GRABMyoFlow - Dataset extension

This dataset is an extension of the Gesture Recognition and Biometrics
Electromyogram (GRABMyo) dataset, a comprehensive collection of surface
electromyography (sEMG) signals from the forearm and wrist while performing
static gestures, designed for hand gesture recognition (HGR) and biometric
authentication research. The study extends the dataset in two key aspects: 1)
by adding wrist-only recordings from 20 newly recruited healthy adults, and 2)
by including a dynamic trial at the end of each session. The extension study
follows the protocol established in the original study to ensure
methodological consistency and reliable data acquisition. Combined with prior
wrist recordings, the extended dataset now includes data from 63 participants,
significantly increasing the sample size. Signal strength and quality in the
new recordings have been validated to match the standards of the original
dataset, ensuring uniformity across all subjects. The dynamic gesture
recordings included in the extension capture the natural transitions between
hand poses, better simulating real-world movement scenarios. These dynamic
data enable new avenues for continuous authentication and gesture-event
segmentation, directly addressing prior limitations of static-only datasets.
Data acquisition employed the established electrode configuration, and open
access to the data in the waveform database (WFDB)-format is provided to
support the widespread use of research. This enriched dataset enhances both
the scale and temporal complexity of the GRABMyo dataset, delivering a robust
resource for advancing sEMG-based HGR for human-computer interaction or
biometric systems research.