Key result
IoT-based sensor platform monitors athlete performance with a ~0.4% heart rate error margin.
Why the study?
Indonesian athletic achievements have declined due to a lack of media able to record athletes' field abilities before, during, and after running.
Observational (n=20)
No
An IoT-based system using heart rate and motion sensors can accurately record athlete performance in real-time with a low error margin.
May support real-time athlete monitoring; leaves open clinical validation before cardiovascular use.
Indonesian achievements in the ASEAN Games continued to decline in achievement starting in 1962 with the acquisition of 51 medals and up to 2014 with the acquisition of 20 medals. The decline in achievement was due to the lack of athletic resources due to the absence of media that could record athletes' abilities in the field. Can record the athlete's performance before running, running and after running using the Heart Rate sensor and Motion Capture sensor. The results of the sensor recording will be stored in the database. This system applies the Internet of Things (IoT) concept, using raspberry pi, Arduino microcontroller, T34 polar heart rate sensor to capture and send heartbeat to receivers, gyro-based motion-capture sensors that named wear notch where this sensor serves to capture the movement of athletes, sensors communicate with the system using 4G connectivity, use MQTT as edge computing which acts as a communication medium from sensors to databases, Maria DB and influx DB as accumulation which plays a role in storing heart rate and athlete's movements that have been recorded by sensors, athlete performance monitoring platform with a heart rate sensor and athlete's motion capture is a web-based application that collaborates all processes from the sensor to the system. Sensor heart rate recording results are categorized good because the error margin is only 0.4%. Wearnotch sensor data can be stored in the database, and athletic data can be recorded before sports, while sports, and after sports in real-time
No takes yet. Share an insight, caveat, or question.
Yani et al. (2019) conducted an observational in Healthy volunteers (athletes and non-athletes) (n=20). IoT-based heart rate and motion sensor monitoring vs. Standard sensors (Pulse Finger Sensor, Xiaomi Mi Band 3) was evaluated on Heart rate measurement error margin compared to pulse finger sensor and Xiaomi Mi Band 3. The implemented IoT-based heart rate and motion sensor platform successfully monitored athlete performance, demonstrating a heart rate measurement error margin of only 0.4%.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: