Object and event recognition for stroke rehabilitation

Ahmed Ghali; Andrew S. Cunningham; Tony P. Pridmore

doi:10.1117/12.503470

23 June 2003 Object and event recognition for stroke rehabilitation

Ahmed Ghali, Andrew S. Cunningham, Tony P. Pridmore

Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/10.1117/12.503470
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland

Abstract

Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient’s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient’s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.

Citation Download Citation

Ahmed Ghali, Andrew S. Cunningham, and Tony P. Pridmore "Object and event recognition for stroke rehabilitation", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); https://doi.org/10.1117/12.503470

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