Research Projects
AI based human motion analysis for assistant robots assessment

Programme(s) to which this project applies:

☑ MPhil/PhD ☒ MRes[Med] ☒ URIS

Hong Kong is facing a significant societal challenge – a rapidly aging society. In terms of quality of life, a major difficulty that many older people experience is severe limitation in mobility and manipulability in their daily life, resulting in tremendous social and economic challenges. Hence, it is necessary to develop innovative intelligent robotics systems to improve mobility and manipulability, prevent falls, enhance independence, and improve the quality of life of older adults. During the research and development of intelligent robotics system, we need to perform human motion analysis to identify the individual needs of older adults for achieving mobility, which then leads to determining kinesiology-based design parameters for personalized wearable robots. Physical tests, physiological measurement and behavior assessment in phases 1 and 2 will generate a lot of data. Then, a combination of convolutional neural network (CNN) and recurrent neural network (RNN) in a parallel structure will be employed to estimate compensation metrics of robotic assistance. The efficacy and performance of this approach will be validated in 60 subject of phase 3. It is expected to establish a transfer learning model to assistant individual robotic design at the end of this project.

Professor Y Hu, Department of Orthopaedics and Traumatology

Yong Hu, PhD
Tenured Associate professor, Director of Lab of Neural Engineering and Clinical Electrophysiology, Department of Orthopaedics & Traumatology, The University of Hong Kong

HKU Scholars Hub

For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description.  Interested candidates are advised to enclose with your email:

  1. your CV,
  2. a brief description of your research interest and experience, and
  3. two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).

Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to

HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.  

HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.