The Evaluation of Remote Monitoring Technology Across Participants With Different Skin Tones

Background: Many research studies seek to improve vital sign monitoring to enhance the conditions under which doctors and caregivers track patients' health. Non-invasive and contactless monitoring has emerged as an optimal solution for this problem, with telemedicine, self-monitoring, and well-being tools being the next generation of technology in the biomedical field. However, there is worldwide concern about the general purpose and bias toward a certain demographic group of these techniques. In particular, skin tone and the accuracy of monitoring dark skin tone groups have been key questions among researchers, with the lack of results and studies contributing to this uncertainty. Methods: This paper proposes a benchmark for remote monitoring solutions against a medical device across different skin tone people. Around 330 videos from 90 patients were analyzed, and heart rate (HR) and heart rate variability (HRV) were compared across different subgroups. The Fitzpatrick scale (1-6) was used to classify participants into three skin tone groups: 1 and 2, 3 and 4, and 5 and 6. Results: The results showed that our proposed methodology could estimate heart rate with a mean absolute error of 3 bpm across all samples and subgroups. Moreover, for heart rate variability (HRV) metrics, we achieved the following results: in terms of mobility assistive equipment (MAE), the HRV-inter-beat interval (IBI) was 10 ms, the HRV-standard deviation of normal to normal heartbeats (SDNN) was 14 ms, and the HRV-root mean square of successive differences (RMSSD) between normal heartbeats was 22 ms. No significant performance decrease was found for any skin tone group, and there was no error trend toward a certain group. Conclusions: The study showed that our methodology meets acceptable agreement levels for the proposed metrics. Furthermore, the experiments showed that skin tone did not impact the results, which remained within the same range across all groups. Moreover, it enables the end users to understand their general well-being and improve their overall health.