Connectionists: [Meetings][CFP] WCCI 24 Special Session: Machine Learning in Rehabilitation

[Joni Zhong]

WCCI 2024 Special Session: Machine Learning in Rehabilitation

Venue: Yokohama, Japan

Important Dates:
15 January 2024:Paper Submission Deadline
15 March 2024: Paper Acceptance Notification
1 May 2024: Final Paper Submission & Early Registration Deadline
30 June - 5 July 2024: IEEE WCCI 2024

Rehabilitation, denoting the restoration of physical and cognitive functions following injury or illness, stands to derive substantial benefit from the integration of machine learning (ML) and big data. Given its longitudinal nature and the involvement of a multidisciplinary team, ML advancements present significant potential for applications in rehabilitation. Specifically, with the evolution of deep learning and sensing technologies, ML can proficiently analyze and interpret body movements, speech patterns, and cognitive activities, thereby providing comprehensive assessments in rehabilitation settings.

In the close interplay of physiological and psychological dimensions within rehabilitation, ML technologies also emerge as pivotal, such as robotic exoskeletons, interactive robots, and extended reality (xR) systems, capable of adapting in real-time based on a patient's progress, thereby providing a dynamic and responsive rehabilitation experience. Accurate measurement facilitated by ML not only informs healthcare specialists of physical progress but also instills motivation in patients to actively engage in their rehabilitation journey.

This special session in WCCI 2024 welcomes discussions and explorations of the multifaceted applications and future developments of ML in rehabilitation and healthcare applications.

Please submit your contribution via https://edas.info/newPaper.php?c=31628&track=121739 and choose the special session “Machine Learning in Rehabilitation”.

Main topics but not limited to:
ML-Driven Personalized & Optimizing Rehabilitation
Adaptive Technology Integration
Human-robot Interaction
Human-computer Interaction
Data-driven Clinical Decision-Making
Predictive Analytics for Progress Monitoring
Patient Monitoring and Feedback
Monitoring Health Indicators
Virtual Assistants and Companion Robots
Human Factors and Ergonomics
Gamification for Engagement
Intelligent Tutoring Systems
Serious Game

Organizers: Junpei Zhong, The Hong Kong Polytechnic University, Hong Kong
Chu Kiong Loo, Universiti Malaya, Malaysia
Sao Mai Nguyen, ENSTA Paris, France
Sum Yuet Joyce Lau, The Hong Kong Polytechnic University, Hong Kong
Corresponding Email: joni.zhong at polyu.edu.hk

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