emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography
收藏DataCite Commons2026-02-23 更新2026-05-06 收录
下载链接：
https://nemar.org/dataexplorer/detail?dataset_id=nm000104
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资源简介：
emg2qwerty is the largest public surface electromyography (sEMG) dataset to date, comprising 1,135 sessions from 108 participants performing touch typing on a QWERTY keyboard. The dataset captures wrist-based sEMG signals (32 channels, 2000 Hz sampling rate) synchronized with keystroke ground truth, totaling 346.4 hours of data and 5.26 million keystrokes. Designed to enable keyboard-free text input through decoding of typing intent from neuromuscular activity, the dataset supports research in sequence-to-sequence learning, cross-user generalization, domain adaptation, and neuromotor interfaces for AR/VR and accessibility applications.
提供机构：
NEMAR (Neuroelectromagnetic Data Archive and Tools Resource)
创建时间：
2026-02-23
