Development and Evaluation of an IoT-Based System for Near-Real-Time Average Heart Rate Monitoring in Team Sports

Abstract

Continuous and objective real-time internal load monitoring is essential in team sports but practically challenging to implement simultaneously for multiple athletes. This study aimed to develop and evaluate Mohan Pulsehub, an Internet of Things (IoT)-based real-time physiological monitoring system for multi-athlete average heart rate (HR) tracking. Employing a Research and Development (R&D) design, the system integrated Polar H10 sensors, wireless communication networks, and a centralized dashboard. Testing involved fourteen provincial-level male kabaddi athletes during a 2 x 20-minute match simulation scenario. Data aggregation was managed simultaneously by a central Bluetooth Low Energy (BLE) gateway receiver. System validation assessed data transmission performance through latency and packet loss. Concurrent validity against a commercial benchmark utilized the Intraclass Correlation Coefficient (ICC) and Mean Absolute Error (MAE), while practical usability employed the System Usability Scale (SUS). Results indicated that the system successfully connected all fourteen sensors with a 99.72% transmission success rate, demonstrating an average latency of 186.4 ms and 0.28% packet loss. Data agreement was near-perfect (ICC = 0.998, MAE = 0.45 bpm). Furthermore, a preliminary usability evaluation by three end-users (a head coach, an assistant coach, and a performance analyst) yielded a mean SUS score of 84.3 ± 5.6 (individual scores: 78.8, 84.7, and 89.4, calculated using standard SUS item weighting). Conclusively, while independent physiological validity remains to be established, the study demonstrates that the developed IoT architecture provides robust data transmission integrity and near-perfect software agreement for Polar H10 data, serving as a reliable and user-friendly tool, supporting the feasibility of simultaneous near-real-time internal load monitoring in team sports.