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AI Toolkit for Parkinson's Disease Detection using Gait Data by Deep Learning

  • Unique Paper ID: 167258
  • Volume: 11
  • Issue: 3
  • PageNo: 1206-1213
  • Abstract:
  • People suffering from Parkinson's disease have a lot of variations in their locomotive patterns. A diseased person would have a different kind of walking pattern, that is their stance and stride cycles will be different in relation to healthy people. Machine learning models were trained on the Vertical Ground Reaction Force data present of the two kinds of sub- jects which are Parkinsonian and Control subjects. The VGRF values were measured using sensors on both the foot of the subjects. An AI toolkit was also developed for both users and researchers. Normal users can avail the feature of inputting their own VGRF data file and would get the corresponding prediction of whether or not they have parkinson disease from the four models namely Support Vector Machines, Convolutional Neural Networks, Long Short-Term Memory and decision Tree pretrained by us. Researchers can build their custom models and preprocessing using our GUI and train it on the dataset available.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 3
  • PageNo: 1206-1213

AI Toolkit for Parkinson's Disease Detection using Gait Data by Deep Learning

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