A Multimodal EMG Dataset for Exercise Quality Assessment in ICE Environments
收藏Mendeley Data2026-04-09 收录
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资源简介：
We present a multimodal exercise dataset collected to support autonomous feedback systems for training in isolated, confined, and extreme (ICE) environments. Twenty healthy adults performed a structured set of whole-body exercises in limited space. The dataset includes surface EMG from four muscles, IMU kinematics (quaternions), wrist heart rate, and expert annotations of movement quality against predefined biomechanical criteria. Raw signals were filtered, segmented, synchronized, and EMG envelopes were derived. This resource enables development and validation of machine-learning models for automated assessment of exercise quality when professional supervision is not available.
提供机构：
Ceske Vysoke Uceni Technicke v Praze Fakulta biomedicinskeho inzenyrstvi; Industrial Technology Research Institute; National Taiwan University of Science and Technology
