Nursing homes have night-shift staff who are frequently not fully occupied and could be trained to perform sleep observations. For these reasons, systematic sleep observations are presented as important tools in the assessment of sleep in the nursing home. limited because of irregularities of electroencephalogram (EEG) patterns in this population. Additionally, the utility of the sleep laboratory in assessing sleep in the very demented patient is. Such technology is generally unavailable either for research studies or clinical interventions with elderly people residing in the community. Most of the studies on sleep patterns in elderly people have been performed on small samples in sleep laboratories and with the use of advanced technology. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used. We demonstrated the accuracy of our algorithm to detect the SPT-window. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. sleep diary in 3752 participants (range = 60–82 years) and polysomnography in sleep clinic patients (N = 28) and in healthy good sleepers (N = 22). Detected sleep period time window (SPT-window) was compared against. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries.
View full-textĪbstract Wrist worn raw-data accelerometers are used increasingly in large-scale population research. Quality sleep is inversely associated with the age related rise in overnight metabolic rate, suggesting that increased overnight metabolic rate is a biological sign of ageing as a consequence of diminished quality sleep. When OMR/ BMR was adjusted for quality sleep, the effect of age was non significant. Body movement was negatively related to sleep efficiency (r=-0.38, p<0.01) with no effect on OMR/BMR. The variance of OMR/BMR was significantly explained by quality sleep (r=-0.58, p<0.001). OMR/BMR was positively associated with age (r=0.48, p<0.001), and quality sleep was negatively associated with age (r=-0.51, p<0.001). Overnight metabolic rate was adjusted for body size by dividing by basal metabolic rate (OMR/BMR). Body movement was measured between 23:00 and 07:00 with an accelerometer on the wrist. Quality sleep was calculated as time spent in REM sleep and slow wave sleep divided by total sleep time, and sleep efficiency was calculated as total sleep time divided by the sleep period time. Subsequently basal metabolic rate (BMR) was measured under a ventilated hood. Data was collected between 23:00 and 07:00. chamber to measure sleep stages by polysomnography, and overnight metabolic rate (OMR). The objective of the study was to determine the relationship between quality sleep, sleep efficiency and overnight metabolic rate as measured in a respiration chamber in elderly subjects.įorty subjects, aged 50 to 83 years (17 males, age 63☗ y, BMI 25.7☒.3 kg/m 2) spent one night in a respiration. Increasing age is associated with an increase in overnight metabolic rate.