Adaptive Robot Mediated Upper Limb Training Using Electromyogram Based Muscle Fatigue Indicators
Author
Thacham-Poyil, Azeemsha
Steuber, Volker
Amirabdollahian, Farshid
Attention
2299/21314
Abstract
Electromyogram Data from Upper Limb Muscles and Kinematic Data During Adaptive Robotic Interactions:
The data set consists of kinematic and EMG signals collected from 3 upper limb muscles (Biceps Brachii, Anterior Deltoid, and Middle Deltoid) of healthy participants during an adaptive robotic interaction involving rowing movements.
30 (17 males, 13 females) healthy participants of at least 18 years old with no history of injury to the upper limb and back were involved in this experiment.
Participants were students or staff members of University of Hertfordshire or other volunteers from outside the university.
The measurements were taken using an EMG acquisition device (g.USBamp amplifier) from g.tec medical engineering GmbH.
The data acquisition parameters (sampling rate, channel selection and so on) of the device were configured using Simulink.
Three EMG electrode channels were configured in bipolar mode with a sampling frequency of 1200Hz.
EMG electrodes for Biceps Brachii muscles were connected to Ports 11-12 of g.USBamp, Frontal Deltoid muscles to Ports 13-14 and Middle Deltoid muscles to Ports 15-16.
The tasks involved upper limb exercise, which simulated rowing, using a robot arm (HapticMaster robot) as directed by visual instructions on screen and audio cues.
This involved moving a robotic end-effector, while an animated boat rowing environment running in front of the participant on an LCD monitor.
There were be 3 groups of participants in this study.
Group A participants did not receive any adaptation from the robot during the interaction and were given break periods at regular intervals.
Group B interacted with the adaptive robotic environment, which was designed to adjust the difficulty level of the training exercise based on EMG based fatigue indicators.
Group C participants had a similar environment as Group B, but the environment only adapted based on the subject-reported fatigue.
The participants were asked to continue the exercise until they felt very tired or until they reported fatigue 3 times or until the maximum feasible robotic resistance was reached.
Publication date
2019Published version
https://doi.org/10.18745/ds.21314Funding
Default funderDefault project
Other links
http://hdl.handle.net/2299/21314Metadata
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