Sadek Ibrahim, Abdulrazak Bessam
Ambient Intelligence Laboratory (AMI-Lab), Computer Science Department, Faculty of Science, University of Sherbrooke, Sherbrooke, Canada.
Biomedical Engineering Department, Faculty of Engineering, Helwan University, Helwan, Egypt.
Health Syst (Basingstoke). 2022 May 8;12(3):264-280. doi: 10.1080/20476965.2022.2072777. eCollection 2023.
Sleep is so important, particularly for the elderly. The lack of sleep may increase the risk of cognitive decline. Similarly, it may also increase the risk of Alzheimer's disease. Nonetheless, many people underestimate the importance of getting enough rest and sleep. In-laboratory polysomnography is the gold-standard method for assessing the quality of sleep. This method is considered impractical in the clinical environment, seen as labour-intensive and expensive owing to its specialised equipment, leading to long waiting lists. Hence, user-friendly (remote and non-intrusive) devices are being developed to help patients monitor their sleep at home. In this paper, we first discuss commercially-available non-wearable devices that measure sleep, in which we highlight the features associated with each device, including sensor type, interface, outputs, dimensions, power supply, and connectivity. Second, we evaluate the feasibility of a non-wearable device in a free-living environment. The deployed device comprises a sensor mat with an integrated micro-bending multimode fibre. Raw sensor data were gathered from five senior participants living in a senior activity centre over a few to several weeks. We were able to analyse the participants' sleep quality using various sleep parameters deduced from the sensor mat. These parameters include the wake-up time, bedtime, the time in bed, nap time. Vital signs, namely heart rate, respiratory rate, and body movements, were also reported to detect abnormal sleep patterns. We have employed pre-and post-surveys reporting each volunteer's sleep hygiene to confirm the proposed system's outcomes for detecting the various sleep parameters. The results of the system were strongly correlated with the surveys for reporting each sleep parameter. Furthermore, the system proved to be highly effective in detecting irregular patterns that occurred during sleep.
睡眠非常重要，尤其是对老年人而言。睡眠不足可能会增加认知能力下降的风险。同样，它也可能增加患阿尔茨海默病的风险。然而，许多人低估了充足休息和睡眠的重要性。实验室多导睡眠图是评估睡眠质量的金标准方法。由于其专门的设备，这种方法在临床环境中被认为不切实际，既耗费人力又昂贵，导致等待名单很长。因此，正在开发用户友好型（远程且非侵入性）设备，以帮助患者在家中监测睡眠。在本文中，我们首先讨论市售的用于测量睡眠的非穿戴设备，其中我们突出了与每个设备相关的特征,包括传感器类型、接口、输出、尺寸、电源和连接性。其次，我们评估一种非穿戴设备在自由生活环境中的可行性。所部署的设备包括一个带有集成微弯多模光纤的传感垫。从居住在一个老年活动中心的五名老年参与者那里收集了数周甚至数周以上的原始传感器数据。我们能够使用从传感垫推导出来的各种睡眠参数来分析参与者的睡眠质量。这些参数包括起床时间、就寝时间、卧床时间、小睡时间。还报告了生命体征，即心率、呼吸频率和身体运动情况，以检测异常睡眠模式。我们采用了前后调查，报告每位志愿者的睡眠卫生状况，以确认所提出的系统在检测各种睡眠参数方面的结果。该系统的结果与报告每个睡眠参数的调查结果高度相关。此外，该系统在检测睡眠期间出现的不规则模式方面被证明非常有效。
