Validating novel sleep sensors and devices in older adults with Alzheimer's disease

项目摘要 易于访问、用户友好且经过验证的家庭睡眠监控技术 对老年人的研究、商业和临床需求都很高。监控 患者家中的多种生理信号提供了一个很有希望的机会 临床医生改善治疗结果并方便地获得相关健康 老年人的指标。新的商业级和研究级设备不断出现 不断发展，以满足消费者日益增长的需求并提高准确性。为了提高 精确度，越来越多的设备正在集成更广泛的生理 过程(例如，心率、血氧饱和度、心电图)。然而，科学的验证研究 对这些设备的准确性和性能的检查是最小的，而且是完全的 在患有常见慢性病的老年人和患有 阿尔茨海默病和阿尔茨海默病相关痴呆(AD/ADRD)。但仍有针对性 考虑到与衰老和AD相关的步态变化，这些组的研究是必要的， 移动性和可能降低设备准确性的生理过程。 这项研究旨在验证商用的睡眠检测功能 具有生理传感器的设备在不同的具有代表性的老年人样本中 有常见慢性病和AD/ADRD组。设备性能将 在家庭环境中接受检查，并与黄金标准睡眠测量进行比较 多导睡眠图--脑电、肌电和眼电的蒙太奇。此外，随着一系列 调查问卷，我们将确定高实用设备的功能、使用障碍和其他 与改进未来设备开发和合规性相关的方面 研究和商业环境。我们认为这是重要的第一步， 部署用于健康和研究的设备。

Project Summary Easily accessible, user friendly, and validated in-home sleep monitoring technologies are in high research, commercial, and clinical demand for older adults. Monitoring multiple physiological signals in patients’ homes provides a promising opportunity for clinicians to improve treatment outcomes and conveniently access relevant health metrics in older adults. Novel commercial and research grade devices are constantly evolving to meet growing demand from consumers and increase accuracy. To improve accuracy, more and more devices are integrating a wider array of physiological processes (e.g., heart rate, SpO2, ECG). However, scientific validation studies examining the accuracy and performance of these devices is minimal and completely absent in older adults with common chronic conditions and in individuals with Alzheimer’s disease and Alzheimer’s related dementias (AD/ADRD). Yet targeted studies in these groups are necessary given aging- and AD-related changes in gait, mobility, and physiological processes that may decrease the accuracy of devices. This study seeks to validate sleep detection capabilities of commercially available devices with physiological sensors in a diverse representative sample of older adults with common chronic conditions and a group with AD/ADRD. Device performance will be examined in in-home settings and compared to gold-standard sleep measures (polysomnography – a montage of EEG, EMG, and EOG). Further, with a series of questionnaires, we will identify high-utility device features, barriers to use, and other aspects relevant to improving future device development and compliance in both research and commercial settings. We consider this an essential first step towards deploying devices for health and research.