Monitoring cardio-respiratory and posture movements during sleep: What can be achieved by a single motion sensor

Quality of sleep is an important index of wellbeing and health. Irregular sleep patterns are often associated with stress and disorders such as cardiovascular disease, diabetes, depression, sleep apnea and obesity. In addition to key physiological indices, body movements and posture during sleep are also important for assessing causal relationship of irregular sleep patterns and underlying health issues. In this paper, we explore the feasibility of using a single accelerometer strapped onto the chest to detect posture and cardio-respiratory parameters during sleep. An efficient movement detector suitable for on-node implementation is developed to distinguish static postures from dynamics movements. When in static postures, a linear discriminant analysis (IDA) classifier is used to further divide the static postures into four common sleeping positions. Simultaneously, both heart rate and respiratory rate are extracted from the acceleration signal. A small cohort of 7 healthy subjects were recruited for lab-controlled experiments to evaluate the performance of our proposed methods. ECG signal and K4b2 system's V02 measurements were also collected to extract heart rate and respiratory rate as the ground truth for comparison. An overall classification accuracy of 99% is achieved for recognising the correct sleeping positions. Good matches to ground truths were also obtained for the derived cardiac and respiratory rates.