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Updated: Jul 15, 2026

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
Published on: April 12, 2016
Dataset for self-practice of the peg transfer: Tool and wrist motion, eye gaze, and video measurements for multimodal
Jinwoo Oh1, Shiyu Deng1, Nathan Lau1
1Grado Department of Industrial and Systems Engineering, Virginia Tech, 24060, VA, USA.
Abstract:
This article describes a multimodal dataset on self-directed practice of the peg transfer task in the Fundamentals of Laparoscopic Surgery (FLS) curriculum. Nineteen university students self-practiced the FLS peg transfer task in multiple one-hour sessions consisting of alternating 10-minute practice blocks and 2-minute rest breaks. Data collection continued until participants met the proficiency criterion-ten non-consecutive trials completed within 48 s without dropping objects-or reached a maximum of six sessions. Across all participants, the dataset contains 85 sessions and 1971 trials. Each trial includes measurements from bilateral wrist inertial measurement units (IMUs), tool-handle IMUs, eye tracking, and trainer-box video that were concurrently recorded using a custom C# data logging software application. Trial-level annotations and performance metrics include task completion time, number of objects dropped, and experimenter comments. The dataset is publicly accessible from an institutional repository.