Movement in bed may be an indicator of health problems, i.e., the alteration of the pattern or amount of motor activity can be a disease marker. It can reflect illnesses ranging from flu to depression, pain, or the side effects of certain treatments. There are also motor disturbances that are triggered by sleep such as restless legs syndrome and periodic limb movements during sleep that reduce sleep quality. The assessment of nocturnal motor disturbances in sleep is traditionally performed through overnight polysomnography or actigraphy. In this work, we investigate the use of unobtrusive load cells sensors installed under the supports of a bed to assess movements in bed. Body and leg movements are discriminated using a linear classifier with center of pressure trajectory features derived from load cell signals. Leg movements are scored as periodic leg movements using the criteria defined by The World Association of Sleep Medicine, and a periodic leg movement index is estimated. The system is validated against technicians' annotations of body movements and leg movements (scorings from EMG data) collected from 17 patients during a one-night polysomnogram exam. The classification rate is equal to 96.9%, and the Spearman's correlation coefficient between the periodic leg movement indexes estimated by the system and those obtained from polysomnogram is 0.927. These results demonstrate the feasibility of using load cells for movement classification and detection of periodic leg movements.
ASJC Scopus subject areas
- Biomedical Engineering