Forearm sEMG data from young healthy humans during the execution of hand movements

This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases...

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Bibliographic Details
Main Authors: Ballesteros, M. (Author), Cruz-Ortiz, D. (Author), Gomez-Correa, M. (Author), Salgado, I. (Author)
Format: Article
Language:English
Published: NLM (Medline) 2023
Online Access:View Fulltext in Publisher
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LEADER 01932nam a2200181Ia 4500
001 10.1038-s41597-023-02223-x
008 230529s2023 CNT 000 0 und d
020 |a 20524463 (ISSN) 
245 1 0 |a Forearm sEMG data from young healthy humans during the execution of hand movements 
260 0 |b NLM (Medline)  |c 2023 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1038/s41597-023-02223-x 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159701344&doi=10.1038%2fs41597-023-02223-x&partnerID=40&md5=862e6a2b2e9d9a9f7014acf5b0b9e3ad 
520 3 |a This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases or cardiovascular problems. The test protocol consisted of sEMG signals acquisition corresponding to ten wrist and grasping movements (extension, flexion, ulnar deviation, radial deviation, hook grip, power grip, spherical grip, precision grip, lateral grip, and pinch grip), considering three repetitions for each gesture. Also, the dataset contains general information such as anthropometric measures of the upper limb, gender, age, laterally of the person, and physical condition. Likewise, the implemented acquisition system consists of a portable armband with four sEMG channels distributed equidistantly for each forearm. The database could be used for the recognition of hand gestures, evaluation of the evolution of patients in rehabilitation processes, control of upper limb orthoses or prostheses, and biomechanical analysis of the forearm. © 2023. The Author(s). 
700 1 0 |a Ballesteros, M.  |e author 
700 1 0 |a Cruz-Ortiz, D.  |e author 
700 1 0 |a Gomez-Correa, M.  |e author 
700 1 0 |a Salgado, I.  |e author 
773 |t Scientific data