Objectives: Our count-scaled algorithm automatically scores sleep across 24 hours to
process sleep timing, quantity, and quality. The aim of this study was to validate the …

Recent work in unobtrusive sleep/wake classification has shown that cardiac and respiratory
features can help improve classification performance. Nevertheless, actigraphy remains the …

Purpose Wrist-worn actigraphy via research-grade devices, a well-established approach to
the assessment of rest-activity, is limited by poor compliance, battery life, and lack of direct …

Introduction Sleep is a fundamental and essential physiological process for recovering
physiological function. Sleep disturbance or deprivation has been known to be a causative …

Objective estimation of sleep can utilize a range of technologies. For field-based recordings,
the most accepted approach is “actigraphy,” or movement-based estimation of sleep versus …

Background Differentiating nonwear time from sleep and wake times is essential for the
estimation of sleep duration based on actigraphy data. To efficiently analyze large-scale …

Study Objectives: Our objective was to examine the ability of a consumer-grade wearable
device (Basis B1) with accelerometer and heart rate technology to assess sleep patterns …

Two validation studies were conducted to optimize the sleep-detection algorithm of the
Actillume. The first study used home recordings of postmenopausal women (age range: 51 …

Clinical actigraphy devices provide adequate estimates of some sleep measures across
large groups. In practice, providers are asked to apply clinical or consumer wearable data to …

Movement-based sleep-wake detection devices (ie, actigraphy devices) were first
developed in the early 1970s and have repeatedly been validated against …