The Impact of Wearable Technologies in Health Research: Scoping Review

• Published in: JMIR mHealth and uHealth Vol. 10; no. 1; p. e34384
• Main Authors: Huhn, Sophie, Axt, Miriam, Gunga, Hanns-Christian, Maggioni, Martina Anna, Munga, Stephen, Obor, David, Sié, Ali, Boudo, Valentin, Bunker, Aditi, Sauerborn, Rainer, Bärnighausen, Till, Barteit, Sandra
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 25.01.2022
• Subjects: Accuracy; Blood pressure; Body temperature; Cardiac arrhythmia; Consumers; Coronaviruses; COVID-19; Fitness Trackers; Heart rate; Humans; Intervention; Medical research; Multimedia; Pandemics; Rare diseases; Review; SARS-CoV-2; Sensors; Signs; Sleep; Software; Wearable computers; Wearable Electronic Devices; Wrist; United States > US; global health; wearable; population health; mHealth; consumer-grade wearables; low-resource setting; research; fitness trackers; commercially available wearables; mobile phone; review; tracker; big data; public health
• DOI: 10.2196/34384
• ISSN: 2291-5222

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing. We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations-wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%). Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.