Wearable Devices in Asthma
Most of the wearable fitness device research to date has focused in diseases associated with low levels of physical activity, namely cardiovascular disease, diabetes, and cancer. Few have focused on asthma and of the studies conducted in asthma populations, all have honed in on the use of Fitbit-derived sleep measures (i.e., sleep quality). Castner et al. used the Fitbit Charge™ to validate sleep measures in women with asthma [18••]. The sleep measures collected by the Fitbit were compared with Actigraph GT3X +, a well-known and validated device to collect sleep measures [19, 20]. The Fitbit device tended to overestimate sleep efficiency and underestimate wake counts compared with actigraphy. Two additional studies were conducted in pediatric populations and focused on correlating Fitbit-derived sleep measures to patient-reported outcomes such as asthma control and asthma impact [21, 22]. Bian and colleagues assessed the association between self-reported asthma impact and Fitbit-derived sleep quality (the ratio of minutes asleep to minutes in bed) and physical activity measures (daily minutes of moderate and vigorous activity) in adolescents with asthma [21]. Fitbit-derived sleep quality was moderately correlated with Patient-Reported Outcomes Measurement Information System (PROMIS) sleep disturbance score (r = − 0.31, P = 0.01) and had a weak but significant correlation with the PROMIS pediatric asthma impact score (average r = − 0.18, P = 0.02). Fitbit-derived physical activity levels were not associated with PROMIS pediatric asthma impact (r = 0.04, P = 0.62). These findings suggest that measurement of sleep quality, using the Fitbit device, may help develop personalized asthma management strategies for children and their caregivers in real time. The final study measured several mobile metrics of asthma including physical activity and sleep using Fitbits, forced expiratory volume in 1 s and peak expiratory flow, indoor air quality using Foobot (https://foobot.io/), and a mobile app that collected information on asthma control (symptoms, physical limitations due to asthma, nighttime awakenings, and medication intake) [22]. These metrics were used together to digitally phenotype children with asthma and provide a better measure of the patient’s asthma control to their clinician when compared with the Asthma Control Test scores taken infrequently during clinic visits. Additional work using this ecological metric of asthma control is needed and may be used in the future to generate insights on the relationship between a patient’s asthma symptoms and triggers across different seasons [23].
Acoustic monitoring is another type of wearable devices that has been studied in asthma. Breathing sound measured by microphones over human skin can detect breathing patterns (respiratory rate, flow rate, tidal volume) and symptoms that may be due to asthma (wheeze, cough). Moreover, chest movement signals can be acquired using an accelerometer or belt-shaped device [24, 25]. Boner et al. measured the nocturnal wheeze in children with asthma using an acoustic respiratory monitor. They found that among children with apparently well-controlled asthma, 57% had considerable amounts of night wheezing that was unrelated to conventional measures of lung function [26]. The use of these continual wearable monitoring systems is still a developing field that needs further study on its clinical impact.