Work Description

Title: Electromyography from bipolar electrodes implanted into Regenerative Peripheral Nerve Interfaces and residual muscles in persons with amputations Open Access Deposited

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Attribute Value
Methodology
  • This data was collected under University of Michigan IRB HUM00124839, ClinicalTrials.gov Identifier: NCT03260400. Two persons with transradial amputations (P1 and P2) had eight pairs of bipolar recording electrodes implanted into regenerative peripheral nerve interfaces (RPNIs) and residual muscles. We recorded electromyography (EMG) calibration data for pattern recognition algorithms. During this process, each participant followed a cue hand and mimicked individual finger or grasp postures with their phantom hand. The posture of the cue hand is time synced with the raw EMG recordings in the attached data files. The implanted electrodes were manufactured by Synapse Biomedical and the neural signal processor that recorded electromyography was a Cerebus system from Blackrock Microsystems. P2 also has one dataset where surface EMG was recorded with gelled Biopac electrodes simultaneously with the implanted electrodes.
Description
  • The data was used to calibrate and simulate pattern recognition algorithms for the following publication: Surgically Implanted Electrodes Enable Real-Time Finger and Grasp Pattern Recognition for Prosthetic Hands (medRxiv 2020, IEEE TRO in review). Each data file is named as follows Px_PostureSet.csv. Where Px is the patient number. The 1 of 10 posture set contains individual finger and intrinsic thumb movements, the grasps posture set contains a fewer number of combined finger movements. P1’s calibration data for individual fingers is labelled 1 of 12 because it also includes two grasps, which were removed for analysis in the publication. The first column of each .csv file is the experiment time in seconds. The second column is the posture of the cue hand at that timestamp. The rest of the columns are the raw EMG data in microvolts sampled at 30KSps. A legend of the movement postures, each patients EMG channels, and suggested signal processing and filtering is included in DataLabellingAndProcessing.pdf
Creator
Depositor
  • akvaskov@umich.edu
Contact information
Discipline
Funding agency
  • National Institutes of Health (NIH)
Keyword
Citations to related material
  • Surgically Implanted Electrodes Enable Real-Time Finger and Grasp Pattern Recognition for Prosthetic Hands A. K. Vaskov, P. P. Vu, N. North, A. J. Davis, T. A. Kung, D. H. Gates, P. S. Cederna, C. A. Chestek medRxiv 2020.10.28.20217273; doi: https://doi.org/10.1101/2020.10.28.20217273
Resource type
Last modified
  • 11/17/2022
Published
  • 05/12/2022
Language
DOI
  • https://doi.org/10.7302/fjhy-5q29
License
To Cite this Work:
Vaskov, A. K., Vu, P. P., North, N., Davis, A. J., Kung, T. A., Gates, D. H., Cederna, P. S., Chestek, C. A. (2022). Electromyography from bipolar electrodes implanted into Regenerative Peripheral Nerve Interfaces and residual muscles in persons with amputations [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/fjhy-5q29

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