ScienceDi ec
A ailable online a www.sciencedi ec .com
P ocedia Compu e Science 176 (2020) 3255–3262
1877-0509 © 2020 The Au ho s. Published by Else ie B.V.
This is an open access a icle unde he CC BY-NC-ND license (h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0)
Pee - e iew unde esponsibili y o he scien i ic commi ee o he KES In e na ional.
10.1016/j.p ocs.2020.09.123
10.1016/j.p ocs.2020.09.123 1877-0509
© 2020 The Au ho s. Published by Else ie B.V.
This is an open access a icle unde he CC BY-NC-ND license (h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0)
Pee - e iew unde esponsibili y o he scien i ic commi ee o he KES In e na ional.
A ailable online a www.sciencedi ec .com
ScienceDi ec
P ocedia Compu e Science 00 (2020) 000–000
www.else ie .com/loca e/p ocedia
1877-0509 © 2019 The Au ho (s). Published by Else ie B.V.
This is an open access a icle unde he CC BY-NC-ND license (h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0/)
Pee - e iew unde esponsibili y o KES In e na ional.
24 h In e na ional Con e ence on Knowledge-Based and In elligen In o ma ion & Enginee ing
Sys ems
Can Vi ual Reali y be used as a signi ican s esso o s udies
using ECG?
Wilhelm Daniel Sche za,*, Vic o Co coba Magañab, Ral Seepolda,c,
Na i idad Ma ínez Mad idc,d Juan An onio O egae
aUbiqui ous Compu ing Lab HTWG Kons anz, Al ed-Wach el-S . 8, 78462 Kons anz, Ge many
bUni e si y o O iedo, O iedo 33003, Spain
cI.M. Secheno Fi s Moscow S a e Medical Uni e si y, 2-4, Bolshaya Pi ogo skaya s ., 119435 Moscow, Russian Fede a ion
dReu lingen Uni e si y, Al ebu gs . 150, 72762 Reul ingen, Ge many
eUni e si y o Se ille, A da. Reina Me cedes s/n, Se ille, Spain
Abs ac
In p e ious s udies, we used a me hod o de ec ing s ess ha was based exclusi ely on hea a e and ECG o di e en ia ion
be ween such si ua ions as men al s ess, physical ac i i y, elaxa ion, and es . As a esponse o he hea o hese si ua ions, we
obse ed di e en beha io in he Roo Mean Squa e o he Successi e di e ences hea bea s (RMSSD). This s udy aims o analyze
Vi ual Reali y ia a i ual eali y headse as an e ec i e s esso o u u e wo ks. The alue o he Roo Mean Squa e o he
Successi e Di e ences is an impo an ma ke o he pa asympa he ic e ec o on he hea and can p o ide in o ma ion abou
s ess. Fo hese measu emen s, he RR in e al was collec ed using a b eas bel . In hese s udies, we can obse e he Roo Mean
Squa e o he successi e di e ences hea bea s. Addi ional senso s o he analysis we e no used. We conduc ed expe imen s wi h
en subjec s ha had o d i e a simula o o 25 minu es using moni o s and 25 minu es using i ual eali y headse .Be o e s a ing
and a e inishing each simula ion, he subjec s had o comple e a su ey in which hey had o desc ibe hei men al s a e. The
expe imen esul s show ha d i ing using i ual eali y headse has some in luence on he hea a e and RMSSD, bu i does no
signi ican ly inc ease he s ess o d i ing.
© 2019 The Au ho (s). Published by Else ie B.V.
This is an open access a icle unde he CC BY-NC-ND license (h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0/)
Pee - e iew unde esponsibili y o KES In e na ional.
* Co esponding au ho . Tel.: +49-7531-206-698; ax: +49-7531-206-8698.
E-mail add ess: wsche z@h wg-kons anz.de
A ailable online a www.sciencedi ec .com
ScienceDi ec
P ocedia Compu e Science 00 (2020) 000–000
www.else ie .com/loca e/p ocedia
1877-0509 © 2019 The Au ho (s). Published by Else ie B.V.
This is an open access a icle unde he CC BY-NC-ND license (h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0/)
Pee - e iew unde esponsibili y o KES In e na ional.
24 h In e na ional Con e ence on Knowledge-Based and In elligen In o ma ion & Enginee ing
Sys ems
Can Vi ual Reali y be used as a signi ican s esso o s udies
using ECG?
Wilhelm Daniel Sche za,*, Vic o Co coba Magañab, Ral Seepolda,c,
Na i idad Ma ínez Mad idc,d Juan An onio O egae
aUbiqui ous Compu ing Lab HTWG Kons anz, Al ed-Wach el-S . 8, 78462 Kons anz, Ge many
bUni e si y o O iedo, O iedo 33003, Spain
cI.M. Secheno Fi s Moscow S a e Medical Uni e si y, 2-4, Bolshaya Pi ogo skaya s ., 119435 Moscow, Russian Fede a ion
dReu lingen Uni e si y, Al ebu gs . 150, 72762 Reul ingen, Ge many
eUni e si y o Se ille, A da. Reina Me cedes s/n, Se ille, Spain
Abs ac
In p e ious s udies, we used a me hod o de ec ing s ess ha was based exclusi ely on hea a e and ECG o di e en ia ion
be ween such si ua ions as men al s ess, physical ac i i y, elaxa ion, and es . As a esponse o he hea o hese si ua ions, we
obse ed di e en beha io in he Roo Mean Squa e o he Successi e di e ences hea bea s (RMSSD). This s udy aims o analyze
Vi ual Reali y ia a i ual eali y headse as an e ec i e s esso o u u e wo ks. The alue o he Roo Mean Squa e o he
Successi e Di e ences is an impo an ma ke o he pa asympa he ic e ec o on he hea and can p o ide in o ma ion abou
s ess. Fo hese measu emen s, he RR in e al was collec ed using a b eas bel . In hese s udies, we can obse e he Roo Mean
Squa e o he successi e di e ences hea bea s. Addi ional senso s o he analysis we e no used. We conduc ed expe imen s wi h
en subjec s ha had o d i e a simula o o 25 minu es using moni o s and 25 minu es using i ual eali y headse .Be o e s a ing
and a e inishing each simula ion, he subjec s had o comple e a su ey in which hey had o desc ibe hei men al s a e. The
expe imen esul s show ha d i ing using i ual eali y headse has some in luence on he hea a e and RMSSD, bu i does no
signi ican ly inc ease he s ess o d i ing.
© 2019 The Au ho (s). Published by Else ie B.V.
This is an open access a icle unde he CC BY-NC-ND license (h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0/)
Pee - e iew unde esponsibili y o KES In e na ional.
* Co esponding au ho . Tel.: +49-7531-206-698; ax: +49-7531-206-8698.
E-mail add ess: wsche z@h wg-kons anz.de
3256 Wilhelm Daniel Sche z e al. / P ocedia Compu e Science 176 (2020) 3255–3262
2 Wilhelm Daniel Sche z / P ocedia Compu e Science 00 (2020) 000–000
Keywo ds: S ess de ec ion ; ECG, d i ing ; hea a e ; ca dio ascula ; bio i al signal
1. In oduc ion
Awa eness abou heal h is o g ea impo ance in mode n socie y. Collec ing bio i al da a became an essen ial pa
o i , and as a esul , i changed he pe cep ion and unde s anding o s ess [1]. Nowadays, he e a e se e al
app oxima ions o he es ima ion o s ess. Cu en ly, he mos common app oaches o de ec ing s ess implemen
h ee di e en p inciples: The i s one uses su eys o sel - epo ques ionnai es o e alua e he men al s a e; he
second app oach uses labo a o y bioma ke s like ad enaline and co isol [2], beha io pa e n analysis [3], and he
la e app oach uses physiological pa ame e s like hea a e o skin conduc i i y [4] o s ess de ec ion. The app oach
ha was used in his expe imen uses a educed da a se ha sepa a es be ween mo e o less s ess while using he
simula ion ia moni o s o i ual eali y headse .
The main challenges o de ec ing s ess belong no only o i s de ec ion i sel bu also i s sepa a ion om o he
si ua ions like elaxa ion, physical ac i i y. Cu en ly, he e is a big choice o consume de ices and po able EGC
de ices ha measu e hea a e and moni o ac i i y, which could be used o s ess de ec ion. Ne e heless, he
challenge o sepa a ion emains. I is well known ha he e a e some long- e m e ec s o s ess on he ca dio ascula
sys em [5, 6, 7], s ess a ec s he immune esponse o he body [8], i can igge panic a acks [9], and i lowe s he
li e quali y [10, 11]. Addi ionally, s ess makes i di icul o cope wi h physical and men al demands [12, 13, 14], and
i has a ha m ul in luence on he de elopmen o b ain s uc u es [10]. Simpli ying, s ess could be conside ed o be a
nega i e in luence on heal h and li e quali y, so i is impo an o p ese e and quan i y i and educe he amoun o
s ess ha we expe ience. As an addi ional complica ion, we can name he misde ec ion o physical ac i i y as s ess.
By con as wi h s ess, physical ac i i y has posi i e long- e m e ec s such as change o he lipase composi ion o he
body [15] and imp o emen s in he ca dio ascula sys em. Like s ess, physical ac i i y has sho - e m e ec s. As we
could obse e in p e ious wo ks, many addi ional s esso s o in luence s change he hea 's beha io . As an example,
elaxa ion changes he hea a e and sys olic blood p essu e [16, 17]. This makes i essen ial o ind s esso s ha we
can use o collec di e en da ase s and imp o e s ess de ec ion.
Fo his wo k, i is essen ial o unde s and and o de ine s ess. In his case, we de ine s ess no as he peak o a
d ama ic e en bu as a eac ion o he si ua ions ha equi e a as esponse o ele a ed ac i i y o jus in unusual
si ua ions. We can conside ha s ess is a pa o ou daily li e; i is a mechanism ha helps us o e alua e unknown
and dange ous si ua ions and gi e as e esponses by inc easing he e iciency o ou eac ions. As an example, in
' igh o ligh ' si ua ions, s ess educes he ime o eac ing and decision-making, and as a consequence, in a
dange ous si ua ion, we choose be ween con on a ion o escape [18].
D i ing is a ypical daily ac i i y o many o us. A la ge amoun o s udies shows ha d i ing e iciency and sa e y
a e s ongly in luenced by emo ions and s ess le els o he d i e [19, 20, 21] . Se e al s udies p o e a s ong
ela ionship be ween a ic acciden s and s ess [22, 23]. Tha is why we ha e chosen his use case o he cu en
s udy, as i is a common ac i i y ha is easy and sa e o simula e.
2. Me hods and ma e ials
In he ollowing sec ion, we desc ibe he p o ocol ollowed du ing he expe imen and he ma e ials used. To eco d
he hea a e, ECG, and s ess, wo de ices we e used: he ches band Pola H101 and he w is band Empa ica E42.
Addi ionally, o measu e su ounding condi ions such as empe a u e, humidi y, and C02 le els du ing he expe imen ,
we applied he Ne a mo3 senso . The en i onmen condi ions we e no used in he measu emen o s ess because he
condi ions while he simula ion whe e simila and did no change much.
1 h ps://www.pola .com/de/p oduk e/accessoi es/he z equenz_senso _h10.
2 h ps://www.empa ica.com/ esea ch/e4/
3 h ps://www.ne a mo.com/en-us/wea he /wea he s a ion/indoo -module
Wilhelm Daniel Sche z e al. / P ocedia Compu e Science 176 (2020) 3255–3262 3257
2 Wilhelm Daniel Sche z / P ocedia Compu e Science 00 (2020) 000–000
Keywo ds: S ess de ec ion ; ECG, d i ing ; hea a e ; ca dio ascula ; bio i al signal
1. In oduc ion
Awa eness abou heal h is o g ea impo ance in mode n socie y. Collec ing bio i al da a became an essen ial pa
o i , and as a esul , i changed he pe cep ion and unde s anding o s ess [1]. Nowadays, he e a e se e al
app oxima ions o he es ima ion o s ess. Cu en ly, he mos common app oaches o de ec ing s ess implemen
h ee di e en p inciples: The i s one uses su eys o sel - epo ques ionnai es o e alua e he men al s a e; he
second app oach uses labo a o y bioma ke s like ad enaline and co isol [2], beha io pa e n analysis [3], and he
la e app oach uses physiological pa ame e s like hea a e o skin conduc i i y [4] o s ess de ec ion. The app oach
ha was used in his expe imen uses a educed da a se ha sepa a es be ween mo e o less s ess while using he
simula ion ia moni o s o i ual eali y headse .
The main challenges o de ec ing s ess belong no only o i s de ec ion i sel bu also i s sepa a ion om o he
si ua ions like elaxa ion, physical ac i i y. Cu en ly, he e is a big choice o consume de ices and po able EGC
de ices ha measu e hea a e and moni o ac i i y, which could be used o s ess de ec ion. Ne e heless, he
challenge o sepa a ion emains. I is well known ha he e a e some long- e m e ec s o s ess on he ca dio ascula
sys em [5, 6, 7], s ess a ec s he immune esponse o he body [8], i can igge panic a acks [9], and i lowe s he
li e quali y [10, 11]. Addi ionally, s ess makes i di icul o cope wi h physical and men al demands [12, 13, 14], and
i has a ha m ul in luence on he de elopmen o b ain s uc u es [10]. Simpli ying, s ess could be conside ed o be a
nega i e in luence on heal h and li e quali y, so i is impo an o p ese e and quan i y i and educe he amoun o
s ess ha we expe ience. As an addi ional complica ion, we can name he misde ec ion o physical ac i i y as s ess.
By con as wi h s ess, physical ac i i y has posi i e long- e m e ec s such as change o he lipase composi ion o he
body [15] and imp o emen s in he ca dio ascula sys em. Like s ess, physical ac i i y has sho - e m e ec s. As we
could obse e in p e ious wo ks, many addi ional s esso s o in luence s change he hea 's beha io . As an example,
elaxa ion changes he hea a e and sys olic blood p essu e [16, 17]. This makes i essen ial o ind s esso s ha we
can use o collec di e en da ase s and imp o e s ess de ec ion.
Fo his wo k, i is essen ial o unde s and and o de ine s ess. In his case, we de ine s ess no as he peak o a
d ama ic e en bu as a eac ion o he si ua ions ha equi e a as esponse o ele a ed ac i i y o jus in unusual
si ua ions. We can conside ha s ess is a pa o ou daily li e; i is a mechanism ha helps us o e alua e unknown
and dange ous si ua ions and gi e as e esponses by inc easing he e iciency o ou eac ions. As an example, in
' igh o ligh ' si ua ions, s ess educes he ime o eac ing and decision-making, and as a consequence, in a
dange ous si ua ion, we choose be ween con on a ion o escape [18].
D i ing is a ypical daily ac i i y o many o us. A la ge amoun o s udies shows ha d i ing e iciency and sa e y
a e s ongly in luenced by emo ions and s ess le els o he d i e [19, 20, 21] . Se e al s udies p o e a s ong
ela ionship be ween a ic acciden s and s ess [22, 23]. Tha is why we ha e chosen his use case o he cu en
s udy, as i is a common ac i i y ha is easy and sa e o simula e.
2. Me hods and ma e ials
In he ollowing sec ion, we desc ibe he p o ocol ollowed du ing he expe imen and he ma e ials used. To eco d
he hea a e, ECG, and s ess, wo de ices we e used: he ches band Pola H101 and he w is band Empa ica E42.
Addi ionally, o measu e su ounding condi ions such as empe a u e, humidi y, and C02 le els du ing he expe imen ,
we applied he Ne a mo3 senso . The en i onmen condi ions we e no used in he measu emen o s ess because he
condi ions while he simula ion whe e simila and did no change much.
1 h ps://www.pola .com/de/p oduk e/accessoi es/he z equenz_senso _h10.
2 h ps://www.empa ica.com/ esea ch/e4/
3 h ps://www.ne a mo.com/en-us/wea he /wea he s a ion/indoo -module
Wilhelm Daniel Sche z/ P ocedia Compu e Science 00 (2020) 000–000 3
2.1. Hea a e and ECG signal
The hea signal's ad an age is ha i can be acqui ed in a non-in asi e way, and he Hea Ra e Va iabili y (HRV)
co ela es wi h s ess. In his s udy, wo senso s we e used o measu e s ess: he ches band Pola H10 and he
w is band Empa ica E4. The e a e wo domains o how he hea a e a iabili y can be analyzed: by ime domain and
by equency domain.
Fo he ime domain analysis, quan i ying he mean and he s anda d de i a ion o wo consecu i e hea bea s
in e als has o be done. A hea bea in e al is de ined as RR In e al, and an R peak ep esen s he highes peak o a
hea bea on he QRS complex. An RR in e al is he ime be ween wo hea bea s. The used measu emen s o he
ime domain a e he ollowing: a e age RR in milliseconds (ms), s anda d de i a ion o consecu i e RR du ing he
expe imen (SDNN), a e age hea a e (HR) in ms, s anda d de i a ion hea a e (STD HR), he oo mean squa e o
successi e di e ences (RMSSD) and he pNN50 (%) ha indica es he p opo ion o consecu i e RR in e als wi h
he di e ence o mo e han 50ms. This alue dec eases when s ess inc eases.
Fo he equency domain analysis, we ha e o calcula e he powe o he espi a o y dependen highe equency
and he lowe equency componen s o he hea a e. Fo his, we use he ollowing measu emen : LF/HF indica es
he a ion o he low- equency powe (0.04-0.15 Hz) ha is modula ed by he sympa ic and pa asympa he ic ne ous
sys em and he high- equency powe (0.14-0.4 Hz) ela ed o pa asympa he ic ac i i y. This alue indica es a global
sympa ic agal balance [24]. High esul s o LF/HF indica e ha he sympa he ic sys em is dominan . This happens
when he e is ele a ed s ess.
Nowadays, he e is a ailable a wide ange o de ices ha enable he non-in asi e eco ding o he hea . One o
he mos popula me hods ha a e used in wea able de ices is pho o-ple hysmog aphy. This kind o de ice measu es
he blood olume pulse. The main d awback o his me hod is he sensi i i y o mo emen and he changes in he
de ice's con ac p essu e. [25]. An al e na i e ha also allows he non-in asi e measu emen o he hea a e and, a
he same ime, p o ides highe accu acy a e he ches bands wi h elec odes and ECG unc ion. [26] .
Pola H10 ha was used o his s udy belongs o he second g oup o he de ices and o e s simila unc ionali y
as an ECG Hol e [27].
2.2. D i ing simula o
Fo his s udy, we used he d i ing simula o 'Ci y Ca D i ing' [28]. The main easons o choosing his simula o
we e he ollowing: ealis ic d i ing expe ience based on ad anced ca physics, eal a ic ules, adjus able a ic
condi ions, ealis ic pedes ian and ca simula ion, and high-quali y g aphics simula o . Fo his expe imen , we ha e
chosen he scene 'Old dis ic ' because i cha ac e izes wi h na ow s ee s, simple c ossing, clea a ic pa e ns. The
so wa e simula o was execu ed on a d i ing simula o wi h cha ac e is ics, as shown in Table 1. Fo d i ing wi hou
i ual Reali y, h ee 27-inch sc eens we e used. To ope a e simula ion and o p o ide a ealis ic d i ing expe ience,
we used he s ee ing wheel Logi ech G24 wi h gea box and pedals. This s ee ing wheel also o e s o ce eedback.
This allows us o achie e an imme si e expe ience in he i ual en i onmen .
Table 1. Speci ica ions o he PC in which he d i ing simula o is un
Model
Alienwa e A ea-51 R4
P ocesso
In el Co e i7-7800X
Chipse
In el X299 PCH
Memo y
16 GB DDR4 2666 MHz
GPU
2 X Ge o ce 1080 TI SLI
S o age
128 GB SanDisk M.2
SSD
The d i ing pe o mance was eco ded wi h a specially de eloped p og am ha cap u es he o a ion o he s ee ing
wheel, he p essu e applied on he pedals, and he numbe o a ic in ac ions he es subjec s ealized.
3258 Wilhelm Daniel Sche z e al. / P ocedia Compu e Science 176 (2020) 3255–3262
4 Wilhelm Daniel Sche z / P ocedia Compu e Science 00 (2020) 000–000
2.3. Music empo
Music can in luence human beha io . Se e al s udies show ha e.g., as music educes he amoun o ime ha
cus ome s spend in supe ma ke s; in pubs, i makes people d ink hei be e ages as e [29, 30] o while d i ing as
music can inc ease he eadiness o d i e as e [31].
Fo his s udy, he pa icipan s lis ened o he music using noise-canceling headse s, inc easing he imme sion in o
a simula ion, and educing ex e nal in luences. Each pa icipan could con igu e he olume indi idually acco ding o
hei pe sonal p e e ences. Two playlis s we e c ea ed o he pa icipan s. The i s playlis consis s o low empo
composi ions (65-71 bpm), and he second playlis included songs wi h a as e empo (155-188 bpm). The audio was
ep oduced wi h a quali y o 320 bps. Adi ional o he music, he d i e hea s he sounds o he i ual en i onmen o
he d i ing simula o .
2.4. Su ey
Be o e s a ing o d i e, an ini ial su ey had o be comple ed by he pa icipan s, as well as he second su ey a e
d i ing. The i s su ey gi es in o ma ion abou he emo ional s a e, physical s a e, and he expe iences o he
pa icipan s. The inal su ey is aimed o collec he da a abou he emo ional and physiological s a e o he pa icipan s
a e comple ion o he d i ing exe cise and o obse e i he d i ing ask had any in luence on he d i e . Addi ional
ques ions in he inal su ey e e o he ealism o he simula ion, own pe cep ion o he d i ing pe o mance, and he
en i onmen pe cep ions such as empe a u e and noise. These addi ional ques ions allow us o compa e hei
subjec i e pe cep ion o he si ua ion wi h he measu ed da a and o ind ou whe he he simula o is ealis ic enough
and usable as a ool o collec ing da a.
2.5. P ocedu e desc ip ion
The s udy is composed o 6 pa s. Fi s , he pa icipan answe s he su ey and places he ches band and w i s band.
Then, he pa icipan si s on a sea and places he headse and s a s o lis en o Moza 's Sona a o Two Pianos in D
majo . This i s phase is used o elax he pa icipan and s abilize he senso s and de ices. A e his, he pa icipan
s a s d i ing o 25 minu es, and he hea signal, en i onmen cha ac e is ics, and d i ing a e eco ded. As soon as
he pa icipan s a s d i ing, he sys em p oposes a ou e ha he has o d i e. The p oposed ou e always has a leng h
o 5 km. The amoun o a ic is always he same and compa able. A coun e s a s a 20 poin s, o each in ac ion a
poin is aken, and i he coun e eaches 0 poin s, he ou e has o be es a ed. A e 25 minu es, he pa icipan can
es o 1-2 minu es. A e he pa icipan has se up com o ably and s a ed he VR, he VR headse a new ou e is
ini ialized wi h he segmen s o 5 km and 25 minu es. A e his, he pa icipan can es 1-2 minu es and has o answe
he inal su ey.
3. Resul s
A o al o 10 d i e s wi h an a e age age o 25.4 (max: 33, min: 20; s d. de .: 3.47) and d i ing expe ience o 7 o
8 yea s (max 15, min: 2, s d. de : 3.62) pa icipa ed in he expe imen . Fi s , he pa icipan pu on he senso s,
comple ed he ini ial su ey, and hen lis ened o Moza 's Sona a o Two Pianos in D majo using headphones. This
ack has been selec ed because i imp o es men al unc ion [32]. The objec i e o his phase is o be elaxed be o e
he d i ing es and o s abilize he senso s.
Pa icipan s d o e o 25 minu es. The d i e s had o comple e he ou es p oposed by he GPS o he d i ing
simula o . Each ou e has a leng h o 5 km, and i s le el o di icul y is compa able because he concen a ion o
ehicles and pedes ians is he same in all cases. The d i ing simula o assigns poin s o he pa icipan a he beginning
o he ou e. Each ime an in ac ion is commi ed, poin s a e deduc ed. When he sco e is ze o, he o she mus epea
he ou e. This allows he pa icipan o ocus on he d i ing ask as i in a eal en i onmen [33]. The d i ing ime is
25 minu es o ensu e ha he e is enough ime o he s ess da a o be alid [34]. A e wa d, he pa icipan s elaxed
o 5 minu es and s a ed he same es again, bu in his case, using i ual Reali y.
Wilhelm Daniel Sche z e al. / P ocedia Compu e Science 176 (2020) 3255–3262 3259
4 Wilhelm Daniel Sche z / P ocedia Compu e Science 00 (2020) 000–000
2.3. Music empo
Music can in luence human beha io . Se e al s udies show ha e.g., as music educes he amoun o ime ha
cus ome s spend in supe ma ke s; in pubs, i makes people d ink hei be e ages as e [29, 30] o while d i ing as
music can inc ease he eadiness o d i e as e [31].
Fo his s udy, he pa icipan s lis ened o he music using noise-canceling headse s, inc easing he imme sion in o
a simula ion, and educing ex e nal in luences. Each pa icipan could con igu e he olume indi idually acco ding o
hei pe sonal p e e ences. Two playlis s we e c ea ed o he pa icipan s. The i s playlis consis s o low empo
composi ions (65-71 bpm), and he second playlis included songs wi h a as e empo (155-188 bpm). The audio was
ep oduced wi h a quali y o 320 bps. Adi ional o he music, he d i e hea s he sounds o he i ual en i onmen o
he d i ing simula o .
2.4. Su ey
Be o e s a ing o d i e, an ini ial su ey had o be comple ed by he pa icipan s, as well as he second su ey a e
d i ing. The i s su ey gi es in o ma ion abou he emo ional s a e, physical s a e, and he expe iences o he
pa icipan s. The inal su ey is aimed o collec he da a abou he emo ional and physiological s a e o he pa icipan s
a e comple ion o he d i ing exe cise and o obse e i he d i ing ask had any in luence on he d i e . Addi ional
ques ions in he inal su ey e e o he ealism o he simula ion, own pe cep ion o he d i ing pe o mance, and he
en i onmen pe cep ions such as empe a u e and noise. These addi ional ques ions allow us o compa e hei
subjec i e pe cep ion o he si ua ion wi h he measu ed da a and o ind ou whe he he simula o is ealis ic enough
and usable as a ool o collec ing da a.
2.5. P ocedu e desc ip ion
The s udy is composed o 6 pa s. Fi s , he pa icipan answe s he su ey and places he ches band and w i s band.
Then, he pa icipan si s on a sea and places he headse and s a s o lis en o Moza 's Sona a o Two Pianos in D
majo . This i s phase is used o elax he pa icipan and s abilize he senso s and de ices. A e his, he pa icipan
s a s d i ing o 25 minu es, and he hea signal, en i onmen cha ac e is ics, and d i ing a e eco ded. As soon as
he pa icipan s a s d i ing, he sys em p oposes a ou e ha he has o d i e. The p oposed ou e always has a leng h
o 5 km. The amoun o a ic is always he same and compa able. A coun e s a s a 20 poin s, o each in ac ion a
poin is aken, and i he coun e eaches 0 poin s, he ou e has o be es a ed. A e 25 minu es, he pa icipan can
es o 1-2 minu es. A e he pa icipan has se up com o ably and s a ed he VR, he VR headse a new ou e is
ini ialized wi h he segmen s o 5 km and 25 minu es. A e his, he pa icipan can es 1-2 minu es and has o answe
he inal su ey.
3. Resul s
A o al o 10 d i e s wi h an a e age age o 25.4 (max: 33, min: 20; s d. de .: 3.47) and d i ing expe ience o 7 o
8 yea s (max 15, min: 2, s d. de : 3.62) pa icipa ed in he expe imen . Fi s , he pa icipan pu on he senso s,
comple ed he ini ial su ey, and hen lis ened o Moza 's Sona a o Two Pianos in D majo using headphones. This
ack has been selec ed because i imp o es men al unc ion [32]. The objec i e o his phase is o be elaxed be o e
he d i ing es and o s abilize he senso s.
Pa icipan s d o e o 25 minu es. The d i e s had o comple e he ou es p oposed by he GPS o he d i ing
simula o . Each ou e has a leng h o 5 km, and i s le el o di icul y is compa able because he concen a ion o
ehicles and pedes ians is he same in all cases. The d i ing simula o assigns poin s o he pa icipan a he beginning
o he ou e. Each ime an in ac ion is commi ed, poin s a e deduc ed. When he sco e is ze o, he o she mus epea
he ou e. This allows he pa icipan o ocus on he d i ing ask as i in a eal en i onmen [33]. The d i ing ime is
25 minu es o ensu e ha he e is enough ime o he s ess da a o be alid [34]. A e wa d, he pa icipan s elaxed
o 5 minu es and s a ed he same es again, bu in his case, using i ual Reali y.
Wilhelm Daniel Sche z/ P ocedia Compu e Science 00 (2020) 000–000 5
We ha e used he Sympa he ic Tone Index (SNS) [35] o compa e he s ess su e ed by he pa icipan when hey
a e d i ing using he d i ing simula o wi h and wi hou i ual Reali y. SNS index is calcula ed using Mean HR
(bpm), Bae sky’s s ess index, and LF powe no mal uni (n.u.). Figu e 1 cap u es he alues ob ained by he
pa icipan s wi hou and wi h i ual Reali y. The esul s show ha he e a e no signi ican di e ences in he s ess
le el when d i e s do no use i ual eali y (a e age SNS index = 0.898, SD = 1.23) wi h when hey do use i (a e age
SNS index = 0.784, SD = 1.16), (9) = 1.210, p> 0.05. An SNS index alue o ze o means ha he pa ame e s e lec ing
sympa he ic ac i i y a e, on a e age equal o he no mal popula ion a e age. Non-ze o SNS index alues desc ibe
how many SDs below (nega i e alues) o abo e (posi i e alues) he no mal popula ion a e age he pa ame e alues
a e.
Fig. 1. Compa ison o Sympa he ic Tone Index (SNS).
Table 2 shows he esul s o he analysis o hea a e a iabili y in ime and equency. We can obse e ha he
pa icipan s who mani es ed a high le el o s ess du ing he d i ing es wi hou i ual Reali y also p esen ed i when
hey used i ual Reali y. This is he case o d i e s 3, 5, 6, 7, and 10.
Figu e 2 cap u es he esul s o he su ey comple ed by he pa icipan s be o e s a ing he d i ing es . Pa icipan s
we e asked abou he le el o s ess hey no mally eel when d i ing in a eal en i onmen and he quali y o sleep he
las nigh . We ha e used a Like ype scale whe e ‘1’ has a e y posi i e meaning ( he d i e says ha he does no
su e s ess when d i ing o he slep e y well he nigh be o e) and ‘5’ is conside ed e y bad ( he d i e su e s a
lo o s ess when d i ing in he eal en i onmen o did no sleep well he las nigh ). The esponses ha e been g ouped
acco ding o he SNS index ob ained when using he simula o . The e a e wo g oups, hose ha ob ain an SNS index
less han o equal o 0.76 ( elaxed d i e s) and hose ha ob ain an SNS index highe han 0.76 (s essed d i e s). In
bo h cases, we a e conside ing he alues ob ained wi h and wi hou i ual Reali y. The da a indica es ha he e is a
signi ican di e ence be ween bo h g oups F (9) = 24.20, p <0.05 second he ANOVA es when we conside he s ess
ques ion. The d i e s who eel he mos s ess when d i ing in he eal en i onmen a e he ones who show he mos
s ess in he i ual en i onmen , using i ual Reali y and wi hou i . In he case o he ques ion abou sleep quali y,
he d i e s who p esen ed he highes s ess le el du ing he d i ing es we e he ones who slep he wo s he nigh
be o e. The di e ence be ween he wo g oups is signi ican . The ANOVA es esul is F (9) = 12.25, p <0.05.
-2,00
-1,00
0,00
1,00
2,00
3,00
4,00
12345678910
SNS Index
D i e
SNS Index (Wi hou i ual eali y) SNS Index (Wi h i ual eali y)

3260 Wilhelm Daniel Sche z e al. / P ocedia Compu e Science 176 (2020) 3255–3262
6 Wilhelm Daniel Sche z / P ocedia Compu e Science 00 (2020) 000–000
Table 2. Hea Ra e Analysis
D i e Vi ual Reali y
A e age RR
(ms)
SDNN
(ms)
A e age
HR (bpm)
STD HR
(bpm)
RMSSD
(ms) pNN50 LF/HF
1
No
813.11
23.90
73.79
2.21
24.72
4.10
3.36
Yes
743.71
42.41
80.67
4.72
31.80
10.56
2.48
2
No
860.17
32.67
69.75
2.66
24.38
3.98
3.96
Yes
862.86
30.54
69.53
2.47
22.49
2.57
4.76
3
No
674.51
51.95
88.95
6.85
32.15
8.72
6.29
Yes
686.20
61.92
87.48
7.86
40.04
13.53
5.04
4
No
813.95
43.33
73.71
4.02
35.54
13.96
3.35
Yes
884.46
58.33
67.83
4.57
46.81
22.78
2.78
5
No
625.47
29.776
95.92
4.57
19.29
1.88
2.93
Yes
650.04
30.624
92.30
4.31
20.15
1.53
2.38
6
No
693.55
28.961
86.51
3.63
18.07
1.01
7.62
Yes
697.13
37.552
86.06
4.58
20.12
2.65
8.78
7
No
700.52
55.332
85.65
6.80
47.19
16.23
1.78
Yes
740.45
40.64
81.03
4.36
33.94
13.20
2.05
8
No
1175.90
77.084
51.02
3.37
81.18
48.88
2.11
Yes
1133.00
82.77
52.91
3.92
83.59
50.36
2.17
9
No
804.11
44.07
74.61
4.11
32.63
9.91
5.93
Yes
769.06
68.41
78.01
6.87
48.95
19.22
5.27
10
No
729.06
28.20
82.29
3.19
19.32
1.09
3.56
Yes
743.37
28.34
80.71
3.09
20.15
2.20
3.36
Fig. 2. Resul s o he su ey g ouped by SNS index.
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
SNS index <= 0.76
SNS index > 0.75
Like Scale (1: Ve y good, 5: Ve y bad)
Sleep Quali y be o e he d i ing expe imen S ess in a eal d i ing en i onmen
Wilhelm Daniel Sche z e al. / P ocedia Compu e Science 176 (2020) 3255–3262 3261
6 Wilhelm Daniel Sche z / P ocedia Compu e Science 00 (2020) 000–000
Table 2. Hea Ra e Analysis
D i e
Vi ual Reali y
A e age RR
(ms)
SDNN
(ms)
A e age
HR (bpm)
STD HR
(bpm)
RMSSD
(ms)
pNN50
LF/HF
1
No
813.11
23.90
73.79
2.21
24.72
4.10
3.36
Yes
743.71
42.41
80.67
4.72
31.80
10.56
2.48
2
No
860.17
32.67
69.75
2.66
24.38
3.98
3.96
Yes
862.86
30.54
69.53
2.47
22.49
2.57
4.76
3
No
674.51
51.95
88.95
6.85
32.15
8.72
6.29
Yes
686.20
61.92
87.48
7.86
40.04
13.53
5.04
4
No
813.95
43.33
73.71
4.02
35.54
13.96
3.35
Yes
884.46
58.33
67.83
4.57
46.81
22.78
2.78
5
No
625.47
29.776
95.92
4.57
19.29
1.88
2.93
Yes
650.04
30.624
92.30
4.31
20.15
1.53
2.38
6
No
693.55
28.961
86.51
3.63
18.07
1.01
7.62
Yes
697.13
37.552
86.06
4.58
20.12
2.65
8.78
7
No
700.52
55.332
85.65
6.80
47.19
16.23
1.78
Yes
740.45
40.64
81.03
4.36
33.94
13.20
2.05
8
No
1175.90
77.084
51.02
3.37
81.18
48.88
2.11
Yes
1133.00
82.77
52.91
3.92
83.59
50.36
2.17
9
No
804.11
44.07
74.61
4.11
32.63
9.91
5.93
Yes
769.06
68.41
78.01
6.87
48.95
19.22
5.27
10
No
729.06
28.20
82.29
3.19
19.32
1.09
3.56
Yes
743.37
28.34
80.71
3.09
20.15
2.20
3.36
Fig. 2. Resul s o he su ey g ouped by SNS index.
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
SNS index <= 0.76
SNS index > 0.75
Like Scale (1: Ve y good, 5: Ve y bad)
Sleep Quali y be o e he d i ing expe imen S ess in a eal d i ing en i onmen
Wilhelm Daniel Sche z/ P ocedia Compu e Science 00 (2020) 000–000 7
In conclusion, i ual Reali y did no cause addi ional s ess when he pa icipan s d o e in he d i ing simula o .
The main ad an age o his echnology is ha he simula ion seems mo e ealis ic. Howe e , i s main d awback is ha
i causes dizziness. Pa icipan s illed ou a su ey whe e hey e alua ed using a Like scale i hey el dizzy a e
comple ing he d i ing es . On his scale, '1' mean ha hey we e no dizzy and '5' ha hey we e e y dizzy. The
mean alue was 3.1 ± 0.73 o d i e s who used i ual Reali y. In he case o 21 d i e s who ca ied ou he same es
bu wi hou using i ual Reali y, he mean alue was 1.33 ± 0.96. The e o e, i ual Reali y can be a headse lea ning
ool o d i e s o imp o e d i ing om an ecological and sa e y poin o iew. Howe e , i ual eali y de ices mus
imp o e o a oid dizziness ha discou ages hei use and educes aining ime.
4. Conclusions and u u e wo k
In p e ious s udies, we collec ed da a in ou di e en si ua ions, and we ied o desc ibe s ess using hea signals
de ec ion. In his s udy, we only obse ed he hea signals while d i ing a simula o wi h and wi hou VR. The aim
was o analyses he use o i ual eali y headse as a possible s esso . Fo his, we compa ed he HRV o 10
pa icipan s while d i ing wi h and wi hou i ual Reali y. The ob ained da a showed ha he pa icipan s had a
sligh ly highe hea a e and o he physiological pa ame e s, bu a p oo ha VR induces mo e s ess could no be
obse ed in such small g oup al hough we could obse e some s ess esponse and dizziness by some pa icipan s
while using he VR.
Fu u e esea ch should conside he po en ial e ec s o i ual Reali y as a possible s esso mo e ca e ully, o
example, by expanding he s udy o a bigge g oup o pa icipan s. I he esul s do eplica e in a bigge s udy, di e en
applica ions o he VR could be conside ed, such as eaching d i ing o o he applica ions.
Acknowledgmen s
This esea ch was pa ially unded by he EU In e eg V-P og am "Alpen hein-Bodensee-Hoch hein": P ojec "IBH
Li ing Lab Ac i e and Assis ed Li ing", g an s ABH040, ABH041, ABH066 and ABH068.
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