웨어러블 단말의 가속도 센서를 이용한 수면 중 움직임 및 자세를 감지하는 방법
A Method for Detecting Movement and Posture During Sleep Using an Acceleration Sensor of a Wearable Device
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The number of patients with many complications grows with the increase of aging population. As the elders and severely ill patients spend most of their time in bed, it leads to Pressure Injuries (PI) such as bedsores. Unfortunately, there is no method to automatically detect changes in patient’s posture which leads to the need for a caregiver every set of times when the patient needs to be moved. Many studies are conducted to solve this inefficient problem. Yet, these studies require costly devices or use methods that disturb patient’s sleeping environment. Those methods are mostly hard to implement in practice due to these reasons. We propose a method to detect posture using a three-axis acceleration sensor from the wrist band. We developed a wearable watch that measures sleep-related data. We analyzed 40 people’s sleep data with a wearable module and watch to measure their postures such as supine, left-side, and right-side. Then, we compared the classified posture from the watch with the wearable module and achieved 90% accuracy. Therefore, we concluded that only by using the wearable watch, we can detect the sleeping position without any new equipment or system to diagnose the patients without discomfort during their daily lives.
Abstract
The number of patients with many complications grows with the increase of aging population. As the elders and severely ill patients spend most of their time in bed, it leads to Pressure Injuries (PI) such as bedsores. Unfortunately, there is no method to automatically detect changes in patient’s posture which leads to the need for a caregiver every set of times when the patient needs to be moved. Many studies are conducted to solve this inefficient problem. Yet, these studies require costly devices or use methods that disturb patient’s sleeping environment. Those methods are mostly hard to implement in practice due to these reasons. We propose a method to detect posture using a three-axis acceleration sensor from the wrist band. We developed a wearable watch that measures sleep-related data. We analyzed 40 people’s sleep data with a wearable module and watch to measure their postures such as supine, left-side, and right-side. Then, we compared the classified posture from the watch with the wearable module and achieved 90% accuracy. Therefore, we concluded that only by using the wearable watch, we can detect the sleeping position without any new equipment or system to diagnose the patients without discomfort during their daily lives.
참고문헌 (10)
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