Invisible ECG for High Throughput Screening in eSports

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 22; p. 7601
• Main Authors: Silva, Aline Santos, Correia, Miguel Velhote, Silva, Hugo Plácido
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 16.11.2021; MDPI
• Subjects: Electrocardiography; Esports; Exercise; Heart rate; invisibles; Keyboards; off-the-person; pervasive sensing; Physical fitness; Physiology; Sensors; Sleep; Success; Teams
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s21227601

eSports is a rapidly growing industry with increasing investment and large-scale international tournaments offering significant prizes. This has led to an increased focus on individual and team performance with factors such as communication, concentration, and team intelligence identified as important to success. Over a similar period of time, personal physiological monitoring technologies have become commonplace with clinical grade assessment available across a range of parameters that have evidenced utility. The use of physiological data to assess concentration is an area of growing interest in eSports. However, body-worn devices, typically used for physiological data collection, may constitute a distraction and/or discomfort for the subjects. To this end, in this work we devise a novel “invisible” sensing approach, exploring new materials, and proposing a proof-of-concept data collection system in the form of a keyboard armrest and mouse. These enable measurements as an extension of the interaction with the computer. In order to evaluate the proposed approach, measurements were performed using our system and a gold standard device, involving 7 healthy subjects. A particularly advantageous characteristic of our setup is the use of conductive nappa leather, as it preserves the standard look and feel of the keyboard and mouse. According to the results obtained, this approach shows 3–15% signal loss, with a mean difference in heart rate between the reference and experimental device of −1.778 ± 4.654 beats per minute (BPM); in terms of ECG waveform morphology, the best cases show a Pearson correlation coefficient above 0.99.