LEAVE-ONE-OUT ELECTROMYOGRAPHY (EMG) DATA SET OF 4 GESTURES PERFORMED WITH THE RIGHT HAND
- Citation Author(s):
-
Bolivar Nuñez
(FIMCP, Escuela Superior Politécnica del Litoral, ESPOL)
Edwin Valarezo
(FIEC, Escuela Superior Politécnica del Litoral, ESPOL)
- Submitted by:
- Bolivar Nunez
- Last updated:
- DOI:
- 10.21227/ndjb-x470
- Data Format:
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Abstract
A new design and implementation of a control system for an anthropomorphic robotic hand has been developed for the Bioinformatics and Autonomous Learning Laboratory (BALL) at ESPOL. Myoelectric signals were acquired using a bioelectric data acquisition board (CYTON BOARD) with six out of the available eight channels. These signals had an amplitude of 200 [uV] and were sampled at a frequency of 250 [Hz].
The data presented here extends the experiment conducted in the (ELECTROMYOGRAPHY (EMG) DATA SET OF 4 GESTURES PERFORMED WITH THE RIGHT HAND, ###), which was utilized for training, validation, and testing of the Multi-channel Biosignal Transformer (MuCBiT). For this purpose, five healthy subjects were recruited, including four females, with an average age of 28 years. All subjects were right-handed (with an Edinburgh Handedness Inventory (EHI) dexterity test score of 77.56), as measured by the Edinburgh Handedness Inventory (EHI) dexterity test (Oldfield RC, 1971).
Instructions:
The following methodology has been considered to proceed with the transformer model MuCBiT:
- Load the data in *.csv files, considering that each file is an independent subject.
- The data are separated by class, then centralized through the mean and normalized with the MIN-MAX scaler.
- Any digital filtering is applied.
- The present data set was used for testing the model which got an accuracy of 85%.
