Adjustment for physical activity in high-frequency biosensor data

Music City Center 

Remote safety monitoring using biosensor devices presents advantages compared to traditional clinical approach for physiological parameters (e.g. blood pressure and heart rate). It operates remotely and do not need frequent site visits, thus significantly reduces burden on patients and clinical sites. However, physiological parameters are highly impacted by physical activity (PA), which makes the variability of physiological parameters in remote setting larger than that in clinical visit. The higher variability results in less precision in safety endpoint estimation. We developed a spline-based model to quantify the individualized relationship between heart rate (HR) and PA, and conducted adjustment of HR to remove the impact of PA. This method is applied on a biosensor data which contains simultaneous high-frequency data of HR and PA. Compared with traditional parametric model, our model has better fitting performance. The adjusted HR has much less influence of PA and shows reduced variability. This adjustment approach can help future clinical trials when applying biosensor device and is easy to implement.

biosensor data

spline method

high frequency

adjustment for physical activity 

Biopharmaceutical Section