Enhancing Clinical Efficiency: Autonomous Determination of Cardiac Effective Refractory Period Using ECG Signals

37 Leka a echnika – Clinician and Technology 2024, ol. 54(2), pp. 37–42, DOI: 10.14311/CTJ.2024.2.01 ISSN 0301-5491 (P in ), ISSN 2336-5552 (Online) ORIGINAL RESEARCH ENHANCING CLINICAL EFFICIENCY: AUTONOMOUS DETERMINATION OF CARDIAC EFFECTIVE REFRACTORY PERIOD USING ECG SIGNALS Richa d Redina1, 2, Ma ina Filipenska1 1Depa men o Biomedical Enginee ing, Facul y o Elec ical Enginee ing and Communica ions, B no Uni e si y o Technology, B no, Czech Republic 2In e na ional Clinical Resea ch Cen e, S . Anne’s Hospi al, B no, Czech Republic Abs ac Elec ophysiological p ocedu es o managing a hy hmias emain ime-consuming, causing pa ien s o wai o c i ical in e en ions. To add ess his p essing need, we in oduce a e olu iona y algo i hm ha au onomously calcula es he e ec i e e ac o y pe iod (ERP) o ca diac issue om elec oca diog am (ECG). The algo i hm p incipally comp ises signal il e ing echniques and he de ec ion o local ex ema wi hin he signal wa e o m. This algo i hm unde wen igo ous assessmen using an in-house da abase o ECG signals acqui ed om en pa ien s who unde wen elec ophysiological examina ions. Fundamen al digi al signal p ocessing me hods, such as linea il e ing and h esholding, we e employed in he de e mina ion o ERP. The algo i hm yielded esul s cong uen wi h he ERP alues es ablished by elec ophysiologis s in nine ou o en cases, wi h a s anda d de ia ion o 18.97 milliseconds. By being accu a e and easy o in eg a e., his algo i hm holds p omise o eal- ime deploymen in clinical se ings, whe e i could po en ially s eamline and au oma e s imula ion p o ocols, he eby expedi ing he examina ion p ocess. Keywo ds Ca diac Elec ophysiology, E ec i e Re ac o y Pe iod, A hy hmology, S1–S2 S imula ion, In aca diac Elec og am In oduc ion In ou con empo a y landscape, he p e alence o ca diac ailmen s is s eadily moun ing, emphasizing he c i ical need o imp o ed ea men modali ies [1]. Wi hin his con ex , elec ophysiology eme ges as a ealm ipe o inno a i e b eak h oughs in ca diac ca e. Elec ophysiology is a specialized ield dedica ed o he in es iga ion o elec ical phenomena in biological sys ems, wi h a p ima y ocus on he human body. This discipline aiming on he p ecise measu emen o elec ical signals o igina ing wi hin cells, issues, and o gans, all in he pu sui o deepe insigh s in o pa hological condi ions [2]. The co ne s one o elec ophysiology's app oach o managing ca diac a hy hmias is he elec ophysio- logical examina ion [3]. This p ocedu e is pi o al in i s dual ole o elucida ing issue cha ac e is ics unde sc u iny, iden i ying abe an conduc ion pa hways be ween a ia and en icles, and pinpoin ing he o igins o ca diac a hy hmias. Mo eo e , i encompasses he apeu ic dimensions, in ol ing he isola ion o a ec ed myoca dial segmen s h ough he applica ion o adio equency ene gy. Ou esea ch is chie ly ocused on s eamlining he diagnos ic phase o his p ocedu e, pa icula ly in au oma ing he de e mina ion o he e ec i e e ac o y pe iod (ERP) o he conduc ion sys em. Ou ul ima e goal is o expedi e he en i e examina ion p ocess, which is inhe en ly ime-consuming, h ough he au oma ion o his c i ical s ep. Addi ionally, we p o ide a p o icien and unbiased diagnos ic ool o he a ending physician. This endea ou ma ks a signi ican s ide owa d enhancing he e iciency and p ecision o ca diac examina ions and ea men s. 38 Leka a echnika – Clinician and Technology 2024, ol. 54(2), pp. 37–42, DOI: 10.14311/CTJ.2024.2.01 ISSN 0301-5491 (P in ), ISSN 2336-5552 (Online) ORIGINAL RESEARCH Me hods Da ase An in e nal da abase o signals ob ained du ing elec ophysiological examina ions conduc ed a he Uni e si y Hospi al B no was u ilized o he de elop- men o he algo i hm o au oma ed ERP measu emen . All pa icipan s p o ided w i en in o med consen . A o al o en signals we e andomly selec ed om a ious pa ien s unde going ERP measu emen s o he a io en icula (AV) node. The signal du a ions anged om 57 o 208 seconds. The S . Jude Wo kMa e 4.2 EP, S . Jude Medical, USA sys em was employed o signal acquisi ion, wi h a sampling equency o 2000 Hz and a ol age esolu ion o 78 nV/LSB. The acquisi ion sys em is equipped wi h a buil -in band-s op il e o supp ess he 50 Hz equency and a high-pass il e wi h a cu -o equency o 0.1 Hz o elimina e low- equency noise. Du ing he p ocedu e, pa ien s we e subjec ed o con en ional wel e-lead su ace ECG measu emen s alongside i e in aca diac elec og am leads. These in aca diac elec og ams we e eco ded using en-pole ca he e s posi ioned in he co ona y sinus (CS). S1–S2 s imula ion A c ucial aspec o he eco ding p ocess in ol ed S1– S2 s imula ion, a widely employed p o ocol o assessing he elec ophysiological cha ac e is ics o he issue unde in es iga ion, pa icula ly in ERP de e mining [4]. This p o ocol en ails epe i i e s imula ion o he issue wi h an S1 in e al, succeeded by one o mo e s imuli a an S2 in e al, ypically sho e . The p ecise numbe o s imuli and he du a ion o he S1 phase can exhibi a iabili y. By inc emen ally dec easing he leng h o he S2 in e al, a h eshold is eached whe e he examined issue can no longe espond o he s imulus. The ERP o he issue is hen de e mined as he sho es du a ion o he S2 in e al o which he issue emains esponsi e. A isual ep esen a ion o his p o ocol is p esen ed in Fig. 1. When assessing he ERP o he AV node, s imula ion is conduc ed a he a ial le el (CS leads), wi h esponse moni o ing aking place a he en icula le el (su ace ECG). Au oma ic ERP measu emen The p oposed me hodology o au oma ed ERP de ec ion is elegan ly s aigh o wa d ye highly e icien , encompassing a se ies o p e-p ocessing and analy ical s eps applied o bo h in aca diac and su ace eco dings (see Fig. 2). Time (s) Fig. 1: S1–S2 s imula ion. Numbe o S1 s imuli (T = 500 ms) a e ollowed by sho e S2 s imulus T = 300 ms (a) o T = 290 ms (b). The las one ansduced is a s imulus wi h a pe iod o 300 ms; sho e S2 was no ansduced (black a ows). 39 Leka a echnika – Clinician and Technology 2024, ol. 54(2), pp. 37–42, DOI: 10.14311/CTJ.2024.2.01 ISSN 0301-5491 (P in ), ISSN 2336-5552 (Online) ORIGINAL RESEARCH Fig. 2: Block scheme o he algo i hm o au oma ed ERP de ec ion. Ini ially, a lead showcasing exclusi ely s imula ion spikes, cha ac e ized by he highes ampli udes among all eco ded signals, is singled ou . Wi hin his lead, s imula ion spikes a e u he pinpoin ed as de ia ions mee ing speci ic c i e ia: hei peak magni ude mus be a leas 75% o he signal's maximum alue, wi h adjacen spikes sepa a ed by a minimum o 150 milliseconds. In he in e als be ween indi idual s imula ions, he sea ch commences o subsequen S2 pe iods sho e han he p eceding S1 pe iod. Subsequen ly, he analysis shi s o su ace lead V6, which unde goes il a ion. I is subjec ed o bo h a low- pass il e wi h a cu -o equency o 45 Hz and a high- pass il e wi h a cu -o equency o 15 Hz, u ilizing a ini e impulse esponse (FIR) il e o de o 35. This p ocess accen ua es he QRS complexes while supp essing unwan ed componen s [5]. Following his, segmen s las ing 500 milliseconds a e selec ed a e he al eady iden i ied S2 pe iods, beginning 25 milliseconds a e he pe iod's ends. These segmen s a e p esumed o con ain he hea 's esponse o s imula ion, mani es ing as a QRS complex in he su ace ECG. The e o e, QRS complex de ec ion is pe o med in each selec ed segmen by compa ing he maximum de ia ion o he segmen wi h an empi ically se h eshold o 2 µV. A sub h eshold maximum indica es he absence o a QRS complex in he segmen ollowing s imula ion, signi ying he absence o issue esponse o such a b ie s imula ion pe iod. The las S2 pe iod ea u ing a p esen QRS complex is iden i ied as he ERP and epo ed o u he u iliza ion. Model obus ness One o he c ucial a ibu es o any signal p ocessing algo i hm is i s obus ness agains noise ha may be p esen in he da a. The e can be se e al ypes o such noise, and o he pu poses o his wo k, wo we e selec ed, he occu ence o which is nea ly una oidable. The i s one is andom noise, speci ically Gaussian noise. This ype o noise is cha ac e ized by a p obabili y densi y unc ion equal o he no mal dis ibu ion. The second ype o noise is powe line in e e ence (PLI). The p esence o his ype o noise is almos ine i able unde common condi ions due o he ubiqui ous elec ical g id. An ad an age o his noise is i s na ow spec al cha ac e is ic, p ima ily limi ed o he equency o 50 Hz (o 60 Hz in he US). Bo h ypes o noise we e a i icially in oduced in o he signals, and a ious le els o signal- o-noise a io (SNR) we e es ed o e alua e he algo i hm's pe o mance unde challenging condi ions. The obus ness o he model was es ed a a o al o i e SNR le els (20, 15, 10, 5, and 0 dB). Resul s ERP es ima ion The p esen ed algo i hm was applied o en eco ds om elec ophysiological examina ions, and he algo i hm's ou pu s a e summa ized in Table 1. In nine ou o en cases, he ERP o he AV node was co ec ly iden i ied. In one case, he ERP o he AV node was no co ec ly iden i ied due o he p esence o a pa hological conduc ion pa hway wi h a lowe ERP han ha o he AV node. Consequen ly, he s imula ion p opaga ed o he en icles. Howe e , he p opaga ed s imulus was delayed and exhibi ed al e ed mo phology. This case is illus a ed in Fig. 3. 40 Leka a echnika – Clinician and Technology 2024, ol. 54(2), pp. 37–42, DOI: 10.14311/CTJ.2024.2.01 ISSN 0301-5491 (P in ), ISSN 2336-5552 (Online) ORIGINAL RESEARCH Time (s) Fig. 3: No iceable change in he mo phology o he QRS complex ma king he eaching o he ERP accesso y pa hway (a). Exceeding he ERP o he accesso y pa hway esul s in he disappea ance o he cha ac e is ic del a wa e o he second case (b). Robus ness o a i icial noise As demons a ed in he s udy [6], he commonly measu ed SNR le els in signals ypically ho e a ound 10 dB, a le el ha he model should be able o handle. In he con ex o ou expe imen , we independen ly co up ed he su ace ECG signal wi h bo h ypes o noise. The algo i hm's pe o mance on he co up ed da a is summa ized in Tables 2 and 3. The bolded alues in he ables highligh he di e ence om he anno a ion p o ided by he physician. Table 2: ERP alues (ms) in indi idual pa ien s unde di e en Gaussian noise le el (dB). The las ow ep esen s he s anda d de ia ion (ms) o he whole se . SNR Pa ien 20 15 10 5 0 1 270 270 270 270 270 2 250 250 250 250 250 3 300 300 300 300 300 4 260 260 260 260 250 5 320 320 320 320 380 6 220 220 220 330 220 7 340 340 330 340 330 8 320 320 320 320 320 9 400 400 400 400 400 10 310 310 310 300 340 σ 18.97 18.97 18.97 19.24 34.79 Al hough inc easing a ia ions wi h inc easing noise le el a e cap u ed in he ables, a wo-way ANOVA es did no con i m a signi ican e ec o in ensi y le el o noise ype (p > 0.05). Thus, i can be said ha he p oposed me hod does no show s a is ically signi ican de ia ions in ei he ca ego y. Table 1: Resul ing ERP alues (ms) measu ed du ing he p ocedu e by he elec ophysiologis and ob ained using he algo i hm. The las ow ep esen s he s anda d de ia ion (ms) o he whole se . Pa ien Physician Algo i hm 1 270 270 2 310 250 3 300 300 4 260 260 5 320 320 6 220 220 7 340 340 8 320 320 9 400 400 10 310 310 σ - 18.97 41 Leka a echnika – Clinician and Technology 2024, ol. 54(2), pp. 37–42, DOI: 10.14311/CTJ.2024.2.01 ISSN 0301-5491 (P in ), ISSN 2336-5552 (Online) ORIGINAL RESEARCH Table 3: ERP alues (ms) in indi idual pa ien s unde di e en powe line in e e ence noise (dB). The las ow ep esen s he s anda d de ia ion (ms) o he whole se . SNR 20 15 10 5 0 Pa ien 1 270 270 270 270 270 2 250 250 250 250 250 3 300 300 300 300 300 4 260 250 250 250 250 5 320 320 320 320 320 6 220 220 220 220 220 7 330 330 330 330 330 8 320 320 320 320 320 9 400 390 390 390 390 10 300 300 300 300 300 σ 18.97 19.49 20.00 20.00 20.00 Discussion The algo i hm p esen ed by us se es as a undamen al building block o he au oma ed assessmen o ERP du ing elec ophysiological p ocedu es. In ou pape , we show ha ERP measu emen s can be la gely au oma ed and hus sa e ime du ing elec ophysiological p ocedu es. Despi e p omising esul s, his is only a p oo o concep . One o he limi a ions o he algo i hm could undoub edly be he ela i ely small da ase on which i was es ed. Un o una ely, a small da ase may no adequa ely cap u e he wide in e indi idual a iabili y p esen among di e en pa ien s. Addi ionally, he algo i hm does no accoun o he possible p esence o accesso y conduc ion pa hways, which may be pa icula ly ele an in younge pa ien s. As e iden om he ables, he algo i hm's pe o mance de e io a es wi h inc easing noise le els. To compa e he esul s o he indi idual ypes o noise, we can use he s anda d de ia ion o he e o om he o iginal anno a ion. A clea compa ison eme ges, showing ha he algo i hm handles PLI noise be e . This is likely due o he ac ha he signal passes h ough a low-pass il e wi h a cu -o equency o 45 Hz, which should e ec i ely il e ou he unwan ed in luence o PLI. Con e sely, he wideband Gaussian noise is emo ed less e ec i ely, and he s anda d de ia ion alue almos doubles wi h inc easing SNR. To achie e be e noise emo al, i would be necessa y o add an addi ional il e o educe he cu -o equency o he men ioned high- pass il e . The esul s ob ained by ou me hod no only co espond o he esul s ob ained manually by an elec ophysiologis du ing he p ocedu e, bu also align wi h he alues ob ained expe imen ally in he s udy [7]. Despi e he men ioned limi a ions, he e is signi ican po en ial o es ing he algo i hm on addi ional eco ds om di e en pa ien s. Ano he a enue o expanding he algo i hm is conside ing he examina ion o o he issues, hus in ol ing he analysis o a ious lead combina ions. An ancilla y p oduc o he algo i hm is he iden i ica ion o he s imula ed hy hm, which can p o ide aluable in o ma ion o aining deep lea ning sys ems. Since one o he limi a ions men ioned is he ela i ely small da ase used o es ing, pe o ming c oss- alida ion on la ge da ase s om di e se pa ien popula ions can p o ide a mo e comp ehensi e assessmen o he algo i hm's pe o mance and i s abili y o gene alize ac oss di e en pa ien coho s. Gi en he algo i hm's inabili y o accoun o accesso y conduc ion pa hways, conduc ing sensi i i y analyses o simula ions o assess he impac o hese pa hways on algo i hm pe o mance could be aluable. This could in ol e in oducing simula ed accesso y pa hways in o he da a and e alua ing how he algo i hm esponds. Conclusion In ou pape , an algo i hm o he au oma ic de ec ion o AV node ERP was in oduced. The algo i hm demons a ed success in nine ou o en cases, es ablishing i s eliabili y. Fu he de elopmen o he algo i hm could po en ially lead o ully au oma ed eal- ime measu emen o he ERP in a ious pa s o he conduc ion sys em du ing examina ions. The use o ou me hod can educe he ime o S1–S2 s imula ion, which can ake se e al minu es. The au oma ic assessmen o he ca diac issue esponse can ee he hands o he physician, who can ocus on o he ac i i ies du ing he examina ion—e.g. inse ing he apeu ic ca he e s. Pa ial esul s om his wo k we e p e iously published a he T ends in Biomedical Enginee ing 2023 con e ence [8]. Acknowledgemen B no Ph.D. Talen Schola ship Holde unded by he B no Ci y Municipali y. Du ing he p epa a ion o his wo k he au ho s used OpenAI's Cha GPT and Google Ba d o p e-co ec ing English syn ax and g amma . A e using his ool/se ice, he au ho s e iewed and edi ed he con en as needed and ake ull esponsibili y o he con en o he publica ion. 42 Leka a echnika – Clinician and Technology 2024, ol. 54(2), pp. 37–42, DOI: 10.14311/CTJ.2024.2.01 ISSN 0301-5491 (P in ), ISSN 2336-5552 (Online) ORIGINAL RESEARCH Re e ences [1] Vadugana han M, Mensah GA, Tu co JV, Fus e V, Ro h GA. The Global Bu den o Ca dio ascula Diseases and Risk: A Compass o Fu u e Heal h. Jou nal o he Ame ican College o Ca diology. 2022 No ;80(25):2361–71. DOI: 10.1016/j.jacc.2022.11.005 [2] Ka i sis DG, Bo iani G, Cosio FG, Hind icks G, Jaïs P, Josephson ME, e al. Eu opean Hea Rhy hm Associa ion (EHRA) consensus documen on he managemen o sup a en icula a hy hmias, endo sed by Hea Rhy hm Socie y (HRS), Asia-Paci ic Hea Rhy hm Socie y (APHRS), and Sociedad La inoame icana de Es imulación Ca diaca y Elec o isiologia (SOLAECE). EP Eu opace. 2016 No 17;19(3):465–511. DOI: 10.1093/eu opace/euw301 [3] Ma in E, Alan B, Ma in F. 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DOI: 10.1093/eu opace/euu246 [8] Ředina R, Ronzhina M. Es ima ion o myoca dial conduc ion eloci y using a co ona y sinus ca he e . In: No ak V, edi o . P oceedings II o he 29 h Con e ence STUDENT EEICT 2023; 2023 Ap 25. B no: B no Uni e si y o Technology, Facul y o Elec ical Enginee ing and Communica ion; c2023. p. 156–60. DOI: 10.13164/eeic .2023.156 Richa d Ředina Depa men o Biomedical Enginee ing Facul y o Elec ical Enginee ing and Communica ion B no Uni e si y o Technology An onínská 2, CZ-601 00, B no E-mail: 195715@ u .cz Phone: +420 541 146 676