Shih-Ching Yeh1, Ming-Chun Huang2, Pa-Chun Wang3, Te-Yung Fang4, Mu-Chun Su1, Po-Yi Tsai5, Albert Rizzo6. 1. Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan. 2. Department of Computer Science, University of California at Los Angles, USA. 3. Department of Otolaryngology, Cathay General Hospital, Taipei, Taiwan; Fu Jen Catholic University School of Medicine, New Taipei City, Taiwan; Department of Public Health, China Medical University, Taichung, Taiwan; School of Medicine, Taipei Medical University, Taipei, Taiwan. Electronic address: drtony@seed.net.tw. 4. Department of Otolaryngology, Cathay General Hospital, Taipei, Taiwan; Fu Jen Catholic University School of Medicine, New Taipei City, Taiwan. 5. Department of Physical Medicine and Rehabilitation, Taipei Veterans General Hospital, Taipei, Taiwan. 6. Institute for Creative Technologies, University of Southern California, USA.
Abstract
BACKGROUND AND OBJECTIVE: Dizziness is a major consequence of imbalance and vestibular dysfunction. Compared to surgery and drug treatments, balance training is non-invasive and more desired. However, training exercises are usually tedious and the assessment tool is insufficient to diagnose patient's severity rapidly. METHODS: An interactive virtual reality (VR) game-based rehabilitation program that adopted Cawthorne-Cooksey exercises, and a sensor-based measuring system were introduced. To verify the therapeutic effect, a clinical experiment with 48 patients and 36 normal subjects was conducted. Quantified balance indices were measured and analyzed by statistical tools and a Support Vector Machine (SVM) classifier. RESULTS: In terms of balance indices, patients who completed the training process are progressed and the difference between normal subjects and patients is obvious. CONCLUSIONS: Further analysis by SVM classifier show that the accuracy of recognizing the differences between patients and normal subject is feasible, and these results can be used to evaluate patients' severity and make rapid assessment.
BACKGROUND AND OBJECTIVE:Dizziness is a major consequence of imbalance and vestibular dysfunction. Compared to surgery and drug treatments, balance training is non-invasive and more desired. However, training exercises are usually tedious and the assessment tool is insufficient to diagnose patient's severity rapidly. METHODS: An interactive virtual reality (VR) game-based rehabilitation program that adopted Cawthorne-Cooksey exercises, and a sensor-based measuring system were introduced. To verify the therapeutic effect, a clinical experiment with 48 patients and 36 normal subjects was conducted. Quantified balance indices were measured and analyzed by statistical tools and a Support Vector Machine (SVM) classifier. RESULTS: In terms of balance indices, patients who completed the training process are progressed and the difference between normal subjects and patients is obvious. CONCLUSIONS: Further analysis by SVM classifier show that the accuracy of recognizing the differences between patients and normal subject is feasible, and these results can be used to evaluate patients' severity and make rapid assessment.
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