On-Device Machine Learning for Diagnosis of Parkinson's Disease from Hand Drawn Artifacts

Sai Vaibhav Polisetti Venkata, Shubhankar Sabat, Chinmay Anand Deshpande, Asiful Arefeen, Daniel Peterson, Hassan Ghasemzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Effective diagnosis of neuro-degenerative diseases is critical to providing early treatments, which in turn can lead to substantial savings in medical costs. Machine learning models can help with the diagnosis of such diseases like Parkinson's and aid in assessing disease symptoms. This work introduces a novel system that integrates pervasive computing, mobile sensing, and machine learning to classify hand-drawn images and provide diagnostic insights for the screening of Parkinson's disease patients. We designed a computational framework that combines data augmentation techniques with optimized convolutional neural network design for on-device and real-time image classification. We assess the performance of the proposed system using two datasets of images of Archimedean spirals drawn by hand and demonstrate that our approach achieves 76% and 83% accuracy respectively. Thanks to 4x memory reduction via integer quantization, our system can run fast on an Android smartphone. Our study demonstrates that pervasive computing may offer an inexpensive and effective tool for early diagnosis of Parkinson's disease1.

Original languageEnglish (US)
Title of host publicationBHI-BSN 2022 - IEEE-EMBS International Conference on Biomedical and Health Informatics and IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665487917
DOIs
StatePublished - 2022
Event2022 IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, BSN 2022 - Ioannina, Greece
Duration: Sep 27 2022Sep 30 2022

Publication series

NameBHI-BSN 2022 - IEEE-EMBS International Conference on Biomedical and Health Informatics and IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks - Proceedings

Conference

Conference2022 IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, BSN 2022
Country/TerritoryGreece
CityIoannina
Period9/27/229/30/22

Keywords

  • convolutional neural networks
  • Machine learning
  • mobile sensing
  • Parkinson's disease
  • pervasive computing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Biomedical Engineering
  • Instrumentation

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