A technology for prediction and prevention of freezing of gait (FOG) in individuals with parkinson disease

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Abstract

External cueing in the form of visual, auditory or vibratory cue is useful to avoid freezing of gait (FOG) problem commonly experienced by individuals with Parkinson Disease (PD). The currently available technology-assisted solutions are of limited help because of two main issues: (i) the use of accelerometer or gyro-based wearable sensors for prediction of FOG are noise prone and (ii) deliver external cues without any individualization. In our present research, we have designed a low-cost system that can be attached as an add-on module on ordinary walking stick that can (i) predict freezing of gait (ii) deliver visual, auditory and/or vibratory cues in an individualized manner. We conducted a preliminary study with one PD participant. The preliminary results show potential of our system to reduce freezing counts, increase average step length and walk speed of the participant.

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Patel, M., Krishna, G. S. R., Das, A., & Lahiri, U. (2017). A technology for prediction and prevention of freezing of gait (FOG) in individuals with parkinson disease. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10515 LNCS, pp. 395–403). Springer Verlag. https://doi.org/10.1007/978-3-319-67687-6_26

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