Multichannel bed pressure sensor for sleep monitoring

A bed sensor with multiple pressure sensitive non-contacting electrodes has been applied for unobtrusive monitoring during sleep. The novelty is in using multichannel algorithms to improve extraction of the heart rate and respiration signal from the recorded ballistocardiographic (BCG) data. Heart rate is extracted by using a sliding Fourier Transform, and after averaging the sensor channels in the frequency domain, the attained resolution enables to detect individual heart beat intervals (HBI) and estimate the heart rate variability (HRV). The respiration signal is calculated from the low pass filtered BCG signals by updating the linear coefficients with an adaptive principal component analysis (PCA) model. In comparison to the reference ECG R-R interval, the relative error of the HBI has been 0.40 % with 88 % measurement coverage for the healthy subjects during normal sleep. The error of the respiratory rate estimated from the bed sensor has been 1.5 % in comparison with the respiratory inductive plethysmogram (RIP). For the group of patients having different kinds of suspected sleep disorders, the measurement coverage varied a lot between subjects due to increased movement artifacts. In this case, some examples of detecting respiratory disorders with bed sensor signals are shown.