Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis

Benjamin De Ridder, Bart Van Rompaey, Jarl K Kampen, Steven Haine, Tinne Dilles, Benjamin De Ridder, Bart Van Rompaey, Jarl K Kampen, Steven Haine, Tinne Dilles

Abstract

Background: Smartphone ownership is rising at a stunning rate. Moreover, smartphones prove to be suitable for use in health care due to their availability, portability, user-friendliness, relatively low price, wireless connectivity, far-reaching computing capabilities, and comprehensive memory. To measure vital signs, smartphones are often connected to a mobile sensor or a medical device. However, by using the white light-emitting diode as light source and the phone camera as photodetector, a smartphone could be used to perform photoplethysmography (PPG), enabling the assessment of vital signs.

Objective: The objective of this meta-analysis was to evaluate the available evidence on the use of smartphone apps to measure heart rate by performing PPG in comparison with a validated method.

Methods: PubMed and ISI Web of Knowledge were searched for relevant studies published between January 1, 2009 and December 7, 2016. The reference lists of included studies were hand-searched to find additional eligible studies. Critical Appraisal Skills Programme (CASP) Diagnostic Test Study checklist and some extra items were used for quality assessment. A fixed effects model of the mean difference and a random effects model of Pearson correlation coefficient were applied to pool the outcomes of the studies.

Results: In total, 14 studies were included. The pooled result showed no significant difference between heart rate measurements with a smartphone and a validated method (mean difference -0.32; 99% CI -1.24 to 0.60; P=.37). In adults, the Pearson correlation coefficient of the relation between heart rate measurement with a smartphone and a validated method was always ≥.90. In children, the results varied depending on measuring point and heart rate. The pooled result showed a strong correlation that was significant (correlation coefficient .951; 95% CI 0.906-0.975; P<.001). The reported limits of agreement showed good agreement between a smartphone and a validated method. There was a moderately strong significant negative correlation between the year of publication of the included studies and the mean difference (r=-.69; P<.001).

Conclusions: Smartphone apps measuring heart rate by performing PPG appear to agree with a validated method in an adult population during resting sinus rhythm. In a pediatric population, the use of these apps is currently not validated.

Keywords: electrocardiography; heart rate; meta-analysis; mobile applications; oximetry; photoplethysmography.

Conflict of interest statement

Conflicts of Interest: None declared.

©Benjamin De Ridder, Bart Van Rompaey, Jarl K Kampen, Steven Haine, Tinne Dilles. Originally published in JMIR Cardio (http://cardio.jmir.org), 27.02.2018.

Figures

Figure 1
Figure 1
Search and selection strategy.
Figure 2
Figure 2
Forest plot for the meta-analysis of mean difference.
Figure 3
Figure 3
Forest plot for the meta-analysis of Pearson correlation coefficient.
Figure 4
Figure 4
Scatter plot comparing correlation between mean heart rate measured by control and mean difference.
Figure 5
Figure 5
Scatter plot comparing correlation between sample size and mean difference.
Figure 6
Figure 6
Scatter plot comparing correlation between year of publication and mean difference.

References

    1. Poushter J. Pewglobal. 2016. [2017-01-06]. Smartphone Ownership and Internet Usage Continues to Climb in Emerging Economies
    1. Baig MM, GholamHosseini H, Connolly MJ. Mobile healthcare applications: system design review, critical issues and challenges. Australas Phys Eng Sci Med. 2015 Mar;38(1):23–38. doi: 10.1007/s13246-014-0315-4.
    1. Sarasohn-Kahn J. CHCF. 2010. [2017-08-06]. How Smartphones Are Changing Health Care for Consumers and Providers .
    1. Bruining N, Caiani E, Chronaki C, Guzik P, van der Velde E, Task Force of the e-Cardiology Working Acquisition and analysis of cardiovascular signals on smartphones: potential, pitfalls and perspectives: by the Task Force of the e-Cardiology Working Group of European Society of Cardiology. Eur J Prev Cardiol. 2014 Nov;21(2 Suppl):4–13. doi: 10.1177/2047487314552604.
    1. Ozdalga E, Ozdalga A, Ahuja N. The smartphone in medicine: a review of current and potential use among physicians and students. J Med Internet Res. 2012;14(5):e128. doi: 10.2196/jmir.1994.
    1. Martínez-Pérez B, de la Torre-Diez I, López-Coronado M, Herreros-González J. Mobile apps in cardiology: review. JMIR Mhealth Uhealth. 2013;1(2):e15. doi: 10.2196/mhealth.2737.
    1. Allen J. Photoplethysmography and its application in clinical physiological measurement. Physiol Meas. 2007 Mar;28(3):R1–39. doi: 10.1088/0967-3334/28/3/R01.
    1. Jonathan E, Leahy M. Investigating a smartphone imaging unit for photoplethysmography. Physiol Meas. 2010 Nov;31(11):N79–83. doi: 10.1088/0967-3334/31/11/N01.
    1. Elgendi M. On the analysis of fingertip photoplethysmogram signals. Curr Cardiol Rev. 2012 Feb;8(1):14–25.
    1. Critical Appraisal Skills Programme. 2016. 12 questions to help you make sense of a diagnostic test study .
    1. Hanneman SK. Design, analysis, and interpretation of method-comparison studies. AACN Adv Crit Care. 2008;19(2):223–34. doi: 10.1097/01.AACN.0000318125.41512.a3.
    1. Deeks JJ, Higgins JP, Altman DG. Chapter 9: Analysing data and undertaking meta-analyses. In: Higgins JP, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. UK: Cochrane Collaboration; 2011.
    1. Weng J, Guo XM, Chen LS, Yuan ZH, Ding XR, Lei M. Study on real-time monitoring technique for cardiac arrhythmia based on smartphone. J Med Biol Eng. 2013;33(4):394. doi: 10.5405/jmbe.1278.
    1. Waks JW, Fein AS, Das S. Wide complex tachycardia recorded with a smartphone cardiac rhythm monitor. JAMA Intern Med. 2015 Mar;175(3):437–9. doi: 10.1001/jamainternmed.2014.7586.
    1. Tofield A. Cardiac arrhythmia challenge: a new app. Eur Heart J. 2013 Nov;34(44):3392.
    1. Tan YY, Chung WY. Mobile health-monitoring system through visible light communication. Biomed Mater Eng. 2014;24(6):3529–38. doi: 10.3233/BME-141179.
    1. Tabing A, Harrell T, Francisco G, Romero S. Supraventricular tachycardia diagnosed by smartphone electrocardiography. J Am Coll Cardiol. 2016 Apr;67(13):1237. doi: 10.1016/S0735-1097(16)31238-4.
    1. Su Y, Yin L, Al-Hakim L. Ephone: embedded cardiac care device in mobile phone. Sen Lett. 2011 Oct 01;9(5):1974–1978. doi: 10.1166/sl.2011.1542.
    1. Petersen CL, Chen TP, Ansermino JM, Dumont GA. Design and evaluation of a low-cost smartphone pulse oximeter. Sensors (Basel) 2013 Dec 06;13(12):16882–93. doi: 10.3390/s131216882.
    1. Peng RC, Zhou XL, Lin WH, Zhang YT. Extraction of heart rate variability from smartphone photoplethysmograms. Comput Math Methods Med. 2015;2015:516826. doi: 10.1155/2015/516826. doi: 10.1155/2015/516826.
    1. Oster J, Behar J, Colloca R, Li Q, Li Q, Clifford G. Open source Java-based ECG analysis software and Android app for Atrial Fibrillation screening. Computing in Cardiology Conference (CinC); September 22-25, 2013; Zaragoza, Spain. 2013.
    1. Orchard J, Freedman SB, Lowres N, Peiris D, Neubeck L. iPhone ECG screening by practice nurses and receptionists for atrial fibrillation in general practice: the GP-SEARCH qualitative pilot study. Aust Fam Physician. 2014 May;43(5):315–9.
    1. Nyotowidjojo I, Erickson RP, Lee KS. Crowd-sourcing syncope diagnosis: mobile smartphone ECG apps. Am J Med. 2016 Apr;129(4):e17–8. doi: 10.1016/j.amjmed.2015.11.022.
    1. Nguyen HH, Van Hare GF, Rudokas M, Bowman T, Silva JN. SPEAR trial: smartphone pediatric electrocARdiogram trial. PLoS One. 2015;10(8):e0136256. doi: 10.1371/journal.pone.0136256.
    1. Li JP, Berry D, Hayes R. A mobile ECG monitoring system with context collection. 4th European Conference of the International Federation for Medical and Biological Engineering; November 23-27; Antwerp, Belgium. 2009. pp. 1222–1225.
    1. Lee J, Reyes BA, McManus DD, Mathias O, Chon KH. Atrial fibrillation detection using an iPhone 4S. IEEE Trans Biomed Eng. 2013 Jan;60(1):203–6. doi: 10.1109/TBME.2012.2208112.
    1. Landreani F, Martin-Yebra A, Casellato C, Frigo C, Pavan E, Migeotte P, Caiani EG. Beat-to-beat heart rate detection by smartphone's accelerometers: validation with ECG. IEEE 38th Annual International Conference of Engineering in Medicine and Biology Society (EMBC), 2016; August 16-20, 2016; Orlando, FL, USA. 2016. Aug, pp. 525–528.
    1. Kwon S, Lee J, Chung GS, Park KS. Validation of heart rate extraction through an iPhone accelerometer. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:5260–3. doi: 10.1109/IEMBS.2011.6091301.
    1. Kwon S, Kim H, Park KS. Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:2174–7. doi: 10.1109/EMBC.2012.6346392.
    1. Kirtava Z, Gegenava T, Gegenava M, Matoshvili Z, Kasradze S, Kasradze P. Mobile telemonitoring for arrhythmias in outpatients in the Republic of Georgia: a brief report of a pilot study. Telemed J E Health. 2012 Sep;18(7):570–1. doi: 10.1089/tmj.2011.0170.
    1. Karapetyan G, Barseghyan R, Sarukhanyan H, Agaian S. Development and validation of an improved smartphone heart rate acquisition system. Image Process Algorithms Syst XIII. 2015;9399 doi: 10.1117/12.2083381.
    1. Jokic S, Krco S, Sakac D, Jokic ID, Delic V. Autonomic telemedical application for Android based mobile devices. Eleventh Symposium on Neural Network Applications in Electrical Engineering; September 20-22, 2012; Belgrade, Serbia. 2012.
    1. Jaworek J, Augustyniak P. A cardiac telerehabilitation application for mobile devices. Computing in Cardiology; September 18-21, 2011; Hangzhou, China. 2011.
    1. Issac R, Ajaynath MS. CUEDETA: a real time heart monitoring system using Android smartphone. India Conference (INDICON); December 7-9, 2012; Kochi, India. Cuedeta: 2012.
    1. Işik AH, Güler I. Pulse oximeter based mobile biotelemetry application. Stud Health Technol Inform. 2012;181:197–201.
    1. de Oliveira IH, Cene VH, Balbinot A. Portable electrocardiograph through Android application. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015; August 25-29, 2015; Milan, Italy. 2015. pp. 6780–3.
    1. Hadiyoso S, Usman K, Rizal A. Arrhythmia detection based on ECG signal using Android mobile for athlete and patient. 2015 3rd International Conference on Information and Communication Technology (ICoICT); May 27-29, 2015; Nusa Dua, Bali. 2015.
    1. Gradl S, Kugler P, Lohmuller C, Eskofier B. Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:2452–5. doi: 10.1109/EMBC.2012.6346460.
    1. Filipovic N, Stojanovic R, Lekic N, Caplanova A. Monitoring and analysis of vital physiological parameters using PDA devices. 24th International Conference Radioelektronika (Radioelektronika); April 15-16, 2014; Bratislava, Slovakia. 2014.
    1. Filipovic N, Stojanovic R, Debevc M, Devedzic G. On line ECG processing and visualization using Android smartphone. 2nd Mediterranean Conference on Embedded Computing (Meco); June 15-20, 2013; Budva, Serbia. 2013.
    1. Fernandes B, Afonso JA, Simoes R. Vital signs monitoring and management using mobile devices. 6th Iberian Conference on Information Systems and Technologies; June 15-18, 2011; Chaves, Portugal. 2011.
    1. Ferdman DJ, Liberman L, Silver ES. A smartphone application to diagnose the mechanism of pediatric supraventricular tachycardia. Pediatr Cardiol. 2015 Oct;36(7):1452–7. doi: 10.1007/s00246-015-1185-6.
    1. Cruz T, Brás S, Soares SC, Fernandes JM. Monitoring physiology and behavior using Android in phobias. Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:3739–42. doi: 10.1109/EMBC.2015.7319206.
    1. Choo KY, Ling HC, Lo YC, Yap ZH, Pua JS, Phan RC, Goh VT. Android based self-diagnostic electrocardiogram system for mobile healthcare. Technol Health Care. 2015;23 Suppl 2:S435–42. doi: 10.3233/THC-150980.
    1. Banos O, Damas M, Glossekotter P, Hermes A, Mende H, Pomares H, Rojas I. Physiodroid: an app for physiological data monitoring. International Work-Conference on Bioinformatics and Biomedical Engineering; March 18-20, 2013; Granada, Spain. 2013.
    1. Amiri AM, Abhinav. Mankodiya K. m-QRS: an efficient QRS detection algorithm for mobile health applications. 17th International Conference on E-Health Networking, Application & Services (Healthcom); October 14-17, 2015; Boston, MA, USA. 2015.
    1. Abi Zeid Daou R, Aad E, Nakhle F, Hayek A, Borcsok J. Patient vital signs monitoring via Android application. 2015 International Conference on Advances in Biomedical Engineering (ICABME); Beirut, Lebanon; September 16-18, 2015. 2015.
    1. No authors listed ECG? There's an app for that! Harv Heart Lett. 2013 Mar;23(7):8.
    1. Winkler S, Schieber M, Lücke S, Heinze P, Schweizer T, Wegertseder D, Scherf M, Nettlau H, Henke S, Braecklein M, Anker SD, Koehler F. A new telemonitoring system intended for chronic heart failure patients using mobile telephone technology--feasibility study. Int J Cardiol. 2011 Nov 17;153(1):55–8. doi: 10.1016/j.ijcard.2010.08.038.
    1. Vashist SK, Schneider EM, Luong JH. Commercial smartphone-based devices and smart applications for personalized healthcare monitoring and management. Diagnostics (Basel) 2014 Aug 18;4(3):104–28. doi: 10.3390/diagnostics4030104.
    1. Saldarriaga AJ, Perez JJ, Restrepo J, Bustamante J. A mobile application for ambulatory electrocardiographic monitoring in clinical and domestic environments. 2013 Pan American Health Care Exchanges (PAHCE); 29 April-4 May, 2013; Medellin, Colombia. 2013.
    1. Plesnik E, Malgina O, Tasic JF, Zajc M. ECG signal acquisition and analysis for telemonitoring. 15th IEEE Mediterranean Electrotechnical Conference (MELECON 2010); April 26-28, 2010; Valletta, Malta. 2010.
    1. Mittal S. Smartphone-based electrocardiographic and cardiac implantable electronic device monitoring. Cardiol Rev. 2017;25(1):12–16. doi: 10.1097/CRD.0000000000000132.
    1. Mattila J, Ding H, Mattila E, Särelä A. Mobile tools for home-based cardiac rehabilitation based on heart rate and movement activity analysis. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:6448–52. doi: 10.1109/IEMBS.2009.5333540.
    1. Mateev H, Simova I, Katova T, Dimitrov N. Clinical evaluation of a mobile heart rhythm telemonitoring system. ISRN Cardiol. 2012;2012:192670. doi: 10.5402/2012/192670. doi: 10.5402/2012/192670.
    1. Madias JE. A proposal for monitoring patients with heart failure via “smart phone technology”-based electrocardiograms. J Electrocardiol. 2016;49(5):699–706. doi: 10.1016/j.jelectrocard.2016.06.001.
    1. Kumpusch H, Hayn D, Kreiner K, Falgenhauer M, Mor J, Schreier G. A mobile phone based telemonitoring concept for the simultaneous acquisition of biosignals physiological parameters. Stud Health Technol Inform. 2010;160(Pt 2):1344–8.
    1. Kumar M, Veeraraghavan A, Sabharwal A. DistancePPG: Robust non-contact vital signs monitoring using a camera. Biomed Opt Express. 2015 May 01;6(5):1565–88. doi: 10.1364/BOE.6.001565.
    1. Guzik P, Malik M. ECG by mobile technologies. J Electrocardiol. 2016;49(6):894–901. doi: 10.1016/j.jelectrocard.2016.07.030.
    1. Gonzalez-Fernandez R, Mulet-Cartaya M, Lopez-Cardona JD, Lopez-Rodriguez R. A mobile application for cardiac rhythm study. Computing in Cardiology Conference (CinC); September 6-9, 2015; Nice, France. 2015.
    1. Garabelli P, Stavrakis S, Po S. Smartphone-based arrhythmia monitoring. Curr Opin Cardiol. 2017 Jan;32(1):53–57. doi: 10.1097/HCO.0000000000000350.
    1. Freedman B. Screening for atrial fibrillation using a smartphone: is there an app for that? J Am Heart Assoc. 2016 Jul 21;5(7) doi: 10.1161/JAHA.116.004000.
    1. Fang DJ, Hu JC, Wei XF, Shao H, Luo YE. A smart phone healthcare monitoring system for oxygen saturation and heart rate. International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery; October 13-15, 2014; Shanghai, China. 2014.
    1. de Lucena SE, Sampaio D, Mall B, Meyer M, Burkart MA, Keller FV. ECG monitoring using Android mobile phone and Bluetooth. 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings; May 11-14, 2015; Pisa, Italy. 2015.
    1. Bal U. Non-contact estimation of heart rate and oxygen saturation using ambient light. Biomed Opt Express. 2015 Jan 01;6(1):86–97. doi: 10.1364/BOE.6.000086.
    1. Ahamed MA, Hasan MK, Alam MS. Design and implementation of low cost ECG monitoring system for the patient using smartphone. 2015 International Conference on Electrical & Electronic Engineering (ICEEE); November 4-6, 2015; Rajshahi, Bangladesh. 2015. pp. 261–264.
    1. Bobra NP, Wang ZB, Zhang WF, Luo A. A high-quality, low-energy, small-size system-on-chip (soc) solution enabling ECG mobile applications. 39th Annual Conference of the IEEE Industrial Electronics Society; November 10-13, 2013; Vienna, Austria. 2013. pp. 8406–8409.
    1. Bolkhovsky JB, Scully CG, Chon KH. Statistical analysis of heart rate and heart rate variability monitoring through the use of smart phone cameras. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:1610–3. doi: 10.1109/EMBC.2012.6346253.
    1. Cheatham SW, Kolber MJ, Ernst MP. Concurrent validity of resting pulse-rate measurements: a comparison of 2 smartphone applications, the polar H7 belt monitor, and a pulse oximeter with bluetooth. J Sport Rehabil. 2015 May;24(2):171–8. doi: 10.1123/jsr.2013-0145.
    1. Drijkoningen L, Lenaerts F, Van der Auwera J, Leysen K, Nuyens D, Vandervoort P, Grieten L. Validation of a smartphone based photoplethysmographic beat detection algorithm for normal and ectopic complexes. Computing in Cardiology 2014; September 7-10, 2014; Cambridge, MA, USA. 2014.
    1. Flatt AA, Esco MR. Validity of the ithleteTM smart phone application for determining ultra-short-term heart rate variability. J Hum Kinet. 2013 Dec 18;39:85–92. doi: 10.2478/hukin-2013-0071.
    1. Garabelli P, Stavrakis S, Albert M, Koomson E, Parwani P, Chohan J, Smith L, Albert D, Xie RS, Xie QY, Reynolds D, Po S. Comparison of QT interval readings in normal sinus rhythm between a smartphone heart monitor and a 12-lead ECG for healthy volunteers and inpatients receiving sotalol or dofetilide. J Cardiovasc Electrophysiol. 2016 Jul;27(7):827–32. doi: 10.1111/jce.12976.
    1. Gregoski MJ, Mueller M, Vertegel A, Shaporev A, Jackson BB, Frenzel RM, Sprehn SM, Treiber FA. Development and validation of a smartphone heart rate acquisition application for health promotion and wellness telehealth applications. Int J Telemed Appl. 2012;2012:696324. doi: 10.1155/2012/696324. doi: 10.1155/2012/696324.
    1. Haberman ZC, Jahn RT, Bose R, Tun H, Shinbane JS, Doshi RN, Chang PM, Saxon LA. Wireless smartphone ECG enables large-scale screening in diverse populations. J Cardiovasc Electrophysiol. 2015 May;26(5):520–6. doi: 10.1111/jce.12634.
    1. Ho CL, Fu YC, Lin MC, Chan SC, Hwang B, Jan SL. Smartphone applications (apps) for heart rate measurement in children: comparison with electrocardiography monitor. Pediatr Cardiol. 2014 Apr;35(4):726–31. doi: 10.1007/s00246-013-0844-8.
    1. Huang RY, Dung LR. Measurement of heart rate variability using off-the-shelf smart phones. Biomed Eng Online. 2016 Jan 29;15:11. doi: 10.1186/s12938-016-0127-8.
    1. Kanva AK, Sharma CJ, Deb S. Determination of spo(2) and heart-rate using smart-phone camera. Proceedings of The 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC); January 31-February 2, 2014; Calcutta, India. 2014. pp. 237–241.
    1. Koenig N, Seeck A, Eckstein J, Mainka A, Huebner T, Voss A, Weber S. Validation of a new heart rate measurement algorithm for fingertip recording of video signals with smartphones. Telemed J E Health. 2016 Aug;22(8):631–6. doi: 10.1089/tmj.2015.0212.
    1. Lagido RB, Lobo J, Leite S, Sousa C, Ferreira L, Silva-Cardoso J. Using the smartphone camera to monitor heart rate and rhythm in heart failure patients. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI); June 1-4, 2014; Valencia, Spain. 2014. pp. 556–559.
    1. Losa-Iglesias ME, Becerro-de-Bengoa-Vallejo R, Becerro-de-Bengoa-Losa KR. Reliability and concurrent validity of a peripheral pulse oximeter and health-app system for the quantification of heart rate in healthy adults. Health Informatics J. 2016;22(2):151–9. doi: 10.1177/1460458214540909.
    1. Mateev H, Simova I, Katova T, Dimitrov N. Clinical evaluation of a mobile heart rhythm telemonitoring system. ISRN Cardiol. 2012;2012:192670. doi: 10.5402/2012/192670. doi: 10.5402/2012/192670.
    1. Matsumura K, Yamakoshi T. iPhysioMeter: a new approach for measuring heart rate and normalized pulse volume using only a smartphone. Behav Res Methods. 2013 Dec;45(4):1272–8. doi: 10.3758/s13428-012-0312-z.
    1. McManus DD, Chong JW, Soni A, Saczynski JS, Esa N, Napolitano C, Darling CE, Boyer E, Rosen RK, Floyd KC, Chon KH. Pulse-smart: Pulse-based arrhythmia discrimination using a novel smartphone application. J Cardiovasc Electrophysiol. 2016 Jan;27(1):51–7. doi: 10.1111/jce.12842.
    1. McManus DD, Lee J, Maitas O, Esa N, Pidikiti R, Carlucci A, Harrington J, Mick E, Chon KH. A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation. Heart Rhythm. 2013 Mar;10(3):315–9. doi: 10.1016/j.hrthm.2012.12.001.
    1. Nam Y, Kong Y, Reyes B, Reljin N, Chon KH. Monitoring of heart and breathing rates using dual cameras on a smartphone. PLoS One. 2016;11(3):e0151013. doi: 10.1371/journal.pone.0151013.
    1. Papon MTI, Ahmad I, Saquib N, Rahman A. Non-invasive heart rate measuring smartphone applications using on-board cameras: a short survey. 2015 International Conference on Networking Systems and Security (NSysS); January 5-7, 2015; Dhaka, Bangladesh. 2015.
    1. Pelegris P, Banitsas K, Orbach T, Marias K. A novel method to detect heart beat rate using a mobile phone. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:5488–91. doi: 10.1109/IEMBS.2010.5626580.
    1. Po LM, Xu XY, Feng LT, Li YM, Cheung KW, Cheung CH. Frame adaptive ROI for photoplethysmography signal extraction from fingertip video captured by smartphone. 2015 IEEE International Symposium on Circuits and Systems (ISCAS); May 24-27, 2015; Lisbon, Portugal. 2015. pp. 1634–1637.
    1. Scully CG, Lee J, Meyer J, Gorbach AM, Granquist-Fraser D, Mendelson Y, Chon KH. Physiological parameter monitoring from optical recordings with a mobile phone. IEEE Trans Biomed Eng. 2012 Feb;59(2):303–6. doi: 10.1109/TBME.2011.2163157.
    1. Wackel P, Beerman L, West L, Arora G. Tachycardia detection using smartphone applications in pediatric patients. J Pediatr. 2014 May;164(5):1133–5. doi: 10.1016/j.jpeds.2014.01.047.
    1. Kurylyak Y, Lamonaca F, Grimaldi D. Smartphone-based photoplethysmogram measurement. In: Duro RJ, López-Peña F, editors. Digital Image, Signal and Data Processing for Measurement Systems. Denmark: River Publishers; 2012. pp. 135–164.
    1. Terbizan DJ, Dolezal BA, Albano C. Validity of seven commercially available heart rate monitors. Meas Phys Educ Exerc Sci. 2002 Dec;6(4):243–247. doi: 10.1207/S15327841MPEE0604_3.
    1. Boulos MN, Wheeler S, Tavares C, Jones R. How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX. Biomed Eng Online. 2011;10:24. doi: 10.1186/1475-925X-10-24.
    1. Parak J, Uuskoski M, Machek J, Korhonen I. Estimating heart rate, energy expenditure, and physical performance with a wrist photoplethysmographic device during running. JMIR Mhealth Uhealth. 2017 Jul 25;5(7):e97. doi: 10.2196/mhealth.7437.
    1. Fallow BA, Tarumi T, Tanaka H. Influence of skin type and wavelength on light wave reflectance. J Clin Monit Comput. 2013 Jun;27(3):313–7. doi: 10.1007/s10877-013-9436-7.
    1. van Stralen KJ, Jager KJ, Zoccali C, Dekker FW. Agreement between methods. Kidney Int. 2008 Nov;74(9):1116–20. doi: 10.1038/ki.2008.306.
    1. Zaki R, Bulgiba A, Ismail R, Ismail NA. Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review. PLoS One. 2012;7(5):e37908. doi: 10.1371/journal.pone.0037908.
    1. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986 Feb 8;1(8476):307–10.

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