ABSTRACT
INTRODUCTION: Real-time digital heart rate (HR) monitoring in sports can provide unique physiological insights into athletic performance. However, most HR monitoring of elite athletes is limited to non-real-time, non-competition settings while utilizing sensors that are cumbersome. The present study was undertaken to test the feasibility of using small, wearable medical-grade sensors, paired with a novel technology system, to capture and process real-time HR data from elite athletes during professional competition. METHODS: We examined the performance of the BioStamp nPoint® sensor compared to the Polar chest strap HR sensor in 15 Professional Squash Association (PSA) tournament matches in 2019-2020. Fourteen male professional squash players volunteered for the study (age = 23.8 ± 4.9 years; height = 177.9 ± 7.1 cm; weight = 71 ± 7.0 kg), which was approved by the PSA in accordance with their Code of General Conduct and Ethics. Algorithms developed by Sports Data Labs (SDL; Detroit, MI, USA) used proprietary data collection, transmission, and signal processing protocols to produce HR values in real-time during matches. We calculated the mean and maximum HR from both sensors and used widely accepted measures of agreement to compare their performance. RESULTS: The system captured 99.8% of HR data across all matches (range 98.3-100%). The BioStamp's mean HR was 170.4 ± 20.3 bpm, while the Polar's mean HR was 169.4 ± 21.7 bpm. Maximum HR ranged from 182 to 202 bpm (Polar) and 185 to 203 bpm (BioStamp). Spearman's correlation coefficient (r s) was 0.986 (p < 0.001), indicating a strong correlation between the 2 devices. The mean difference (d) in HR was 1.0 bpm, the mean absolute error was 2.2 bpm, and the percent difference was 0.72%, demonstrating high agreement between device measurements. CONCLUSIONS: It is feasible to accurately measure and monitor real-time HR in elite athletes during competition using BioStamp's and SDL's proprietary system. This system facilitates development and understanding of physiological digital biomarkers of athletic performance and physical and psychosocial demands in elite athletic competition.
ABSTRACT
BACKGROUND: Increasingly, drug and device clinical trials are tracking activity levels and other quality of life indices as endpoints for therapeutic efficacy. Trials have traditionally required intermittent subject visits to the clinic that are artificial, activity-intensive, and infrequent, making trend and event detection between visits difficult. Thus, there is an unmet need for wearable sensors that produce clinical quality and medical grade physiological data from subjects in the home. The current study was designed to validate the BioStamp nPoint® system (MC10 Inc., Lexington, MA, USA), a new technology designed to meet this need. OBJECTIVE: To evaluate the accuracy, performance, and ease of use of an end-to-end system called the BioStamp nPoint. The system consists of an investigator portal for design of trials and data review, conformal, low-profile, wearable biosensors that adhere to the skin, a companion technology for wireless data transfer to a proprietary cloud, and algorithms for analyzing physiological, biometric, and contextual data for clinical research. METHODS: A prospective, nonrandomized clinical trial was conducted on 30 healthy adult volunteers over the course of two continuous days and nights. Supervised and unsupervised study activities enabled performance validation in clinical and remote (simulated "at home") environments. System outputs for heart rate (HR), heart rate variability (HRV) (including root mean square of successive differences [RMSSD] and low frequency/high frequency ratio), activity classification during prescribed activities (lying, sitting, standing, walking, stationary biking, and sleep), step count during walking, posture characterization, and sleep metrics including onset/wake times, sleep duration, and respiration rate (RR) during sleep were evaluated. Outputs were compared to FDA-cleared comparator devices for HR, HRV, and RR and to ground truth investigator observations for activity and posture classifications, step count, and sleep events. RESULTS: Thirty participants (77% male, 23% female; mean age 35.9 ± 10.1 years; mean BMI 28.1 ± 3.6) were enrolled in the study. The BioStamp nPoint system accurately measured HR and HRV (correlations: HR = 0.957, HRV RMSSD = 0.965, HRV ratio = 0.861) when compared to ActiheartTM. The system accurately monitored RR (mean absolute error [MAE] = 1.3 breaths/min) during sleep when compared to a Capnostream35TM end-tidal CO2 monitor. When compared with investigator observations, the system correctly classified activities and posture (agreement = 98.7 and 92.9%, respectively), step count (MAE = 14.7, < 3% of actual steps during a 6-min walk), and sleep events (MAE: sleep onset = 6.8 min, wake = 11.5 min, sleep duration = 13.7 min) with high accuracy. Participants indicated "good" to "excellent" usability (average System Usability Scale score of 81.3) and preferred the BioStamp nPoint system over both the Actiheart (86%) and Capnostream (97%) devices. CONCLUSIONS: The present study validated the BioStamp nPoint system's performance and ease of use compared to FDA-cleared comparator devices in both the clinic and remote (home) environments.
