alexa Continuous Assessment of Gait Velocity in Parkinson’s Disease from Unobtrusive Measurements


Journal of Biosensors & Bioelectronics

Author(s): Misha Pavel

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The ability to assess the neurological state of patients with neurodegenerative diseases on a continuous basis is an important component of future care for these chronically ill patients. In this paper we de scribe a set of algorithms to infer gait velocity and its var iability using data from an unobtrusive sensor network by incorporating a simple dynamic description of a patient’s movements within his or her residence. The sensors include a combination of passive motion detectors and active radio fre quency identification tags. The dynamic model is a simple 4 state hidden Markov model. We investigated the ability of this model to assess gait velocity and its variability using data from a six month pilot study of several patients with early stage Parkinson’s disease.

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This article was published in IEEE and referenced in Journal of Biosensors & Bioelectronics

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