  We introduce UbiPhysio, a milestone framework that delivers fine-grained
action description and feedback in natural language to support people's daily
functioning, fitness, and rehabilitation activities. This expert-like
capability assists users in properly executing actions and maintaining
engagement in remote fitness and rehabilitation programs. Specifically, the
proposed UbiPhysio framework comprises a fine-grained action descriptor and a
knowledge retrieval-enhanced feedback module. The action descriptor translates
action data, represented by a set of biomechanical movement features we
designed based on clinical priors, into textual descriptions of action types
and potential movement patterns. Building on physiotherapeutic domain
knowledge, the feedback module provides clear and engaging expert feedback. We
evaluated UbiPhysio's performance through extensive experiments with data from
104 diverse participants, collected in a home-like setting during 25 types of
everyday activities and exercises. We assessed the quality of the language
output under different tuning strategies using standard benchmarks. We
conducted a user study to gather insights from clinical physiotherapists and
potential users about our framework. Our initial tests show promise for
deploying UbiPhysio in real-life settings without specialized devices.
