Surface Electromyography (EMG) and Inertial Measurement Unit (IMU) sensors are gaining the attention of the research community as data sources for automatic sign language recognition. In this regard, we provide a dataset of EMG and IMU data collected using the Myo Gesture Control Armband, during the execution of the 26 gestures of the Italian Sign Language alphabet. For each gesture, 30 data acquisitions were executed, composing a total of 780 samples included in the dataset. The gestures were performed by the same subject (male, 24 years old) in lab settings. EMG and IMU data were collected in a 2 seconds time window, at a sampling frequency of 200 Hz.

A surface electromyography and inertial measurement unit dataset for the Italian Sign Language alphabet / Pacifici, I.; Sernani, P.; Falcionelli, N.; Tomassini, S.; Dragoni, A. F.. - In: DATA IN BRIEF. - ISSN 2352-3409. - ELETTRONICO. - 33:(2020), pp. 1064551-1064555. [10.1016/j.dib.2020.106455]

A surface electromyography and inertial measurement unit dataset for the Italian Sign Language alphabet

Tomassini, S.;Dragoni, A. F.
2020-01-01

Abstract

Surface Electromyography (EMG) and Inertial Measurement Unit (IMU) sensors are gaining the attention of the research community as data sources for automatic sign language recognition. In this regard, we provide a dataset of EMG and IMU data collected using the Myo Gesture Control Armband, during the execution of the 26 gestures of the Italian Sign Language alphabet. For each gesture, 30 data acquisitions were executed, composing a total of 780 samples included in the dataset. The gestures were performed by the same subject (male, 24 years old) in lab settings. EMG and IMU data were collected in a 2 seconds time window, at a sampling frequency of 200 Hz.
2020
Pacifici, I.; Sernani, P.; Falcionelli, N.; Tomassini, S.; Dragoni, A. F.
A surface electromyography and inertial measurement unit dataset for the Italian Sign Language alphabet / Pacifici, I.; Sernani, P.; Falcionelli, N.; Tomassini, S.; Dragoni, A. F.. - In: DATA IN BRIEF. - ISSN 2352-3409. - ELETTRONICO. - 33:(2020), pp. 1064551-1064555. [10.1016/j.dib.2020.106455]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/403288
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