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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>WCCI 2024 Special Session: Machine Learning in Rehabilitation</b></span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>Venue: Yokohama, Japan</b></span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>Important Dates:</b></span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>15 January 2024:Paper Submission Deadline</b></span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>15 March 2024: Paper Acceptance Notification</b></span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>1 May 2024: Final Paper Submission & Early Registration Deadline</b></span></div>
<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"><b>30 June - 5 July 2024: IEEE WCCI 2024</b></span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">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.</span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">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.</span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">This special session in WCCI 2024 welcomes discussions and explorations of the multifaceted applications and future developments of
ML in rehabilitation and healthcare applications.</span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Please submit your contribution via https://edas.info/newPaper.php?c=31628&track=121739 and choose the special session “Machine Learning
in Rehabilitation”.</span></div>
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<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Main topics but not limited to:</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">ML-Driven Personalized & Optimizing Rehabilitation</span></div>
<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Adaptive Technology Integration</span></div>
<div class="elementToProof"><span style="letter-spacing: normal; font-family: Calibri, Helvetica, sans-serif; font-size: 16px; font-weight: 400; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);">Human-robot Interaction</span></div>
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<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Data-driven Clinical Decision-Making</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Predictive Analytics for Progress Monitoring</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Patient Monitoring and Feedback</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Monitoring Health Indicators</span></div>
<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Virtual Assistants and Companion Robots</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Human Factors and Ergonomics</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Gamification for Engagement</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Intelligent Tutoring Systems</span></div>
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<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Organizers: Junpei Zhong, The Hong Kong Polytechnic University, Hong Kong</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Chu Kiong Loo, Universiti Malaya, Malaysia</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Sao Mai Nguyen, ENSTA Paris, France</span></div>
<div><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Sum Yuet Joyce Lau, The Hong Kong Polytechnic University, Hong Kong</span></div>
<div class="elementToProof"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Corresponding Email: joni.zhong@polyu.edu.hk</span></div>
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