Validation of biofeedback wearables for photoplethysmographic heart rate tracking.

Author:Jo, Edward
Position:Research article - Report
 
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Introduction

Digital health, specifically wearable biosensor technology, has recently undergone tremendous advancements in the sport, fitness, and health industries. Initially developed to augment personal fitness and performance with basic quantitative biofeedback, the newest generation of devices, i.e. "activity trackers", provide real-world, immediate feedback on multiple biometrics related to the consumers' physical activity, health, and exercise quality (Lyons et al., 2014). With continuous technological advancements in wearable biofeedback devices, the potential applications have also expanded to include medical surveillance, non-invasive medical care, and mobile health-wellness monitoring.

The pursuit for practical and accurate methods to assess personal health and physical activity continues to lay emphasis on wearable and sophisticated biosensor technologies. It has been previously suggested that integrative biometric processing through multiple sensors (e.g. body temperature, skin galvanic response, heart rate, etc.) may support activity-specific prediction algorithms to accurately compute real-life energy expenditure and overall activity level (Chen and Bassett, 2005; Doherty and Oh, 2012; Gao et al., 2014). This has stimulated the adoption of multi-sensor technology in nascent activity trackers which has shown to outperform more rudimentary devices that utilize basic accelerometer data that record steps to infer movement, energy expenditure, and subsequently overall activity level. Moreover, with the inclusion of sophisticated reflective photoplethysmography (PPG) technology, contemporary activity trackers such as the Basis PeakTM (BPk) and Fitbit Charge HRTM (FB) have the capacity to use heart rate-derived algorithms to support energy expenditure estimations (Keytel et al., 2005; Luke et al., 1997; Wallen et al., 2016). Besides predicting energy expenditure, PPG-based heart rate detection allows for unobtrusive objective monitoring of physical exertion as well as systematic exercise prescriptions. The use of PPG technology for heart rate monitoring has shown acceptable validity, however there is inherent variability, indicating that the accuracy of these trackers is dependent on the specific device used and the type and intensity of activity. Therefore, PPG-based activity trackers remain under much scrutiny with respect to accuracy especially considering the number of extrinsic factors that may interrupt proper heart rate detection (i.e. ambient light, sweat, anatomical placement, movement, skin contact force) (Allen, 2007).

With the recent development of new types of activity trackers incorporating PPG-based heart rate sensors and multi-sensor technology, there needs to be a steady focus on improving overall device performance. With that said, validation of heart rate measurement accuracy for such multi-sensor activity trackers becomes a critical step in improving the consumer experience and at times, their safety. Notwithstanding, there is a paucity of rigorous, scientifically-based validation studies on the accuracy of multi-sensor trackers incorporating reflective PPG in reference to gold-standard methods for heart rate measurements, i.e. ECG. Therefore, the objective of this study was to determine the capability of two current generation activity trackers, the BPk and FB, to accurately measure heart rate during a variety of laboratory-based exercise tasks in reference to the ECG criterion measure. Moreover, this study aimed to assess the accuracy of heart rate measurements for these activity trackers specifically during differing levels of physical efforts (e.g. high vs. low ECG heart rate range) and exercise tasks (e.g. running, cycling, resistance exercise, isometric exercise, etc.).

Methods

Experimental design

Twenty-four college-aged subjects (12 males and 12 females) were recruited to participate in this randomized, controlled, crossover design study. Through random sampling methods subjects were recruited via posted flyers as well as mass email and social media solicitations. Each subject underwent an identical 77-minute protocol during a single visit to the Human Performance Research Laboratory at California State Polytechnic University, Pomona (CPP). Initially, participants completed and signed an informed consent form and underwent assessment for basic anthropometric measures (i.e. height, bodyweight). Subsequently, subjects underwent preparatory steps for 12-lead ECG testing procedures for criterion measurements for heart rate (HR) (described below). Next, researchers placed the Basis Peak (BPk) and Fitbit Charge HR (FB) on opposite wrists. Wrist assignment (i.e. dominant vs. non-dominant) was alternated between subjects for counterbalance and to control for any confounding effects associated with wrist assignment. Care was taken to follow proper-use guidelines as suggested by the manufacturer for each device. Time synced heart rate data from each device (test devices and ECG) were concurrently and continuously acquired second-by-second throughout the entire 77-minute protocol for each participant. During data acquisition, participants completed an initial rest period (supine) of 15 minutes (data excluded) followed by 5 minute periods of each of the following activities: low cycling (60W resistance), intense cycling (120W), walk (3.0-3.5mph speed), jog (4.0-5.0mph), run (5.5-7.0mph), arm raises with self-selected added resistance using dumbbells (12 reps), lunges with self-selected added resistance using dumbbells (12 reps), and isometric plank (60 second hold). In between each exercise task, a 5-minute sitting rest period was implemented during which time HR data was continuously acquired and included in the analysis. This study was approved by the CPP Institutional Review Board (ethics board).

Participants

Twenty-four healthy participants (12 males and 12 females) volunteered in this study (age = 24.8 [+ or -] 2.1 years, weight = 71.3 [+ or -] 9.9 kg, height = 1.66 [+ or -] 0.07 m). Written informed consent was obtained after discussing the study procedures in detail, including the voluntary nature of participation and notification that the subject can withdraw at any time. Upon the subject's agreement to...

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