Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/16688
Title: Recognition of Postures and Freezing of Gait in Parkinson’s Disease Patients Using Microsoft Kinect Sensor
Authors: Amini Maghsoud Bigy, A
Banitsas, K
Issue Date: 2015
Publisher: IEEE
Citation: 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)
Abstract: Freezing of Gait (FOG) is a disabling symptom and movement disorder, typically associated with the latter stages of Parkinson’s disease. In this paper, we propose a novel approach for real-time FOG, tremor monitoring and fall detection, consisting of a 3D camera sensor based on the Microsoft Kinect architecture. The system is capable of recognizing freezing episodes (FOG) in a standstill state, tremors and fall incidents, commonly seen in Parkinson’s disease patients. In case of an incident, it automatically alerts relatives and healthcare providers. The system was tested on seven simulated subjects in 12 events indicating that the design was able to detect 99% of the falling incidents, 91% of tremor and 92% of the freezing of gait episodes with an average latency of 300 milliseconds. The performance of the system can be further improved with the deployment of the recently released version of Kinect, capable of providing even higher levels of accuracy.
URI: http://bura.brunel.ac.uk/handle/2438/16688
DOI: http://dx.doi.org/10.1109/NER.2015.7146727
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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