HomeProjectsBiomedical Sciences and Healthcare TechnologiesWearable Health Monitoring and Dynamic Gait Analysis of Neurodegenerative Parkinson’s Disease

Wearable Health Monitoring and Dynamic Gait Analysis of Neurodegenerative Parkinson’s Disease

Project Quick Facts

Principal Investigator

  • Prof. LIAO Wei Hsin

    Department of Mechanical and Automation Engineering

  • Funding Sources

    Innovation and Technology Commission

    Noitom Technology Ltd.

  • Collaboration

    Xi’an Jiaotong University

To address the difficulties in early diagnosis and challenges of quantitative evaluation of neurodegenerative Parkinson’s disease, this project aims to reveal the degeneration mechanism of pathological gait by establishing a kinetic model of human walking lower limbs. An adaptive gait characterization technique for neurodegenerative Parkinson’s disease will be proposed, and the co-featured space of multi-source parameters can be obtained. The project will use myoelectric signals, kinematic and dynamic parameters to form a comprehensive quantitative evaluation index of Parkinson’s disease gait. The final purpose is to develop a wearable health monitoring and intelligent diagnostic system to provide Parkinson’s patients with convenient and accurate daily monitoring and early diagnosis services.

Locations of sensors underneath the feet

Uniqueness and Competitive Advantages:

  • Strong Interdisciplinary: Neuropathology, biomechanics, mechanical engineering and other multidisciplinary medical-industrial crossover research
  • Highly specialized: Need to build foot-ground friction and system dynamics, mapping rules, intelligent identification technology, patient and clinical expert data and fault diagnosis method guidance
  • Highly Targeted: It can realize the quantitative diagnosis and early warning of neurodegenerative Parkinson’s disease with wearable health monitoring system
  • Highly proactive: Development and utilization of a database of pathological gait and significant pathological features
  • Lightweight and reliable: The product is small in size and light in weight, with light wearability and wearing reliability, and light burden to the user.
Data processing, feature extraction and disease diagnosis process based on plantar pressure

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