Detection of movement in bed using unobtrusive load cell sensors.
Quality of sleep is an important attribute of an individual's health state and its assessment is therefore a useful diagnostic feature. Changes in the patterns of motor activities during sleep can be a disease marker, or can reflect various abnormal physiological and neurological conditions. Presently, there are no convenient, unobtrusive ways to assess quality of sleep outside of a clinic. This paper describes a system for unobtrusive detection of movement in bed that uses load cells installed at the corners of a bed. The system focuses on identifying when a movement occurs based on the forces sensed by the load cells. The movement detection approach estimates the energy in each load cell signal over short segments to capture the variations caused by movement. The accuracy of the detector is evaluated using data collected in the laboratory. The detector is capable of detecting voluntary movements in bed while the subjects were awake, with an average equal error rate of 3.22% (+/-0.54). Its performance is invariant with respect to the individual's characteristics, e.g., weight, as well as those of the bed. The simplicity of the resulting algorithms and their relative insensitivity to the weight and height of the monitored individual make the approach practical and easily deployable in residential and clinical settings.
Adami
Adriana M
AM
Oregon Health and Science University, Portland, OR 97239, USA. amiorell@ucs.br
Pavel
Misha
M
Hayes
Tamara L
TL
Singer
Clifford M
CM
D056044:Actigraphy / Q000295:instrumentation / Q000379:methods; D000465:Algorithms; D001513:Beds; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012890:Sleep / Q000502:physiology*; D014851:Wakefulness / Q000502:physiology*