Hand by Hand: LLM Driving EMS Assistant for Operational Skill Learning
Wei Xiang, Ziyue Lei, Haoyuan Che, Fangyuan Ye, Xueting Wu, Lingyun Sun

TL;DR
This paper presents FlightAxis, a novel system combining LLMs and Electrical Muscle Stimulation to enhance kinesthetic skill learning in operational tasks, demonstrating high user acceptance and improved training efficiency.
Contribution
Introduces a new LLM-based kinesthetic training method using EMS, bridging the gap between textual feedback and physical skill acquisition.
Findings
High user acceptance of LLM-mediated body control
Significantly reduced task completion times
Enhanced trainee awareness and engagement
Abstract
Operational skill learning, inherently physical and reliant on hands-on practice and kinesthetic feedback, has yet to be effectively replicated in large language model (LLM)-supported training. Current LLM training assistants primarily generate customized textual feedback, neglecting the crucial kinesthetic modality. This gap derives from the textual and uncertain nature of LLMs, compounded by concerns on user acceptance of LLM driven body control. To bridge this gap and realize the potential of collaborative human-LLM action, this work explores human experience of LLM driven kinesthetic assistance. Specifically, we introduced an "Align-Analyze-Adjust" strategy and developed FlightAxis, a tool that integrates LLM with Electrical Muscle Stimulation (EMS) for flight skill acquisition, a representative operational skill domain. FlightAxis learns flight skills from manuals and guides…
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Taxonomy
TopicsOil and Gas Production Techniques · AI-based Problem Solving and Planning · Quality and Safety in Healthcare
