Development and evaluation of a heart rate sensor software for team sports monitoring

Abstract

Mankind has always been passionate about competing in sports of all sorts. First known sports originate thousands of years back in time. Despite the long history of sports, the last decades and years of technological improvements are now changing the nature of sports as we know it. Better technology has provided us ways to measure, quantify and analyse athlete performance in more detailed and profound ways than ever before. These tools have led to even more disciplined training programs, pushing the limits of athletes further and further. However, especially in team sports the best exercise programs and appropriate loads of training are hard to estimate. Every athlete and team are unique, as well as the training scenarios and games where the athletes push themselves. Therefore, there is an ever-increasing need for even better and more versatile monitoring tools to meet the needs of team sports.

In this thesis the objectives were to develop and evaluate a next generation elite team sports wearable heart rate monitoring and sensor solution for the heart rate and sports analytics company Firstbeat Technologies Oy. The work consists of evaluating an existing sensor system solution Suunto Movesense and developing an application on top of it to meet the needs of demanding team sports. The developed sensor software integrates an existing physiological algorithm monitoring library into the Movesense sensor, enabling wireless real-time monitoring of athletes with analytics being run on the sensor itself. The real-time analytics of each athlete is broadcasted over BLE advertising to a client device responsible for capturing and visualizing the data to team coaches. RR-intervals of measured ECG signal are also internally saved to non-volatile memory. This ensures that no single beat is lost, making all data accessible during and after the exercises. Client communication APIs for managing the sensor and data transfers were built on top of Movesense libraries.

As part of the thesis, performance of the ECG R-peak detection algorithm of the Movesense sensor was also measured and evaluated against Firstbeat’s Bodyguard 2 monitoring device in a controlled field test. Suitability of the Movesense sensor and final software are also evaluated against predefined use cases.

Development of the sensor software was performed in an iterative manner by continuously evaluating the sensor’s performance based on feedback from on-going team sports field test reports. Summaries from field-test reports are provided and analysed as part of this thesis, to evaluate the sensor software development process and the performance of the sensor. Reports of memory usage and power consumption are reported. A simple RRI-signal generator was also devised and used for testing and development purposes. Preliminary plans for continuous integration (CI) pipeline with hardware-in-the-loop simulation testing are briefly discussed.

The result of the thesis project is a market-ready consumer product Firstbeat Sports sensor, which meets the needs and requirements set by the business. The reported results show that the sensor can reliably work in the challenging use cases of professional team sports. Future work and challenges of the development process are discussed at the end of the thesis.