Developing an assistive interface for individuals with spasticity disorders cd.

Czwartek, 19 marca

6. EXPERIMENTAL RESULTS ON TRAINING AND CLASSIFICATION

Various tests were done on both aspects of the Bayesian classifier. Training was done utilizing eq. 2 with sufficient test cases (over 30). Next, classification is done utilizing the rules that were presented above. Once MitSpacPoC was activated, the 400th pixel was chosen to be the trigger point for the classification process. Fig. 4 shows the path that was taken by a user, and the decision button B1 that was chosen.

Fig. 6. Spastic data, shown in white, followed by the decision button (B) once the 400th pixel is reached.

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1. INTRODUCTION
2. CEREBRAL PALSY
3. PREVALENT HEAD-AIM DEVICES
4. DATA ACQUISITION
5. MITIGATING SPASTICITY
6. EXPERIMENTAL RESULTS ON TRAINING AND CLASSIFICATION
7. DISCUSSION

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