A method for classification of movements in bed

Oregon Health and Science University, Portland, OR 97239, USA.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:7881-4. DOI: 10.1109/IEMBS.2011.6091943
Source: PubMed


Sleep is characterized by episodes of immobility interrupted by periods of voluntary and involuntary movement. Increased mobility in bed can be a sign of disrupted sleep that may reduce sleep quality. This paper describes a method for classification of the type of movement in bed using load cells installed at the corners of a bed. The approach is based on Gaussian Mixture Models using a time-domain feature representation. The movement classification system is evaluated on data collected in the laboratory, and it classified correctly 84.6% of movements. The unobtrusive aspect of this approach is particularly valuable for longer-term home monitoring against a standard clinical setting.

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    • "In [21], authors proposed a method of detection of movements made in bed. The authors of [21] resorted to the usage of load cells connected to the four corners of the bed and Gaussian Mixture Model in time domain to design the required classification system. The method was used on laboratory data and almost 84.6% results were found to be accurate. "
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