UTS RI Talk by Dr. Oluwarotimi Williams Samuel

Advances toward Realizing an Intelligent and Robust Control Scheme for Limb Rehabilitation Robots

Speaker: Dr. Oluwarotimi Williams Samuel, School of Computing and Engineering, University of Derby, UK

Abstract: Limb function loss severely impacts the quality of life of affected individuals, particularly precluding optimal use of their potential and rendering them functionally dependent in aspects such as self-care (eating, drinking, dressing, etc.). Intelligent rehabilitation robots that employ intuitive control scheme (s) driven by pattern recognition of bio-signals have been proposed to restore limb function and reintegrate affected individuals into society. However, state-of-the-art rehabilitation robots have only recorded marginal clinical and commercial success due to some confounding factors. Interestingly, my research team has investigated some limiting factors and proposed novel solutions adopting efficient machine learning/signal processing techniques to develop robustly adequate control schemes for such rehabilitation robots. Therefore, this talk will focus on sharing my recent research progress, emphasizing the breakthroughs recorded, challenges, and prospects.

Bio: Dr. Oluwarotimi Williams Samuel obtained a Ph.D. degree in Pattern Recognition and Intelligent Systems from the University of Chinese Academy of Sciences, Beijing, courtesy of the CAS-TWAS President's Fellowship with excellent dissertation honor and graduate awards. Before that, he received his bachelor's and master's degree in Computer Science with first-class honors and distinction, respectively. He is currently a Senior Lecturer and Lead Investigator with the School of Computing and Engineering at the University of Derby, United Kingdom. Before joining the University of Derby, Dr. Samuel was an Associate Professor with the Shenzhen Institute of Advanced Technology, Chinese Academy of Science (CAS) and the Shenzhen University of Technology, CAS. He conducts cutting-edge scientific research investigating core factors limiting Cyber-physical Systems' practical deployment (such as Assistive Technologies, Clinical Decision Support Systems, and Human-machine Interfaces, etc.) and develops novel AI-based Data-driven solutions to resolve such limitations. Besides, Dr. Samuel’s scholarly works have yielded several contributions, including 100+ articles in reputable peer-reviewed journals indexed by the Web of Science (WOS) and IEEE conference proceedings; “Top Cited/Influential Papers” courtesy of WOS, ESI-Index, and IOP Science; listed among “Top 2% Scientists Globally” courtesy of Stanford University, USA; and a nomination for the “2022 STEM for Britain Award” that spurred the presentation of our work in the House of Commons before the Members of Parliament. In addition, he has received 15+ academic awards and honors with 5+ successful international collaborations. Moreover, for Teaching and Mentorship, Dr. Samuel received the “Outstanding Teacher Award” and a cumulative rating score that by far exceeded the mean score in every case. Furthermore, his unwavering commitment to promoting scientific research, fostering collaboration, and leadership engineered his appointment as Associate Editor of Frontiers in Big Data, Advisory Board Member of the ELSP International Open Science Platform, Chair, Co-chair, and Technical Program Committee Member of various IEEE international conferences and academic meetings.

 

If you couldn't join us on the day, Dr Samuel's presentation is available to view -

 

 

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