Abstract
We present a method for measuring gait velocity using data from an existing ambient sensor network. 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 description of the sensor patterns. Experiments are carried out on 15 months of data and include repeated assessments from an occupational therapist. We showed that the measured gait velocities correlate with these assessments.
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- 1.
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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Acknowledgments
This work is part of the research programs SIA-raak Smart Systems for Smart Services, Health-lab and COMMIT. The authors would like to thank the participants at Vivium Zorggroep Naarderheem.
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Nait Aicha, A., Englebienne, G., Kröse, B. (2015). Continuous Gait Velocity Analysis Using Ambient Sensors in a Smart Home. In: De Ruyter, B., Kameas, A., Chatzimisios, P., Mavrommati, I. (eds) Ambient Intelligence. AmI 2015. Lecture Notes in Computer Science(), vol 9425. Springer, Cham. https://doi.org/10.1007/978-3-319-26005-1_15
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