Sleep Monitoring Based on a Tri-Axial Accelerometer and a Pressure Sensor

• Published in: Sensors (Basel, Switzerland) Vol. 16; no. 5; p. 750
• Main Authors: Nam, Yunyoung, Kim, Yeesock, Lee, Jinseok
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI 23.05.2016; MDPI AG
• Subjects: Algorithms; Biosensing Techniques - instrumentation; Blood Pressure Monitors; breathing; health care; Heart Rate - physiology; heart rate variability; Humans; Monitoring, Physiologic - instrumentation; Polysomnography; pressure sensor; Respiration; sleep apnea; Sleep Apnea Syndromes - diagnosis; Sleep Apnea Syndromes - physiopathology; sleep monitoring; Sleep Wake Disorders - diagnosis; Sleep Wake Disorders - physiopathology; sleeping pose; pressure sensor; sleeping pose; breathing; heart rate variability; polysomnography; sleep apnea; sleep monitoring; health care
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s16050750

Sleep disorders are a common affliction for many people even though sleep is one of the most important factors in maintaining good physiological and emotional health. Numerous researchers have proposed various approaches to monitor sleep, such as polysomnography and actigraphy. However, such approaches are costly and often require overnight treatment in clinics. With this in mind, the research presented here has emerged from the question: "Can data be easily collected and analyzed without causing discomfort to patients?" Therefore, the aim of this study is to provide a novel monitoring system for quantifying sleep quality. The data acquisition system is equipped with multimodal sensors, including a three-axis accelerometer and a pressure sensor. To identify sleep quality based on measured data, a novel algorithm, which uses numerous physiological parameters, was proposed. Such parameters include non-REM sleep time, the number of apneic episodes, and sleep durations for dominant poses. To assess the effectiveness of the proposed system, three participants were enrolled in this experimental study for a duration of 20 days. From the experimental results, it can be seen that the proposed monitoring system is effective for quantifying sleep quality.