Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics

Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics

Citation Author(s):
Sanjay Kumar
Dwivedi
Jimson
Ngeo
Tomohiro
Shibata
Submitted by:
SANJAY DWIVEDI
Last updated:
Mon, 01/13/2020 - 02:08
DOI:
10.21227/zbkg-gy95
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Accurate proportional myo-electric control of the hand is important in replicating dexterous manipulation in robot prostheses. Many studies in this field have focused on recording discrete hand gestures, while few have focused on the proportional and multiple-DOF control of the human hand using EMG signals. To aid researchers on advanced myoelectric hand control and estimation, we present this data from our work "Extraction of nonlinear muscle synergies for proportional and simultaneous estimation of finger kinematics".  

In our study, surface lectromyographic (sEMG) signals from the forearm and finger joint marker data were recorded from  able-bodied subjects while they were tasked to do individual, simultaneous and random multiple finger flexion and extension movements.  Included in this dataset are the EMG signals from 8 extrinsic muscles along the forearm, and as much as 23 joint  markers attached on the hand obtained from 10 subjects. 

 

More description about the experimental protocol, signal processing methods and equipments  used are described in the paper below. 

- S.K.Dwivedi, J. Ngeo, T.Shibata, Transaction of Biomedical Engineering, In Press, 

"Extraction of Nonlinear Synergies for Proportional and Simultaneous Estimation of Finger Kinematics."

 

 

 

Instructions: 

Data: 10 subjects <downsampled_filtered_emg(dsfilt_emg),  23-joint marker position data(finger_kinematics)>

Data File Extension: .mat 

Cell Variables:

   * dsfilt_emg,              <5x7 cell>    <40000x8>

   * finger_kinematics   <5x7 cell>    <4000x69>  

Cell format:

row - correspond to the number of trials (total 5 trials)

column - correspond to the number of tasks (total 7 tasks)

 7 sets of movement tasks:

(1-5) individual flexion and extension of each finger: thumb, index, middle, ring, little, in this order

(6)   simulteneous flexion and extension of all fingers 

(7)   random free finger movement, in no particular order, and only in the flexion and extension plane

 

Comments:

a.  dsfilt_emg data and muscle activation data consist of 8 column vectors represents the 8 forearm muscles in the following order 

<APL,FCR,FDS,FDP,ED,EI,ECU,ECR>

 b. The finger_kinematics data consists of 69 column vectors. Each column vector is either the <x,y,z> joint positions

   of each marker. There are a total of 23 markers used.The marker assignment has been shown in <Marker_Position.png>.

   Kinematics data can be visualized through the script provided with the dataset - "Visulize_Kinematics_data.m"

Please refer to our paper for the additional detail regarding the data. Please cite [1] if you wish to use this dataset.

[1] - S.K.Dwivedi, J. Ngeo, T.Shibata, Transaction of Biomedical Engineering, In Press, 

"Extraction of Nonlinear Synergies for Proportional and Simultaneous Estimation of Finger Kinematics."

 

Affiliation / Email  --- Graduate School of Life Sciences and System Engineering, 

                                  Kyushu Institute of Technology, Kitakyushu, Japan

                                  (correspondence: tom@brain.kyutech.ac.jp

 

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[1] Sanjay Kumar Dwivedi, Jimson Ngeo, Tomohiro Shibata, "Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/zbkg-gy95. Accessed: Jan. 21, 2020.
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doi = {10.21227/zbkg-gy95},
url = {http://dx.doi.org/10.21227/zbkg-gy95},
author = {Sanjay Kumar Dwivedi; Jimson Ngeo; Tomohiro Shibata },
publisher = {IEEE Dataport},
title = {Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics},
year = {2020} }
TY - DATA
T1 - Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics
AU - Sanjay Kumar Dwivedi; Jimson Ngeo; Tomohiro Shibata
PY - 2020
PB - IEEE Dataport
UR - 10.21227/zbkg-gy95
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Sanjay Kumar Dwivedi, Jimson Ngeo, Tomohiro Shibata. (2020). Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics. IEEE Dataport. http://dx.doi.org/10.21227/zbkg-gy95
Sanjay Kumar Dwivedi, Jimson Ngeo, Tomohiro Shibata, 2020. Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics. Available at: http://dx.doi.org/10.21227/zbkg-gy95.
Sanjay Kumar Dwivedi, Jimson Ngeo, Tomohiro Shibata. (2020). "Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics." Web.
1. Sanjay Kumar Dwivedi, Jimson Ngeo, Tomohiro Shibata. Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/zbkg-gy95
Sanjay Kumar Dwivedi, Jimson Ngeo, Tomohiro Shibata. "Dataset of Surface Electromyographic (sEMG) Signals and Finger Kinematics." doi: 10.21227/zbkg-gy95