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Vojta-Therapy: A Vision-Based Framework to Recognize the Movement Patterns
Abstract
This paper proposed a novel computer vision-based framework to recognize the accurate movements of a patient during the Vojta-therapy. Vojta-therapy is a useful technique for the physical and mental impairments in humans. During the therapy, a specific stimulation is given to the patients to cause the patient's body to perform certain reflexive pattern movements. The repetition of this stimulation ultimately makes available the previously blocked connections between the spinal cord and brain, and after a few sessions, patients can perform these movements without any external stimulation. In this paper the authors propose an automatic method for patient detection and recognition of specific movements in his/her various body parts during the therapy process, using Microsoft Kinect camera. The proposed method works in three steps. In the first step, a robust template matching based algorithm is exploited for patient's detection using his/her head location. Second, several features are computed to capture the movements of different body parts during the therapy process. Third, in the classification stage, a multi-class support vector machine (mSVM) is used to classify the accurate movements of patient. The classification results ultimately reveal the correctness of the given treatment. The proposed algorithm is evaluated on the authors' challenging dataset, which was collected in a children hospital. The detection and classification results show that the proposed method is highly useful to recognize the correct movement pattern either in hospital or in-home therapy systems.
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