Gesture Recognition and Biometrics ElectroMyogram (GRABMyo)

health life sciences medicine

Description

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.

Update Frequency

Not updated

License

Creative Commons Attribution 4.0 International Public License

Documentation

https://doi.org/10.13026/89dm-f662

Managed By

PhysioNet

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Contact

https://physionet.org/about/#contact_us

How to Cite

Gesture Recognition and Biometrics ElectroMyogram (GRABMyo) was accessed on DATE from https://registry.opendata.aws/grabmyo.

Resources on AWS

  • Description
    https://doi.org/10.13026/89dm-f662
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::physionet-open/grabmyo/
    AWS Region
    us-east-1
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://physionet-open/grabmyo/

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