Unobtrusive monitoring of cardiorespiratory signals during sleep based on PVDF sensor and singular spectrum analysis

Abstract

Unobtrusive cardiorespiratory monitoring in the period of sleep could facilitate researchers for sleep analysis and sleep disorders diagnosis. With the recent advancement of biomedical health informatics, it is possible to monitor individual's sleep disorders through cardiovascular parameters. This paper proposes a polyvinylidene fluoride (PVDF) sensor based system for unobtrusive measurements of respiration and heartbeat while sleeping; the sensing unit is deployed on the mattress below the back area of the subject. The PVDF sensor generates the sensory activations due to pulsatile pressure change caused by respiratory and heartbeat movement. To extract and separate the heartbeat and respiration accurately, the method singular spectrum analysis (SSA) was applied while the empirical mode decomposition (EMD) and wavelet analysis methods were used for comparison. Experiments are conducted on two healthy subjects to obtain the respiratory rate and heart rate. To verify and compare the performance of the proposed system, the polysomnography (PSG) system was used to record the thorax effort signal and electrocardiography (ECG) as the gold standard for extracting the respiratory rate and heart rate respectively. The average error rate (AER) of respiratory rate extraction is noted 8.53%, with segmenting the data as 2 mins epochs. Meanwhile, the AERs of the heart rate are 8.01%, 8.80%, 8.55% by utilizing the SSA, EMD and wavelet methods respectively. Overall, the proposed system can obtain accurate respiration and heart rate detection. And the novelty lies in introducing a flexible PVDF sensor which can be combined with the sleep mat for cardiorespiratory signal monitoring in home environment; and new SSA algorithm to extract respiration and heart rates. The experimental results are promising which demonstrated that the proposed system satisfied the basic requirements for cardiorespiratory signal monitoring during sleep.