Gesture Recognition and Biometrics ElectroMyogram (GRABMyo)

We present the Gesture Recognition and Biometrics ElectroMyogram (GRABMyo)
dataset, an open-access dataset of electromyogram (EMG) recordings collected
from the wrist and forearm muscles while performing hand gestures. Data were
collected from 43 healthy participants (age range: 24-35 years) on three
different days while performing 16 hand and finger gestures in identical
experimental sessions on each day. The GRABMyo dataset can be used for
research on: 1) EMG-based biometrics for personal identification and
verification, and 2) EMG-based gesture recognition for neurorehabilitation and
home applications. The large sample size will provide sufficient power for
establishing results, specifically for applications such as biometrics.
Further, it will be useful for subject-independent applications such as
generalized classification models for gesture recognition. The multiday
recordings will provide results that will be consistent over a longer
duration, crucial for the reliability of EMG-based wearable devices.