HMotionGPT: Aligning Hand Motions and Natural Language for Activity Understanding with Smart Rings

Jan 1, 2026ยท
Yang Gao
,
Dong She
,
Wolin Liang
,
Chiyue Wang
,
Yingjing Xiao
,
Xianrong Yao
,
Cong Liu
,
ZhiChao Huang
,
Zhanpeng Jin
ยท 0 min read
Abstract
HMotionGPT studies how smart-ring motion signals can be aligned with natural language to support activity understanding. The work explores a language-grounded representation of hand motion, enabling wearable systems to reason about fine-grained activities through both sensor data and semantic descriptions. By connecting motion patterns from rings with textual knowledge, HMotionGPT points toward more interpretable and flexible wearable intelligence for everyday activity sensing.
Type
Publication
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (PACM IMWUT / UbiComp)