A mobile application to monitor heart rate (HR) during an exercise called Chromozone was developed to enable a user to regulate exercise intensity using a color-coded system rather than numerical display in the most conventional device. In this study, the agreement of HR from Chromozone was compared against the HR dataset from a clinically accepted electrocardiogram (ECG) on different exercise intensity and to assess its reliability by intra-day repeated assessments. Additionally, the usability aspect of the Chromozone smartphone application was also assessed. Forty-two participants underwent self-selected exercise intensities (based on individual HR reserve) included for 5-min followed by a cool-down period (3-min). A 20-min rest period was given to the participant before repeating the same exercise protocol two more times. Chromozone was found to generate excellent criterion-concurrent validity (r = 0.998, p < 0.001) and acceptable bias of 1.96 bpm (Limits of Agreement; LoA: 3.07 to -3.51) for relative and absolute agreement, respectively. Similarly, relative (intraclass correlation coefficient test: 0.998, p < 0.001) and absolute (within-subject coefficient of variation: 1.95 ± 1.4%) reliability using Chromozone application shows an excellent consistency. Additionally, this study also showed that the usability level of the Chromozone application is beyond the satisfactory level. The outcome of this work provides strong support for Chromozone application as a valid and reliable exercise HR monitoring tool that could potentially help athletes, active individuals as well as the clinical population to monitor and regulate their exercise training regime more effectively.

• Andrade, A., Casagrande, P., Bevilacqua, G., Pereira, F., Matte, D., & Coimbra, D. (2019). Burnout in elite junior tennis players: A multiple case study. Revista de Psicologia Del Deporte, 28(4), 97-105.

• Bland, J., & Altman, D. (1987). Caveat doctor: A grim tale of medical statistics textbooks. British Medical Journal (Clinical Research Ed.), 295(6604), 979. https://doi.org/10.1136/bmj.295.6604.979

• Bull, F., Al-Ansari, S., Biddle, S., Borodulin, K., Buman, M., Cardon, G., Carty, C., Chaput, J., Chastin, S., Chou, R., Dempsey, P., Dipietro, L., Ekelund, U., Firth, J., Friedenreich, C., Garcia, L., Gichu, M., Jago, R., Katzmarzyk, P., … & Willumsen, J. (2020). World Health Organization 2020 guidelines on physical activity and sedentary behaviour. British Journal of Sports Medicine, 54(24), 1451-1462. https://doi.org/10.1136/bjsports-2020-102955

• Coppetti, T., Brauchlin, A., Müggler, S., Attinger, A., Templin, C., Schönrath, F., Hellermann, J., Lüscher, T., Biaggi, P., & Wyss, C. (2017). Accuracy of smartphone apps for heart rate measurement. European Journal of Preventive Cardiology, 24(12), 1287-1293. https://doi.org/10.1177/2047487317702044

• Gaynor, M., Sawyer, A., Jenkins, S., & Wood, J. (2019). Variable agreement between wearable heart rate monitors during exercise in cystic fibrosis. ERJ Open Research, 5(4), 00006-02019. https://doi.org/10.1183/23120541.00006-2019

• Goulet, M., & Cousineau, D. (2019). The power of replicated measures to increase statistical power. Advances in Methods and Practices in Psychological Science, 2(3), 199-213. https://doi.org/10.1177/2515245919849434

• Harun, C., Zulkarnain, N., Aziz, M., Mahmood, N., Kamarudin, M., & Linoby, A. (2011). Pulse oximetry color coded heart rate monitoring system using Zigbee. In 5th Kuala Lumpur International Conference on Biomedical Engineering 2011 (pp. 348-351). Springer. https://doi.org/10.1007/978-3-642-21729-6_90

• Harun, F., Zulkarnain, N., Aziz, M., Mahmood, N., Kamarudin, M., & Linoby, A. (2011). Pulse oximetry color coded heart rate monitoring system using ZigBee. IFMBE Proceedings, 35, 348-351. https://doi.org/10.1007/978-3-642-21729-6_90

• Hoffmann, B., Flatt, A., Silva, L., Nczak, M., Baranowski, R., Dziedzic, E., Werner, B., & Gasior, J. (2020). A pilot study of the reliability and agreement of heart rate, respiratory rate and short-term heart rate variability in elite modern pentathlon athletes. Diagnostics, 10(10), Article 833. https://doi.org/10.3390/diagnostics10100833

• Hu, W., Miyato, T., Tokui, S., Matsumoto, E., & Sugiyama, M. (2017). Learning discrete representations via information maximizing self-augmented training. In 34th International Conference on Machine Learning, ICML 2017 (Vol. 4, pp. 2467-2481). MLResearch Press.

• Lee, M., Lee, H., Kim, Y., Kim, J., Cho, M., Jang, J., & Jang, H. (2018). Mobile app-based health promotion programs: A systematic review of the literature. International Journal of Environmental Research and Public Health, 15(12), Article 2838. https://doi.org/10.3390/ijerph15122838

• Leonard, A., & Simpson, S. (2017). The accuracy of heart rate-based zone training using predicted versus measured maximal heart rate (Master thesis). University of Wisconsin-La Crosse, USA. https://minds.wisconsin.edu/handle/1793/76886

• Linoby, A., Asraff, I., Rodzi, A., Mauzaulan, M., Abdul, R., & Abdul, M. (2019). iCobra: A smartphone application for monitoring real-time exercise heart rate using color-coded system. IEEE Reviews in Biomedical Engineering, 9(1), 95-98.

• Linoby, A., Khairi, F., & Kamaruddin, F. (2014). Development of heart rate monitor using colour-coding system to communicate exercise intensity. In Proceedings of the International Colloquium on Sports Science, Exercise, Engineering and Technology 2014 (ICoSSEET 2014) (pp. 421-428). Springer. https://doi.org/10.1007/978-981-287-107-7_44

• Linoby, A., Kusrin, J., Asraf, M. I., Rodzi, M. A., Zaki, S., & Hasan, H. (2020). Chromozone: iOS-based exercise heart rate application using universal colour-coding system. Jurnal Inovasi Malaysia, 4(1), 193-208.

• Mahmood, N., Uyop, N., Zulkarnain, N., Harun, F., Kamarudin, M., & Linoby, A. (2011). LED indicator for heart rate monitoring system in sport application. In 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications (pp. 64-66). IEEE Publishing. https://doi.org/10.1109/CSPA.2011.5759843

• Maramba, I., Chatterjee, A., & Newman, C. (2019). Methods of usability testing in the development of eHealth applications: A scoping review. International Journal of Medical Informatics, 126(February), 95-104. https://doi.org/10.1016/j.ijmedinf.2019.03.018

• Mehta, S., Bastero, R., Sun, Y., Zhu, R., Murphy, D., Hardas, B., & Koch, G. (2018). Performance of intraclass correlation coefficient (ICC) as a reliability index under various distributions in scale reliability studies. Statistics in Medicine, 37(18), 2734-2752. https://doi.org/10.1002/sim.7679

• Rjoob, K., Bond, R., Finlay, D., McGilligan, V., Leslie, S., Rababah, A., Guldenring, D., Iftikhar, A., Knoery, C., McShane, A., & Peace, A. (2020). Machine learning techniques for detecting electrode misplacement and interchanges when recording ECGs: A systematic review and meta-analysis. Journal of Electrocardiology, 62, 116-123. https://doi.org/10.1016/j.jelectrocard.2020.08.013

• Schneider, C., Hanakam, F., Wiewelhove, T., Döweling, A., Kellmann, M., Meyer, T., Pfeiffer, M., & Ferrauti, A. (2018). Heart rate monitoring in team sports - A conceptual framework for contextualizing heart rate measures for training and recovery prescription. Frontiers in Physiology, 9, Article 639. https://doi.org/10.3389/fphys.2018.00639

• Stegmann, G., Hahn, S., Liss, J., Shefner, J., Rutkove, S., Kawabata, K., Bhandari, S., Shelton, K., Duncan, C., & Berisha, V. (2020). Repeatability of commonly used speech and language features for clinical applications. Digital Biomarkers, 4(3), 109-122. https://doi.org/10.1159/000511671

• Thomson, E., Nuss, K., Comstock, A., Reinwald, S., Blake, S., Pimentel, R., Tracy, B., & Li, K. (2019). Heart rate measures from the Apple Watch, Fitbit Charge HR 2, and electrocardiogram across different exercise intensities. Journal of Sports Sciences, 37(12), 1411-1419. https://doi.org/10.1080/02640414.2018.1560644

• Trobec, R., Tomasiv, I., Rashkovska, A., Depolli, M., & Avbelj, V. (2018). Commercial electrocardiograpm systems. In SpringerBriefs in Applied Sciences and Technology (pp. 101-114). Springer. https://doi.org/10.1007/978-3-319-59340-1_6

• Weichbroth, P. (2020). Usability of mobile applications: A systematic literature study. IEEE Access, 8, 55563-55577. https://doi.org/10.1109/ACCESS.2020.2981892

• Xiong, J., Ziegler, C., & Kortum, P. (2020). SUSapp: A free mobile application that makes the system usability scale (SUS) easier to administer. Journal of Usability Studies, 15(3), 135-144.