Forearm EMG Recordings for Pinch and Rock-Paper-Scissors Gestures

Two sets of surface electromyography recordings from 22 and 10 subjects performing pinch and rock-paper-scissors hand gestures, respectively. The data was recorded using a Myo armband at 200 Hz and includes annotations for each gesture. Elisa Donati of ETH Zurich authored the dataset, which is associated with a 2018 IEEE BioCAS conference publication.

Use Cases

• Classifying pinch gestures based on EMG signals from eight forearm sensors
• Recognizing rock-paper-scissors hand poses from time-series EMG data
• Training reservoir computing or neuromorphic systems for real-time gesture prediction
• Benchmarking signal processing algorithms for muscle activation pattern segmentation

Strengths

• Includes data from two distinct gesture sets (4 pinch types and 3 rock-paper-scissors movements)
• Recordings from 22 subjects for pinch gestures and 10 subjects for rock-paper-scissors gestures
• Structured recording sessions with 5 repetitions per gesture and 1-second rest intervals

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Last update date is unknown; freshness unverified

Provenance

Source

Elisa Donati, ETH Zurich

Collection Method

Recorded with a Myo armband featuring 8 sEMG sensors placed around the forearm.