Key result
Physical activity features measured with wrist-worn devices can adequately represent selected gait features typically measured with lumbar-worn devices.
Why the study?
Deploying multiple wearable devices increases patient burden and trial complexity, creating a need to assess whether gait characteristics can be adequately represented by physical activity measured with wrist-worn devices alone.
Can gait characteristics measured by lumbar-worn devices be adequately represented by physical activity measured with wrist-worn accelerometers in healthy participants?
Observational
Can gait characteristics measured by lumbar-worn devices be adequately represented by physical activity measured with wrist-worn accelerometers in healthy participants?
Answers are grounded in this paper and cite their sources.
Wrist-worn accelerometers may be sufficient to capture gait characteristics typically requiring lumbar devices, potentially reducing patient burden and operational complexity in clinical trials.
Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant's naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients' comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities.
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Lin et al. (2023) conducted an observational in Healthy. Physical activity measured with wrist-worn accelerometers vs. Gait characteristics measured with lumbar-worn accelerometers was evaluated on Representation of gait characteristics by physical activity features. Physical activity features measured with wrist-worn devices can adequately represent selected gait features typically measured with lumbar-worn devices.
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