A description of an accelerometer-based mobility monitoring technique.
Accurate monitoring of the mobility status of older adults, over the long-term, is important in rehabilitation medicine, as regular physical activity is central to maintaining both physical and mental health, as well as evaluating quality of life. This technical note describes an accelerometer-based mobility monitoring technique, which can distinguish between static and dynamic activities and can detect the basic postures of sitting, standing and lying. The technique allows thresholds for these postures to be set and two different posture threshold methods are described: mid-point and "best estimate". Preliminary results from using these methods are presented. This preliminary evaluation of the technique was carried out over the long-term (>29 h) in an uncontrolled environment and the method used to carry out the evaluation is described in detail. The two different posture thresholding methods were tested on long-term mobility data from one older adult subject. The subject did not have to follow a specific activity protocol during the recording period (4 days) and was shadowed by an observer in order to evaluate the accuracy of this technique. The monitoring hardware consisted of two accelerometer devices, one on the trunk and the other on the thigh and a pocket-sized ambulatory data-logger. Applying 'best estimate' thresholding, as opposed to mid-point thresholding, improved sitting detection accuracy by 18%, to 93% and lying detection accuracy by 5%, to 84%. Thus, based on these preliminary data, an accurate mobility monitoring system for older adults is described and it was observed that the actual posture threshold limits applied have a high impact on the mobility monitoring system's accuracy and are particularly important for accurately detecting postures when used over the long-term, in an uncontrolled environment.
Biomedical Electronics Laboratory, Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland.
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Lyons
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Culhane
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Hilton
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Grace
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Lyons
D000054:Acceleration; D000203:Activities of Daily Living; D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D009043:Motor Activity / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D010865:Pilot Projects; D011187:Posture / Q000502:physiology*; D014159:Transducers