion o he pos s o he sende . A e he con igu a ion p ocess ends, he biomedical in o ma ion would be ga he ed and subsequen ly s anda dized, enc yp ed and embedded in an objec media, p omo ing he iendly use o social media ne wo k (see Sec ion 3.1.4 as well). Immedia ely a e wa d, he use /pa ien would pos he media objec wi h embedded in o ma ion o he social media (see Figu e 2). All use s subsc ibed o he sende pos s— o example, an in o mal ca egi e —will ecei e no i ica ion o he upda e and would be able o dec yp he biomedical in o ma ion, gi en he key exchange ca ied ou be o ehand. The e o e, he social media would be used as a backbone. Subsequen ly, he in o ma ion ecei ed could be s o ed o analyzed. The ecei e may answe o he ini ial sende jus o acknowledgemen o o ecommend o p esc ibe some hing, and he communica ion could be na u ally ca ied ou in an analogous way. In any case, he in o ma ion could be also ansmi ed o a HIS/PHR and i could be anonymized and sen o a cloud p o ide o esea ch pu poses. 3.1.3. Eligible Social Media The a chi ec u e p oposed elies in exis ing social media, such as Twi e , Facebook, e c. In o de o a social media o be eligible o se ing as backbone ne wo k o he p oposed mHeal h a chi ec u e, i should mee a numbe o compulso y equi emen s: • The social media mus o e a public API, so ha he medical in o ma ion can be exchanged p og amma ically. Mos social media oday o e his op ion. • The social media mus allow he sha ing o in o ma ion among use s. Na u ally, his is some hing ha mos social media enable, since i is pa o he ounda ion o social media hemsel es. Elec onics 2020,9, 2208 16 o 26 al hough he modi ica ion could be decided unila e ally, hey a e always announced in ad ance. Social media o e empo al windows o adap he applica ions elaying on hei API o he new si ua ion. I he API is discon inued o he c i e ia o being an eligible social media a e no longe me , he mHeal h se ice as i is would be o ced o de ini i e closu e. Such eliance on co po a ions could be g appled wi h by using—o implemen ing—an open, decen alized social media, such as he Twi e -like mic oblogging sys ems GNU social [ 49 ] o Mas odon [ 50 ], o he Facebook-like, non-p o i , use -owned, dis ibu ed, social media Diaspo a [ 51 ]. Howe e , use s and ca egi e s would be o ced o mig a e o—o a leas c ea e a new accoun o — his se ice, while he numbe o ac i e use s in he main social media—Twi e , Facebook, e c.—is a he big, which clea ly eases adop ion. Use s may join exis ing se e s o open social media, which could be a simple op ion, o al e na i ely, se e s could be ins alled and con olled by use hemsel es o by o mal o in o mal ca egi e s. Howe e , ins alling and main aining a se e is no a simple p ocess o mos use s. Wi h he p oposal depic ed in his pape , howe e , he only equi ed se -up is he ins alla ion o he applica ions in mobile phones, which is easy and s aigh o wa d, e en o use s wi h educed echnological li e acy. Ano he poin o deba e is he p oposal o using social media as a backbone. As opposed o adi ional clouds, social media o e limi ed capabili ies o s o age and sea ching, and hey do no p o ide compu ing powe wha soe e . None heless, social media a e use o ien ed, and hey ce ainly enable da a communica ion, which may su ice o mos elemoni o ing use cases (see Sec ion 4.2. o a speci ic analysis on speed and da a capaci y). The decen alized na u e o he a chi ec u e p esen ed he e is also deba able. The au ho s p opose an a chi ec u e based on social media opposed o cloud se ices, while social media a e hemsel es cloud based. Howe e , social media a e used in he sys em as a backbone. In adi ional a chi ec u e p oposals, he biomedical da a we e con eyed h ough a ypical clien /se e a chi ec u e o a compu ing cloud o sen o a single HIS loca ed a he hospi al, whe e hey would be pe sis ed. By using he p oposed a chi ec u e, he biomedical da a a e sca e ed h oughou he mobile de ices o he use s/pa ien s and o mal/in o mal ca egi e s. Thus, he a chi ec u e is, by na u e, decen alized. Biomedical da a do go h ough and a e s o ed in he se e s o he social media selec ed, bu enc yp ion p e en s da a om being accessed by hem. The ac ual wo h o in oducing social media is some hing ha equi es u he esea ch and alls beyond he scope o he pape . The pe cei ed wo hiness should be alida ed in eal scena ios. In any case, he success o he pla o m may depend on he inal use s and hei echnological li e acy, as well as on he speci ic a chi ec u e selec ed, among o he ac o s. • S anda ds and In e ope abili y: In p inciple, any s anda d is eligible o he p oposed a chi ec u e. I is no ewo hy howe e , ha some s anda ds may be mo e sui able o a speci ic use case o may be mo e p ac ical depending on whe he such s anda d is used in some o he place wi hin he o e all a chi ec u e. In any case, he inclusion o ele an biomedical s anda ds in he a chi ec u e allows he s aigh o wa d in eg a ion o he ga he ed biomedical heal h in o ma ion in heal hca e sys ems, whene e equi ed. • Secu i y and p i acy: The claimed secu i y and p i acy is p o ided by he end- o-end en elope enc yp ion. This p o ides con iden iali y, ia a combina ion o symme ic and public-key enc yp ion. Addi ionally, he digi al signa u es p o ide au hen ica ion and in eg i y alida ion. The in eg i y alida o could be c ucial in an embedding applica ion like his, since i can be used o e i y ha he con en o he message has no be ampe ed wi h. The p oposed a chi ec u e only adds one manda o y laye o enc yp ion, ha en o ced by openPGP. The es o he secu i y measu es a e buil -in ea u es p o ided by he social ne wo k o he in e ne p o ocols. Gene ally, he use s canno op -ou o such measu es, bu hey a e applied in a anspa en way. Once con igu ed, he use o he applica ion is s aigh o wa d. Howe e , a ade-o be ween secu i y/p i acy and usabili y is always p esen when designing echnological a chi ec u es. In Elec onics 2020,9, 2208 17 o 26 gene al, including addi ional secu i y measu es educes usabili y. In he p oposed app oach, he secu i y and p i acy p ocedu e added implies he managemen o a pai o public/p i a e keys (gene a ion, exchange and s o age). Use s mus c ea e a pai o public/p i a e keys. This has o be done only once and i is as easy as pushing a bu on. The exchange o he public key is only equi ed when con ac ing o a new use . The p ocedu e could also be simple, o example, ansmi ing he key h ough a messaging app o using a QR code. Finally, use s would only ha e o manage a way o access he keys s o ed in he key ing (e.g., passwo d, pin, d awn pa e n o e en biome ic au hen ica ion, such as inge p in o acial ecogni ion). Thus, he addi ional complexi y o he pla o m could be conside ed low. Al hough he added complexi y is na u ally a subjec i e ma e , he au ho s conside ha he imp o ed secu i y and p i acy ou weighs he dec eased usabili y. The secu i y and p i acy measu es p esen ed he ein a e s uc u ed unde an end- o-end pa adigm, om he use /pa ien de ice o he o mal/in o mal ca egi e de ice. This means ha he secu i y p o ocols used a e s acked as di e en laye s ha pa ially o e lap each o he , p o iding secu i y along he whole communica ion and s o age p ocess. Fo example, he eques s o he social media API may be ca ied ou using HTTPS/TLS, bu his co e s only he segmen om he de ices o he social media se e . The addi ional secu i y en elope p o ides u he enc yp ion so ha he in o ma ion is no in accessible e en wi hin he social media se e s. Fo inc eased secu i y, he algo i hms selec ed shall be—whene e possible—di e en om and complemen a y o he algo i hms al eady de ined by he physical ne wo k, he social media and he biomedical s anda d—i hey implemen any. This way, i one c yp og aphic algo i hm is comp omised, he o he may s ill be alid. In any case, i any o he chosen algo i hms o a speci ic implemen a ion we e comp omised, i would ha e o be eplaced wi h ano he exis ing algo i hm conside ed secu e and sui able o he applica ion a such ime. Use s/pa ien s may con igu e mul iple ecei e s o biomedical in o ma ion wi hin he applica ion. The a chi ec u e p oposed implies he need o c ea ing one enc yp ion pe ollowe . This may cause scalabili y issues, al hough his is no a p oblem in small-scale p ojec s wi h ew o mal o in o mal ca egi e s. This end- o-end enc yp ion is equi ed in o de o p e en po en ial ea esd opping—including he social media se ice p o ide i sel —and is widely implemen ed in digi al se ices oday—such as Teleg am, Signal o Wha sApp. Secu i y and p i acy could s ill be comp omised due o, o example, he use /pa ien exposing his/he p i a e key. In ha case, he biomedical in o ma ion should be emo ed om he social media ne wo k. In gene al, online social ne wo ks a e exposed o a a ie y o p i acy and secu i y h ea s, such as phishing, ake p o ile c ea ion, o iden i y clone a acks [ 52 ]. The p oposal p esen ed he ein is ulne able o hese a acks inasmuch as i elies on bo h he in e ne and on online social ne wo ks. In e ne use s in gene al and online social ne wo k use s in pa icula mus be awa e o hem and ollow gene al ecommenda ions. Fo example, hey should cus omize adequa e p i acy se ings o he social ne wo k o build us wi h hose applica ions and pe sons ecei ing o managing he use s’ pe sonal in o ma ion [ 52 ]. In addi ion, online social ne wo ks oday o e ecommenda ion o minimize hese po en ial h ea s. Fo example, Twi e has published a webpage o o e guidance and help wi h gene al sa e y and secu i y conce ns [ 53 ], such as po en ially comp omised/hacked accoun s, epo impe sona ion accoun s, and ake accoun s, among o he s. In any case, o he a chi ec u e o unc ion, he concep and scope o us needs o be add essed. In a scena io wi h a o mal ca egi e , bo h he ca egi e and he inal use mus us he applica ion. Howe e , his could be achie ed i he applica ion is de eloped and dis ibu ed ia o icial channels by he hospi al i sel . In addi ion, use s mus na u ally us he doc o sugges ing he use o he applica ion. E ec i e heal h ca e is based on subs an ial us be ween pa ien s and p o essionals, including he clinical ools hey choose o use [ 54 ]. In any case, pa ien s should be p ope ly in o med and should sign an in o med consen be o ehand. Fo he in o mal ca egi e Elec onics 2020,9, 2208 18 o 26 scena io, he use and he ca egi e mus us each o he . This could be easily achie ed, since hey know each o he pe sonally and would e en be ela i es. They mus also us he applica ion. Such applica ion could be he same one as in he o mal ca egi e scena io, ha is, de eloped and published by a hospi al hey us . Finally, ega dless o he scena io, he applica ion code could be open sou ce in o de o enhance us h ough anspa ency. Ha ing his concep o us among use s de eloped, he e is no eason o mis us he o he end. The e o e, he exchange o he public keys is always pe o med in a way ha can always be conside ed us wo hy. The exchange o public keys could be easily pe o med in pe son. Fo he o mal ca egi e scena io, he exchange is pe o med a he momen o en olling in he p og am, o example, by showing a p in ed QR code o he o he use o scan. Ne e heless, i he public keys a e sen h ough he in e ne , he e a e mechanisms o con i m ha he keys ha e no been ampe ed wi h. Fo example, use s could gene a e a oken o he public keys (e.g., a hash) and exchange hem h ough an al e na i e channel (e.g., hey would be sho enough o be ead o e he phone). All said, despi e o he measu es p oposed, no secu i y scheme is 100% secu e o p i a e. The e is always oom o secu i y o p i acy b eaches. Howe e , he p oposed a chi ec u e p o ides use s wi h a amewo k ha is secu e and p i a e enough o c ea e a easible mobile heal h scena io. In gene al, a p ojec like his does equi e cons an main enance and supe ision. Speci ically, hose pa s ela ed o c yp og aphy (lib a ies, algo i hms, keys, e c.) migh be comp omised and need special a en ion. • P esen a ion: We p oposed embedding he biomedical da a blob in o a mul imedia con en . The a ionale behind his decision is wo old. Fi s , because o he social bene i : i is clea ly iendlie o sha e a beau i ul image han an a ay o appa en ly nonsense by es. Addi ionally, he e is also an economy ac o , measu ed in numbe o pos s pe biomedical da a. Social media usually es ic he maximum amoun o cha ac e s (e.g., 140— ecen ly 280—Unicode codepoin s in a wee ) o he maximum size o an image o ideo (a ew megaby es usually) sha ed in a single pos . Thus, he mul imedia app oach was selec ed since i is possible o embed a mo e da a in a single social media pos i a mul imedia con en is used, compa ed o plain ex . In exchange, he app oach selec ed inc eases he o e head and he p ocessing load, which implies highe delays. Ne e heless, his is no an issue, since he a chi ec u e is no in ended o wo k in eal ime, and he enc yp ion algo i hms a e as enough, gi en he amoun o biomedical da a ha i in a single mul imedia con en . • Embedding: Designe s ha e o ake in o accoun ha social media may ampe wi h he uploaded mul imedia con en in a way ha may no be public, and, i he embedding algo i hm selec ed is no obus enough, he in o ma ion could be co up ed pa ially o comple ely. In he p oposed a chi ec u e, a obus enough embedding algo i hm could p e en in p ac ice any po en ial da a co up ion. Howe e , i he da a a e co up ed, he ecipien will de ec ha he in o ma ion has no been ecei ed p ope ly. The en elope p o ides a mechanism o check his. Thus, he ecei e could ask o a e ansmission. Then, he embedding could be ca ied ou using a mo e obus algo i hm o p e en he same p oblem om occu ing again. The sende ’s applica ion could be p o ided wi h a pool o embedding algo i hms, o de ed in e ms o obus ness, so ha he simples / as es one would selec ed, as long as he da a could be e ie ed a he o he end. In any case, he e is a ade-o be ween speed and obus ness. 4.2. Discussion abou he P oo o Concep • Social Media: P i a e messages ha e been used o add ess a pa icula ecei e . Howe e , use s may exchange o he images aside om he heal hca e se ice. I ha is he case, checking he alpha channel and looking o he openPGP da a s uc u e is an e ec i e mechanism o de ec i he e is ac ual biomedical in o ma ion embedded in o he pic u e. Twi e o e s a kind o g oups ( e e ed o as “lis s”), which can be public o p i a e. Howe e , Elec onics 2020,9, 2208 19 o 26 use s a e no allowed o pos di ec ly o a lis , so ha e e y membe o he lis ecei e he wee . Al e na i ely, in he sys em p oposed, use s can send a p i a e message o all ecei e s (see he pa ag aph below). We p opose sha ing he pic u es h ough p i a e messages, al hough his could be ca ied ou ia he public imeline. While he o me would enable he possibili y o mul iple ecei e s in one single pos /image, he la e enhances p i acy. As ega ds o he Twi e API maximum a es, i can be no ed ha hey a e gene ous enough o s o e-and- o wa d, small-scale p ojec s, bu hey may no be enough in scena ios equi ing highe da a a e ansmission o when dealing wi h a as amoun o use s/pa ien s and/o ca egi e s. Twi e o e s a ee sea ch API, bu i is es ic ed o he pas se en days and i is ocused on ele ance—and no in comple eness. This limi s he use o Twi e as a eliable pe sis ence handle . Howe e , hey o e some en e p ise, high-le el sea ch APIs ha could be implemen ed wi h a mone a y cos . Finally, since use s only publish images ha a e aligned wi h hei as e and he opic o hei usual social pos s, he sys em is minimally in asi e wi h ega d o in o ma ion noise. In any case, use s may also c ea e a di e en accoun o his pu pose. • S anda ds and In e ope abili y: Ve sion 2 o HL7 is su icien o he use case po ayed in he p oo o concep —a use connec ing wi h an in o mal ca egi e . The amoun o da a ansmi ed in an HL7 e sion 2 message does no gi e ise o any issues – ega ding he embedding, o example. In he p oo o concep , he e is no in eg a ion wi h pe sonal heal h eco ds o highe HIS, so one can en ision ha he use o a s anda d may no be necessa y. Howe e , he implemen a ion o HL7 lea es open he possibili y o u he in eg a ion. • Secu i y and P i acy: We chose o implemen openPGP o e CMS. Technical di e ences among hem a e no decisi e. Indeed, bo h can be used as a base o Secu e/Mul ipu pose In e ne Mail Ex ensions (S/MIME), which is an In e ne Enginee ing Task Fo ce (IETF) s anda d o public key enc yp ion and digi al signing o MIME da a. CMS is widely used by companies by building a PKI h ough X.509 ce i ica es, which had o be app o ed and signed by a CA be o ehand, which usually equi es some kind o paymen . openPGP, on he o he hand, p o ides an open, decen alized, ee sys em o ce i ica e managemen , which a e he main easons why we chose o implemen his en elope. The secu i y lib a y chosen, Spongy Cas le, based on Bouncy Cas e, cu en ly suppo s all e sions o And oid. Howe e , And oid has announced he dep eca ion o Bouncy Cas le. The e o e, he implemen ed applica ions will equi e changing o (mos likely) he de aul And oid implemen a ion in he o hcoming u u e. Rega ding OAu h, we ha e implemen ed e sion 1.0a. Twi e suppo s bo h e sions 1.0a and 2.0. Howe e , only e sion 1.0a can be used o pos ing on behal o ano he accoun . • P esen a ion: The image sha ed in he p oo o concep is p e-s o ed in he applica ion. Howe e , in o de o enhance he use sa is ac ion and pe sonal binding, he applica ion could be imp o ed by le ing use s upload hei own images. We ha e selec ed an image wi h a RGBA/ARGB colo model in o de o modi y he alpha channel while embedding he in o ma ion. One could en ision ha agged o ma s could be selec ed o embed he in o ma ion in ags, he eby elimina ing dis o ion. Howe e , his could no be implemen ed in his speci ic p oo o concep , since, a he momen o w i ing, Twi e s ips and disca ds he me ada a om uploaded images. • Embedding: The algo i hm implemen ed wo ks lawlessly unde he condi ions documen ed. As he anspa ency in o ma ion is being modi ied, he p ocess na u ally dis o s he image. Less dis o ing and mo e obus algo i hms could be implemen ed. Howe e , as discussed abo e, he e is a ade-o be ween speed and obus ness/dis o ion. In ou implemen a ion, e sion 2 o he embedding algo i hm esul s in less noisy images, bu i akes longe o comp ess hem (see Table 2). Elec onics 2020,9, 2208 20 o 26 The ac ha he image becomes dis o ed does no ha e any e ec on he “clinical” unc ioning o he pla o m, since he pic u e i sel has no clinical meaning. Howe e , a dis o ed image may diminish he “social” componen o he pla o m. Unde he condi ions es ed, wi h only a ew by es o in o ma ion being ansmi ed, li le dis o ion can be pe cei ed by he human eye (see and zoom he dog pic u e in Figu e 4b). Addi ionally, since he social media p ocessing algo i hm may no be public and, mo eo e , he owne s o he social media can change he in e nal algo i hms o e ime wi hou no i ica ion, he e is a need o e iew and upda e he p oposed embedding algo i hms pe iodically. I is wo h no ing as well ha , since social media selec hei p ocessing algo i hms, an embedding algo i hm ha wo ks o a social media may no wo k o ano he . • Da a capaci y: In o de o discuss he pe o mance o he p oposed echnical p oo o concep , we p esen below an analysis in e ms o da a capaci y and speed (a he ansmi e end). Two scena ios we e conside ed: he one p oposed o p oo -o -concep (a small-scale elemoni o ing sys em ansmi ing jus a ew by es) and a bounda y scena io o he p oo o concep (when all he space a ailable is used up). In o de o assess he speed, wo sizes o images we e es ed o he small-scale scena io. Fo he bounda y scena io, bo h e sions o he embedding algo i hm we e es ed. Fo calcula ing he space a ailable in he la e scena io, some calcula ions ha e o be pe o med, acco ding o Twi e ’s cu en image suppo policies [ 55 ]. Fo his p oo o concep , we ha e decided o use he alpha channel o embedding pu poses. Among he image o ma s suppo ed by Twi e , WebP and Po able Ne wo ks G aphics (PNG) p o ide such channel. Howe e , Twi e s a es ha i will anscode all WebP o ma s o 85% quali y Join Pho og aphic Expe s G oup (JPEG) wi h 4:2:0 ch oma subsampling. This may dis o he embedded in o ma ion. A PNG-32 (8 bi s pe channel ARGB), on he o he hand, will be le as-is i he image has mo e han 256 colo s and i is 900 pixels o smalle in he longes dimension ( ha is, i can i in o 900 × 900). I i has ewe colo s, i will be anscoded o PNG-8. I i is g ea e han 900 × 900, i will be es ed o conside i hey will emain PNG o i hey will be con e ed o JPEG, being he la e mo e likely. Thus, i hese equi emen s a e me , an image wi h 900 × 900 pixels and alpha channel could be uploaded and i will no be anscoded by Twi e . Thus, he ecei e applica ion will be able o e ie e he embedded in o ma ion lawlessly. Gi en ha a pixel is composed o 4 by es (ARGB/RGBA), a maximum o 900 × 900 =810,000 alpha-channel by es a e a ailable. Howe e , no all o hose by es would be ac ual biomedical in o ma ion. Fi s , he begin PGP and end PGP lines, he e sion line, he digi al signa u e and he a o emen ioned edundancy check shall be deduc ed (95 by es). The emaining da a a e encoded in Radix-64. In such encoding, 4*(n/3) cha ac e s a e needed o ep esen n by es, and his needs o be ounded up o a mul iple o 4. In his case, 1 by e is needed o padding. A e decoding, he esul ing da a include he session key enc yp ed wi h he RSA algo i hm (in ou p oo -o -concep , once enc yp ed, i s leng h is 2048 bi s, ha is, 256 by es) and he biomedical da a enc yp ed wi h he AES session key. AES wo ks in blocks, in ou case o 128 bi s (16 by es). The e o e, some padding may be needed. In his si ua ion, 4 padding by es a e equi ed. A he end, a maximum o 607,168 by es o biomedical da a would be a ailable. The amoun o biomedical da a could i in app oxima ely 600 kB depends on he da a hemsel es and he medical s anda d selec ed, i any. Fo example, he size o he HL7-complian message gene a ed in he p oo o concep (including weigh , hea a e, oxygen sa u a ion and blood p essu e) is jus 439 by es in HL7- o ma ed plain ex , 1035 by es a e enc yp ing and encoding. In a 900 × 900 image, i will dis o only he i s ow and pa ly he second ow (ou o 900 ows). A non-comp essed SCP-ECG ile (12 ECG leads, 1000 samples/second, 2 by es/sample, 10 s) is jus 240 kB o ECG da a, plus a ew by es o SCP-ECG me ada a. A numbe o comp ession echniques could be applied o enable la ge egis a ion imes. Fo he case o digi al images, a DICOM ile would also ha e some me ada a, bu a pic u e o 600 kB would p obably ha e enough quali y Elec onics 2020,9, 2208 21 o 26 o a elemoni o ing scena io (e.g., elede ma ology). I is wo h no ing ha DICOM i sel also suppo s image comp ession using JPEG2000 [ 56 ], and i could be used in e nally. Al hough he e is lack o consensus abou he ole able deg ee o comp ession, JPEG2000 ha e been epo ed o allow comp ession a ios anging 30:1–50:1 wi hou a ec ing he clinical quali y. E en ha could be enhanced by selec ing an op imized, ad-hoc pa ame iza ion o he speci ic medical use case [57]. Thus, wi h a 40:1 comp ession a io, a 600 kB comp essed image would mean a 24 MB aw image (8 megapixels RGB), which should be enough o a elede ma ology consul a ion. Fu he mo e, his is conside ing jus one wee . Na u ally, mo e han one wee could be used, enabling he ansmission o la ge amoun s o da a (e en he whole EHR) in a ew wee s. The size o an EHR depends on a a ie y o ac o s. As a e e ence, in a 2011 epo o he Be h Is ael Deaconess Medical Cen e , a eaching hospi al o Ha a d Medical School, i was published ha hey gene a e 1 e aby e o clinical ex da a (s uc u ed and uns uc u ed) pe yea and 19 e aby e o image da a pe yea [ 58 ]. Wi h 250,000 ac i e pa ien s a ha ime, ha means 80 megaby es pe pa ien pe yea . Tha ansla es o app oxima ely 138 wee s pe pa ien pe yea , ha is, one wee pe pa ien e e y 2–3 days. • Speed: The speed o he whole p ocedu e depends on a a ie y o ac o s. Fo example, he p ocesso , he p og amming language, he p og amming coding e iciency, he amoun o da a o be embedded, he size o he image, he embedding algo i hms and he size o he keys, among o he s. Rega ding he c yp og aphy algo i hms, he es da a published in [ 59 ] ha e been used as a e e ence. Such es s we e un wi h an In el Co e 2 a 1.83 GHz (simila o cu en mobile de ices). The algo i hms selec ed a e hose compa able o ou p oo o concep : AES (128-bi key) and RSA (2048-bi key). The esul s a e shown in Table 2 o he wo a o emen ioned scena ios. Such able also shows he ime equi ed o encoding in Radix-64, conside ing he same 1.83 GHz p ocesso . The speed used o he calcula ions is 2 cycles/by e, which is a ypical speed o base64 encoding/decoding, al hough i could be up o en imes as e using ec o ins uc ions [ 60 ]. The da a show ha enc yp ing and encoding is a ma e o milliseconds (sub o al 1, ow numbe 05 in Table 2), e en o ~600 kB o da a. The mos ime-consuming ask would be he RSA enc yp ion ( ow 02 in Table 2) o bo h scena ios. As ega ds he ime equi ed o embedding, he e a e no publicly a ailable da a, because his is no a s anda d algo i hm. The au ho s ha e pe o med a pool o es s unde he ollowing condi ions. The p ocess measu ed includes opening a bi map image, se ing up he necessa y a iables, modi y he equi ed alpha-channel by es and gene a e a comp essed ile in PNG o ma in ARGB/RBGA. Fi s , he sys em was es ed o he small-scale elemoni o ing scena io. Mo e speci ically, 1035 by es (co esponding o he size o he enc yp ed HL7-complian message) we e embedded in o he alpha channel o he dog pic u e in Figu e 4b, es ing wo sizes: 900 × 900 pixels and a escaled e sion o 225 × 225 pixels (exac ly 16 imes less pixels). Secondly, we pe o med wo es s (one pe each e sion o he embedding algo i hm) using all space a ailable ( 900 ×900 alpha by es). The a ionale o es ing wo di e en e sions o he embedding algo i hm is ha he PNG comp ession uses DEFLATE [ 61 ], a lossless comp essed da a o ma in ol ing a combina ion o Lempel–Zi -77 comp ession algo i hm and Hu man coding. This implies ha as e comp ession could be achie ed o images wi h small a ia ions o colo . In o he wo ds, he highe he anspa ency, he as e he comp ession. Con e sely, he image would be noisie and he e o e less iendly. The es s we e un in a cu en (as o 2019), mid- ange mobile phone wi h an oc a-co e MediaTek Helio G90T, including 2 ARM Co ex-A76 a 2.05 GHz and 6 ARM Co ex-A55 a 2.0 GHz, 6 GB o RAM and unning And oid 9.0 (PPR1.180610.011). We pe o med 10 execu ions pe es and calcula ed he a e age ime and he s anda d de ia ion. This p o ides he eade wi h a no ion o he cen al alue o he esul s (a i hme ic mean) and he amoun o dispe sion o he se o esul s (s anda d de ia ion). Th oughou he pape , he esul s a e exp essed as Elec onics 2020,9, 2208 22 o 26 “mean ±s anda d_de ia ion”. The esul s a e shown in Table 2. In gene al, he s anda d de ia ion is low compa ed o he a e age. This sugges s ha he da a a e clus e ed a ound he mean. The embedding is as ( ow 12 in Table 2) o bo h small-scale and bounda y scena ios, aking up less han 30 ms in any case. I is pa icula ly as o he smalle image, whe e i needs only 3.7 ± 0.5 ms. When compa ing he wo embedding algo i hms o he bounda y scena io, we can obse e ha he shi ing p ocess i sel ( ha is, adding 0x85 o each by e) only adds 0.3 ms (5.6 ± 0.5 ms s. 5.3 ± 0.5 ms, ow 11 in Table 2). Fo he small-scale scena io, he wo embedding algo i hms we e no es ed, as hey would beha e simila ly, since only a ew by es a e being modi ied, and hus he image emains la gely una ec ed (see zoomed images in ow 07 in Table 2). As ega ds he PNG comp ession, i can be seen ha i depends la gely on he size o he image (38.1 ± 0.6 ms a 225x255 s. he es , se e al imes slowe , a 900 × 900, ow 13 in Table 2). The o he ac o a ec ing he PNG comp ession ime is he e sion o he embedding algo i hm. The comp ession o he shi ed e sion is slowe compa ed o he non-shi ed one (703.5 ± 4.2 ms s. 548.5 ± 3.8 ms, ow 13 in Table 2). On he o he hand, he image is clea e , which could imp o e use s’ engagemen ( ow 07 in Table 2). The da a show ha he bo leneck o he whole p ocedu e is he PNG comp ession ( ow 13 in Table 2). App oxima ely 80-95% o he o al ime ( ow 14 in Table 2) is spen on he PNG comp ession. In hese es s, we use he buil -in comp esso p o ided by And oid, which is single- h eaded. I is a guably easible o pa allelize he comp ession p ocess, achie ing a educ ion o ime ha would scale linea ly wi h he numbe o co es o he machine. Besides he co es o he cen al p ocessing uni , mobile phones nowadays also inco po a e mul i-co e g aphic p ocessing uni s, which could also be used o pa allelized comp ession. To he bes o ou knowledge, he e is no And oid lib a y a ailable able o pe o m a pa allel comp ession o PNG iles (a he momen o w i ing). The e exis , howe e , Ja a-based pa allel comp esso s o GZIP [ 62 ], a ile o ma simila o PNG, since i is also based on DEFLATE. Ne e heless, p og amming such a comp esso alls ou o he scope o his pape . As a conclusion, o bo h he small-scale elemoni o ing scena io and he bounda y scena io, he whole p ocess could be pe o med a he as (less han 1 s in any case). I can be ca ied ou conside ably as e wi h smalle images: 48.2 ± 0.9 ms (225 × 225) s. 719.6 ± 9.6 ms (900 × 900). In addi ion, using he non-shi ed algo i hm, he p ocess can be pe o med as e in he bounda y scena io o he de imen o noisie images. In any case, he esul s show ha he speed would no be a c i ical issue o mos mHeal h scena ios. Table 2. Speed and size analysis. Row Scena io Small-Scale Bounda y 01 Plain ex (biomedical) da a (by es) 439 607,168 02 RSA enc yp ion (ms) 6.370 03 AES se -up and enc yp ion (ms) 0.004 5.309 04 Radix-64 encoding (ms) 0.001 0.664 05 Sub o al 1: enc yp ion and encoding (ms) 6.375 12.343 06 Embedding Algo i hm Ve sion Shi ed Shi ed Shi ed No shi ed 07 Zoomed (uppe - igh zone) image anspa ency o e iew Elec onics 2020, 9, x FOR PEER REVIEW 22 o 26 as hey would beha e simila ly, since only a ew by es a e being modi ied, and hus he image emains la gely una ec ed (see zoomed images in ow 07 in Table 2). As ega ds he PNG comp ession, i can be seen ha i depends la gely on he size o he image (38.1 ± 0.6 ms a 225x255 s. he es , se e al imes slowe , a 900 × 900, ow 13 in Table 2). The o he ac o a ec ing he PNG comp ession ime is he e sion o he embedding algo i hm. The comp ession o he shi ed e sion is slowe compa ed o he non-shi ed one (703.5 ± 4.2 ms s. 548.5 ± 3.8 ms, ow 13 in Table 2). On he o he hand, he image is clea e , which could imp o e use s’ engagemen ( ow 07 in Table 2). The da a show ha he bo leneck o he whole p ocedu e is he PNG comp ession ( ow 13 in Table 2). App oxima ely 80-95% o he o al ime ( ow 14 in Table 2) is spen on he PNG comp ession. In hese es s, we use he buil -in comp esso p o ided by And oid, which is single- h eaded. I is a guably easible o pa allelize he comp ession p ocess, achie ing a educ ion o ime ha would scale linea ly wi h he numbe o co es o he machine. Besides he co es o he cen al p ocessing uni , mobile phones nowadays also inco po a e mul i-co e g aphic p ocessing uni s, which could also be used o pa allelized comp ession. To he bes o ou knowledge, he e is no And oid lib a y a ailable able o pe o m a pa allel comp ession o PNG iles (a he momen o w i ing). The e exis , howe e , Ja a-based pa allel comp esso s o GZIP [62], a ile o ma simila o PNG, since i is also based on DEFLATE. Ne e heless, p og amming such a comp esso alls ou o he scope o his pape . As a conclusion, o bo h he small-scale elemoni o ing scena io and he bounda y scena io, he whole p ocess could be pe o med a he as (less han 1 s in any case). I can be ca ied ou conside ably as e wi h smalle images: 48.2 ± 0.9 ms (225 × 225) s. 719.6 ± 9.6 ms (900 × 900). In addi ion, using he non-shi ed algo i hm, he p ocess can be pe o med as e in he bounda y scena io o he de imen o noisie images. In any case, he esul s show ha he speed would no be a c i ical issue o mos mHeal h scena ios. Table 2. Speed and size analysis. Row Scena io Small-Scale Bounda y 01 Plain ex (biomedical) da a (by es) 439 607,168 02 RSA enc yp ion (ms) 6.370 03 AES se -up and enc yp ion (ms) 0.004 5.309 04 Radix-64 encoding (ms) 0.001 0.664 05 Sub o al 1: enc yp ion and encoding (ms) 6.375 12.343 06 Embedding Algo i hm Ve sion Shi ed Shi ed Shi ed No shi ed 07 Zoomed (uppe - igh zone) image anspa ency o e iew 08 Image dimension (wid h × heigh in pixels) 225 × 225 900 × 900 09 By es embedded (by es) 1035 900 × 900 = 810,000 10 Embedding se up (ms) 3.6 ± 0.5 20.9 ± 1.2 24.3 ± 3.2 22.3 ± 1.8 11 Embedding (ms) 0.1 ± 0.3 3.9 ± 0.9 5.6 ± 0.5 5.3 ± 0.5 12 Embedding sub o al (ms) 3.7 ± 0.5 24.8 ± 1.9 29.9 ± 3.3 27.6 ± 1.1 13 PNG comp ession (ms) 38.1 ± 0.6 688.4 ± 9.1 703.5 ± 4.2 548.5 ± 3.8 14 % PNG comp ession (100 * ow 13/ ow 16) 79.1 95.7 94.3 93.2 15 Sub o al 2: embedding and comp ession (ms) 41.8 ± 0.9 713.2 ± 9.6 733.4 ± 5.2 576.1 ± 4.1 16 TOTAL TIME: sub o al 1 + sub o al 2 (ms) 48.2 ± 0.9 719.6 ± 9.6 745.7 ± 5.2 588.4 ± 4.1 As a inal e lec ion on Sec ion 4.2, i is wo h no ing ha he elemen s selec ed o a speci ic p oo o concep can be changed independen ly. I he designe decide o use Facebook ins ead o Twi e , he o he pa icula selec ions (HL7, openPGP, o he embedding algo i hms) would s ill be alid. 5. Conclusions Elec onics 2020, 9, x FOR PEER REVIEW 22 o 26 as hey would beha e simila ly, since only a ew by es a e being modi ied, and hus he image emains la gely una ec ed (see zoomed images in ow 07 in Table 2). As ega ds he PNG comp ession, i can be seen ha i depends la gely on he size o he image (38.1 ± 0.6 ms a 225x255 s. he es , se e al imes slowe , a 900 × 900, ow 13 in Table 2). The o he ac o a ec ing he PNG comp ession ime is he e sion o he embedding algo i hm. The comp ession o he shi ed e sion is slowe compa ed o he non-shi ed one (703.5 ± 4.2 ms s. 548.5 ± 3.8 ms, ow 13 in Table 2). On he o he hand, he image is clea e , which could imp o e use s’ engagemen ( ow 07 in Table 2). The da a show ha he bo leneck o he whole p ocedu e is he PNG comp ession ( ow 13 in Table 2). App oxima ely 80-95% o he o al ime ( ow 14 in Table 2) is spen on he PNG comp ession. In hese es s, we use he buil -in comp esso p o ided by And oid, which is single- h eaded. I is a guably easible o pa allelize he comp ession p ocess, achie ing a educ ion o ime ha would scale linea ly wi h he numbe o co es o he machine. Besides he co es o he cen al p ocessing uni , mobile phones nowadays also inco po a e mul i-co e g aphic p ocessing uni s, which could also be used o pa allelized comp ession. To he bes o ou knowledge, he e is no And oid lib a y a ailable able o pe o m a pa allel comp ession o PNG iles (a he momen o w i ing). The e exis , howe e , Ja a-based pa allel comp esso s o GZIP [62], a ile o ma simila o PNG, since i is also based on DEFLATE. Ne e heless, p og amming such a comp esso alls ou o he scope o his pape . As a conclusion, o bo h he small-scale elemoni o ing scena io and he bounda y scena io, he whole p ocess could be pe o med a he as (less han 1 s in any case). I can be ca ied ou conside ably as e wi h smalle images: 48.2 ± 0.9 ms (225 × 225) s. 719.6 ± 9.6 ms (900 × 900). In addi ion, using he non-shi ed algo i hm, he p ocess can be pe o med as e in he bounda y scena io o he de imen o noisie images. In any case, he esul s show ha he speed would no be a c i ical issue o mos mHeal h scena ios. Table 2. Speed and size analysis. Row Scena io Small-Scale Bounda y 01 Plain ex (biomedical) da a (by es) 439 607,168 02 RSA enc yp ion (ms) 6.370 03 AES se -up and enc yp ion (ms) 0.004 5.309 04 Radix-64 encoding (ms) 0.001 0.664 05 Sub o al 1: enc yp ion and encoding (ms) 6.375 12.343 06 Embedding Algo i hm Ve sion Shi ed Shi ed Shi ed No shi ed 07 Zoomed (uppe - igh zone) image anspa ency o e iew 08 Image dimension (wid h × heigh in pixels) 225 × 225 900 × 900 09 By es embedded (by es) 1035 900 × 900 = 810,000 10 Embedding se up (ms) 3.6 ± 0.5 20.9 ± 1.2 24.3 ± 3.2 22.3 ± 1.8 11 Embedding (ms) 0.1 ± 0.3 3.9 ± 0.9 5.6 ± 0.5 5.3 ± 0.5 12 Embedding sub o al (ms) 3.7 ± 0.5 24.8 ± 1.9 29.9 ± 3.3 27.6 ± 1.1 13 PNG comp ession (ms) 38.1 ± 0.6 688.4 ± 9.1 703.5 ± 4.2 548.5 ± 3.8 14 % PNG comp ession (100 * ow 13/ ow 16) 79.1 95.7 94.3 93.2 15 Sub o al 2: embedding and comp ession (ms) 41.8 ± 0.9 713.2 ± 9.6 733.4 ± 5.2 576.1 ± 4.1 16 TOTAL TIME: sub o al 1 + sub o al 2 (ms) 48.2 ± 0.9 719.6 ± 9.6 745.7 ± 5.2 588.4 ± 4.1 As a inal e lec ion on Sec ion 4.2, i is wo h no ing ha he elemen s selec ed o a speci ic p oo o concep can be changed independen ly. I he designe decide o use Facebook ins ead o Twi e , he o he pa icula selec ions (HL7, openPGP, o he embedding algo i hms) would s ill be alid. 5. Conclusions Elec onics 2020, 9, x FOR PEER REVIEW 22 o 26 as hey would beha e simila ly, since only a ew by es a e being modi ied, and hus he image emains la gely una ec ed (see zoomed images in ow 07 in Table 2). As ega ds he PNG comp ession, i can be seen ha i depends la gely on he size o he image (38.1 ± 0.6 ms a 225x255 s. he es , se e al imes slowe , a 900 × 900, ow 13 in Table 2). The o he ac o a ec ing he PNG comp ession ime is he e sion o he embedding algo i hm. The comp ession o he shi ed e sion is slowe compa ed o he non-shi ed one (703.5 ± 4.2 ms s. 548.5 ± 3.8 ms, ow 13 in Table 2). On he o he hand, he image is clea e , which could imp o e use s’ engagemen ( ow 07 in Table 2). The da a show ha he bo leneck o he whole p ocedu e is he PNG comp ession ( ow 13 in Table 2). App oxima ely 80-95% o he o al ime ( ow 14 in Table 2) is spen on he PNG comp ession. In hese es s, we use he buil -in comp esso p o ided by And oid, which is single- h eaded. I is a guably easible o pa allelize he comp ession p ocess, achie ing a educ ion o ime ha would scale linea ly wi h he numbe o co es o he machine. Besides he co es o he cen al p ocessing uni , mobile phones nowadays also inco po a e mul i-co e g aphic p ocessing uni s, which could also be used o pa allelized comp ession. To he bes o ou knowledge, he e is no And oid lib a y a ailable able o pe o m a pa allel comp ession o PNG iles (a he momen o w i ing). The e exis , howe e , Ja a-based pa allel comp esso s o GZIP [62], a ile o ma simila o PNG, since i is also based on DEFLATE. Ne e heless, p og amming such a comp esso alls ou o he scope o his pape . As a conclusion, o bo h he small-scale elemoni o ing scena io and he bounda y scena io, he whole p ocess could be pe o med a he as (less han 1 s in any case). I can be ca ied ou conside ably as e wi h smalle images: 48.2 ± 0.9 ms (225 × 225) s. 719.6 ± 9.6 ms (900 × 900). In addi ion, using he non-shi ed algo i hm, he p ocess can be pe o med as e in he bounda y scena io o he de imen o noisie images. In any case, he esul s show ha he speed would no be a c i ical issue o mos mHeal h scena ios. Table 2. Speed and size analysis. Row Scena io Small-Scale Bounda y 01 Plain ex (biomedical) da a (by es) 439 607,168 02 RSA enc yp ion (ms) 6.370 03 AES se -up and enc yp ion (ms) 0.004 5.309 04 Radix-64 encoding (ms) 0.001 0.664 05 Sub o al 1: enc yp ion and encoding (ms) 6.375 12.343 06 Embedding Algo i hm Ve sion Shi ed Shi ed Shi ed No shi ed 07 Zoomed (uppe - igh zone) image anspa ency o e iew 08 Image dimension (wid h × heigh in pixels) 225 × 225 900 × 900 09 By es embedded (by es) 1035 900 × 900 = 810,000 10 Embedding se up (ms) 3.6 ± 0.5 20.9 ± 1.2 24.3 ± 3.2 22.3 ± 1.8 11 Embedding (ms) 0.1 ± 0.3 3.9 ± 0.9 5.6 ± 0.5 5.3 ± 0.5 12 Embedding sub o al (ms) 3.7 ± 0.5 24.8 ± 1.9 29.9 ± 3.3 27.6 ± 1.1 13 PNG comp ession (ms) 38.1 ± 0.6 688.4 ± 9.1 703.5 ± 4.2 548.5 ± 3.8 14 % PNG comp ession (100 * ow 13/ ow 16) 79.1 95.7 94.3 93.2 15 Sub o al 2: embedding and comp ession (ms) 41.8 ± 0.9 713.2 ± 9.6 733.4 ± 5.2 576.1 ± 4.1 16 TOTAL TIME: sub o al 1 + sub o al 2 (ms) 48.2 ± 0.9 719.6 ± 9.6 745.7 ± 5.2 588.4 ± 4.1 As a inal e lec ion on Sec ion 4.2, i is wo h no ing ha he elemen s selec ed o a speci ic p oo o concep can be changed independen ly. I he designe decide o use Facebook ins ead o Twi e , he o he pa icula selec ions (HL7, openPGP, o he embedding algo i hms) would s ill be alid. 5. Conclusions Elec onics 2020, 9, x FOR PEER REVIEW 22 o 26 as hey would beha e simila ly, since only a ew by es a e being modi ied, and hus he image emains la gely una ec ed (see zoomed images in ow 07 in Table 2). As ega ds he PNG comp ession, i can be seen ha i depends la gely on he size o he image (38.1 ± 0.6 ms a 225x255 s. he es , se e al imes slowe , a 900 × 900, ow 13 in Table 2). The o he ac o a ec ing he PNG comp ession ime is he e sion o he embedding algo i hm. The comp ession o he shi ed e sion is slowe compa ed o he non-shi ed one (703.5 ± 4.2 ms s. 548.5 ± 3.8 ms, ow 13 in Table 2). On he o he hand, he image is clea e , which could imp o e use s’ engagemen ( ow 07 in Table 2). The da a show ha he bo leneck o he whole p ocedu e is he PNG comp ession ( ow 13 in Table 2). App oxima ely 80-95% o he o al ime ( ow 14 in Table 2) is spen on he PNG comp ession. In hese es s, we use he buil -in comp esso p o ided by And oid, which is single- h eaded. I is a guably easible o pa allelize he comp ession p ocess, achie ing a educ ion o ime ha would scale linea ly wi h he numbe o co es o he machine. Besides he co es o he cen al p ocessing uni , mobile phones nowadays also inco po a e mul i-co e g aphic p ocessing uni s, which could also be used o pa allelized comp ession. To he bes o ou knowledge, he e is no And oid lib a y a ailable able o pe o m a pa allel comp ession o PNG iles (a he momen o w i ing). The e exis , howe e , Ja a-based pa allel comp esso s o GZIP [62], a ile o ma simila o PNG, since i is also based on DEFLATE. Ne e heless, p og amming such a comp esso alls ou o he scope o his pape . As a conclusion, o bo h he small-scale elemoni o ing scena io and he bounda y scena io, he whole p ocess could be pe o med a he as (less han 1 s in any case). I can be ca ied ou conside ably as e wi h smalle images: 48.2 ± 0.9 ms (225 × 225) s. 719.6 ± 9.6 ms (900 × 900). In addi ion, using he non-shi ed algo i hm, he p ocess can be pe o med as e in he bounda y scena io o he de imen o noisie images. In any case, he esul s show ha he speed would no be a c i ical issue o mos mHeal h scena ios. Table 2. Speed and size analysis. Row Scena io Small-Scale Bounda y 01 Plain ex (biomedical) da a (by es) 439 607,168 02 RSA enc yp ion (ms) 6.370 03 AES se -up and enc yp ion (ms) 0.004 5.309 04 Radix-64 encoding (ms) 0.001 0.664 05 Sub o al 1: enc yp ion and encoding (ms) 6.375 12.343 06 Embedding Algo i hm Ve sion Shi ed Shi ed Shi ed No shi ed 07 Zoomed (uppe - igh zone) image anspa ency o e iew 08 Image dimension (wid h × heigh in pixels) 225 × 225 900 × 900 09 By es embedded (by es) 1035 900 × 900 = 810,000 10 Embedding se up (ms) 3.6 ± 0.5 20.9 ± 1.2 24.3 ± 3.2 22.3 ± 1.8 11 Embedding (ms) 0.1 ± 0.3 3.9 ± 0.9 5.6 ± 0.5 5.3 ± 0.5 12 Embedding sub o al (ms) 3.7 ± 0.5 24.8 ± 1.9 29.9 ± 3.3 27.6 ± 1.1 13 PNG comp ession (ms) 38.1 ± 0.6 688.4 ± 9.1 703.5 ± 4.2 548.5 ± 3.8 14 % PNG comp ession (100 * ow 13/ ow 16) 79.1 95.7 94.3 93.2 15 Sub o al 2: embedding and comp ession (ms) 41.8 ± 0.9 713.2 ± 9.6 733.4 ± 5.2 576.1 ± 4.1 16 TOTAL TIME: sub o al 1 + sub o al 2 (ms) 48.2 ± 0.9 719.6 ± 9.6 745.7 ± 5.2 588.4 ± 4.1 As a inal e lec ion on Sec ion 4.2, i is wo h no ing ha he elemen s selec ed o a speci ic p oo o concep can be changed independen ly. I he designe decide o use Facebook ins ead o Twi e , he o he pa icula selec ions (HL7, openPGP, o he embedding algo i hms) would s ill be alid. 5. Conclusions 08 Image dimension (wid h ×heigh in pixels) 225 ×225 900 ×900 09 By es embedded (by es) 1035 900 ×900 =810,000 10 Embedding se up (ms) 3.6 ±0.5 20.9 ±1.2 24.3 ±3.2 22.3 ±1.8 11 Embedding (ms) 0.1 ±0.3 3.9 ±0.9 5.6 ±0.5 5.3 ±0.5 12 Embedding sub o al (ms) 3.7 ±0.5 24.8 ±1.9 29.9 ±3.3 27.6 ±1.1 13 PNG comp ession (ms) 38.1 ±0.6 688.4 ±9.1 703.5 ±4.2 548.5 ±3.8 Elec onics 2020,9, 2208 23 o 26 Table 2. Con . Row Scena io Small-Scale Bounda y 14 % PNG comp ession (100 * ow 13/ ow 16) 79.1 95.7 94.3 93.2 15 Sub o al 2: embedding and comp ession (ms) 41.8 ±0.9 713.2 ±9.6 733.4 ±5.2 576.1 ±4.1 16 TOTAL TIME: sub o al 1 +sub o al 2 (ms) 48.2 ±0.9 719.6 ±9.6 745.7 ±5.2 588.4 ±4.1 As a inal e lec ion on Sec ion 4.2, i is wo h no ing ha he elemen s selec ed o a speci ic p oo o concep can be changed independen ly. I he designe decide o use Facebook ins ead o Twi e , he o he pa icula selec ions (HL7, openPGP, o he embedding algo i hms) would s ill be alid. 5. Conclusions In his pape , a gene ic mH3S a chi ec u e has been p oposed. Such a chi ec u e p o ides use s wi h an enhanced heal hca e se ice. The no el y o his app oach can be summa ized as ollows: • No el a chi ec u e: Ins ead o a clien -se e a chi ec u e o a cloud-based a chi ec u e, we p opose an end- o-end sys em ha le e ages online social ne wo ks as a backbone. • Empowe ed use s and pa ien s: Use s do no ely on anyone o c ea e a secu e, p i a e communica ion channel. They decide wha o sha e and wi h whom. • Use - iendly way: A ac i e and ela able media objec s (images, ideos) wi h biomedical da a embedded a e sha ed h ough a social media ne wo k. • S aigh o wa d deploymen : Use s only need o ins all a mobile applica ion and pe o m some mino con igu a ion. • A o dable: The use s a e no asked o spend any money o use he sys em. Only a mobile phone wi h in e ne connec ion is equi ed. • High up ime a ailabili y: The sys em le e ages online social ne wo ks as a backbone. Thus, he se e s a e almos always up. • Imp o ed secu i y and p i acy: This is due o he secu i y en elope, based on a hyb id c yp osys em, he e o e combining he con enience o public-key app oaches wi h he e iciency o symme ic-key schemes. Social ne wo ks con ey he in o ma ion, bu no e en hey a e able o ead he biomedical da a a elling h ough hei se e s. • Reduced added complexi y: Use s a e equi ed o manage some key- ela ed aspec s, bu his is common p ac ice o cu en use s o sma phones and applica ions and i could be ca ied ou easily and swi ly. • Augmen ed in eg abili y: This is p o ided by he in e nal suppo o medical in e ope abili y s anda ds. Addi ionally, a echnical p oo -o -concep implemen a ion o such a chi ec u e has been de eloped by selec ing a speci ic social media (Twi e ), a secu i y en elope (openPGP), an in e ope abili y s anda d (HL7) as well as a speci ic embedding algo i hm. To accomplish such a sys em, wo And oid applica ions we e de eloped: one o use s/pa ien s and he o he o o mal/in o mal ca egi e s. This implemen a ion demons a es he easibili y o he pla o m. The es s show ha he p ocess is as : less han 1 s, e en o p epa ing ( ha is, enc yp ion, encoding and embedding) ~600 kB o biomedical da a. Thus, he addi ional complexi y o he p ocedu e does no en ail imp ac ical delays, and he e o e, he pla o m can be conside ed as enough o mos mHeal h elemoni o ing se ices. As a inal e lec ion, i can be highligh ed ha , al hough he a chi ec u e p esen ed and discussed in his manusc ip has been mo i a ed by a biomedical con ex , i could ce ainly be applied o o he con ex s. Fo example, by eplacing he medical in e ope abili y s anda d wi h ano he s anda d o da a o ma sui able o he applica ion. The e o e, he gene ic a chi ec u e p oposed he e can ac ually be seen as an enable o payload anspa ency. Elec onics 2020,9, 2208 24 o 26 Au ho Con ibu ions: Concep ualiza ion, J.D.T., Ó .J.R., and Á .A.; me hodology, J.D.T. and Ó .J.R.; so wa e, J.D.T. and M.M.-E.; alida ion, J.D.T.; o mal analysis, J.D.T. and Ó .J.R.; in es iga ion, J.D.T.; esou ces, J.D.T., J.G. and L.S.-A.; da a cu a ion, J.D.T., Ó .J.R. and M.M.-E.; w i ing—o iginal d a p epa a ion, J.D.T. and Ó .J.R.; w i ing— e iew and edi ing, J.D.T., Ó .J.R., M.M.-E., Á .A., J.G. and L.S.-A.; isualiza ion, J.D.T. and Ó .J.R.; supe ision, J.G. and L.S.-A.; p ojec adminis a ion, J.D.T., J.G. and L.S.-A.; unding acquisi ion, J.D.T., J.G. and L.S.-A. All au ho s ha e ead and ag eed o he published e sion o he manusc ip . Funding: This esea ch was unded by Public Uni e si y o Na a a (p ojec e e ence numbe PJUPNA29); Minis e io de Econom í a, Indus ia y Compe i i idad om Gobie no de España and Eu opean Regional De elopmen Fund ( e e ence numbe TIN2016-76770-R); Gobie no de A ag ó n (Re e ence G oup T31_20R); and FEDER 2014-2020 “Cons uyendo Eu opa desde A agón”. Con lic s o In e es : The au ho s decla e no con lic o in e es . Re e ences 1. Pew Resea ch Cen e Mobile Fac Shee . A ailable online: h p://www.pewin e ne .o g/ ac -shee /mobile/ (accessed on 7 Sep embe 2020). 2. Wo ld Heal h O ganiza ion (WHO) mHeal h. New Ho izons o Heal h h ough Mobile Technologies. A ailable online: h p://www.who.in /goe/publica ions/goe_mheal h_web.pd (accessed on 7 Sep embe 2020). 3. Adibi, S. Mobile Heal h: A Technology Road Map; Sp inge Publishing Company, Inc.: New Yo k, NY, USA, 2015; ISBN 978-3-319-12816-0. 4. Sil a, B.M.C.; Rod igues, J.J.P.C.; de la To e D í ez, I.; L ó pez-Co onado, M.; Saleem, K. 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