On October 15, a collaborative study conducted by Tsinghua University's Pervasive Human-Computer Interaction Laboratory, Sichuan University's West China Hospital Rehabilitation Medicine Center, and Sichuan University's Institute of Rehabilitation Medicine, titled "UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language," received the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) Distinguished Paper Award at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2025).
From the 208 papers published in Volume 8 of IMWUT over the past year, only eight papers were selected for this prestigious recognition, representing an acceptance rate of just 3.85%. The IMWUT Distinguished Paper Award is presented annually at the UbiComp conference to recognize exceptional contributions to the field of ubiquitous and pervasive computing.
According to the award committee, “UbiPhysio represents a versatile framework for at-home rehabilitation, combining biomechanical movement modeling with instruction-tuned LLMs. Co-designed with physiotherapists and validated on 100+ users, it delivers expert feedback, generalizes across IMU and vision-based data, and lays the groundwork for scalable, accessible remote care.”
The paper’s first author, Dr. Chongyang Wang, conducted the research as a postdoctoral researcher at the Pervasive Human-Computer Interaction Laboratory of Tsinghua University's Department of Computer Science and Technology and currently serves as Research Assistant Professor at the Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, where he leads the Rehab AI Lab. Corresponding authors include Associate Professor Chun Yu from Tsinghua University’s Pervasive HCI Lab, Professor Chengqi He, and Associate Professor Siyi Zhu from Sichuan University’s West China Hospital Rehabilitation Medicine Center. Additional co-authors include Yuan Feng, a master’s graduate from Sichuan University’s West China Hospital; Lingxiao Zhong, an undergraduate alumnus of Tsinghua University; Chi Zhang, an undergraduate from Tsinghua’s Department of Computer Science and Technology; Siqi Zheng, a graduate student at Tsinghua’s Global Innovation Exchange (GIX); Assistant Professor Chen Liang from the Hong Kong University of Science and Technology (Guangzhou); Associate Researcher Yuntao Wang; and Professor Yuanchun Shi from Tsinghua’s Pervasive Human-Computer Interaction Laboratory.
Editor: Li Han
