Abstract
We present a method for measuring gait velocity of older adults using data from existing ambient sensor networks. Gait velocity is an important predictor of fall risk and functional health. In contrast to other approaches that use specific sensors or sensor configurations, our method imposes no constraints on the elderly. We studied different probabilistic models for the modeling of the duration and the distance of the indoor walking paths. Experiments are carried out on 27 months of sensor data and include repeated assessments from an occupational therapist. We showed that gait velocities can be measured with low variance and correlate with most assessments. The advantage of our monitoring system is that because of the continuous measurements, clearer trends can be extracted than from incidental assessments of the occupational therapist.
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Notes
The actual value of the event is not relevant to our purposes: we are interested in the knowledge that the resident is present at a certain location, not in their activity.
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Acknowledgements
This work is part of the research programs SIA-raak Hipper and COMMIT/. The authors would like to thank the participants at Vivium Zorggroep Naarderheem.
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Aicha, A.N., Englebienne, G. & Kröse, B. Continuous measuring of the indoor walking speed of older adults living alone. J Ambient Intell Human Comput 9, 589–599 (2018). https://doi.org/10.1007/s12652-017-0456-x
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DOI: https://doi.org/10.1007/s12652-017-0456-x