Research and development of IMU sensors-based approach for sign language gesture recognition

This paper discusses a few Inertial Measurement Unit (IMU) sensor-based approaches for sign language gesture recognition. Generally, there are three main research areas for the IMU sensor-based approach which consist of the device structure, sensors fusion algorithm and calibration method, and final...

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Main Authors: Abdullah, A., Abdul-Kadir, N. A., Che Harun, F. K.
Format: Article
Published: Universiti Teknikal Malaysia Melaka 2017
Subjects:
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author Abdullah, A.
Abdul-Kadir, N. A.
Che Harun, F. K.
author_facet Abdullah, A.
Abdul-Kadir, N. A.
Che Harun, F. K.
author_sort Abdullah, A.
collection ePrints
description This paper discusses a few Inertial Measurement Unit (IMU) sensor-based approaches for sign language gesture recognition. Generally, there are three main research areas for the IMU sensor-based approach which consist of the device structure, sensors fusion algorithm and calibration method, and finally gesture recognition and classification method. The device structure includes the number and placement of the sensors to cover the degrees of freedom. Sensors fusion algorithms, such as complementary filter, Kalman filter, and EKF are implemented to combine a variety of sensors used for data acquisition. Several gesture classification and recognition methods are also reviewed in this paper. Some of the limitations related to sensor-based technique such as device structure and classification technique are discussed as a research gap for future references.
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institution Universiti Teknologi Malaysia - ePrints
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spelling utm.eprints-765732018-05-31T09:26:11Z http://eprints.utm.my/76573/ Research and development of IMU sensors-based approach for sign language gesture recognition Abdullah, A. Abdul-Kadir, N. A. Che Harun, F. K. TK Electrical engineering. Electronics Nuclear engineering This paper discusses a few Inertial Measurement Unit (IMU) sensor-based approaches for sign language gesture recognition. Generally, there are three main research areas for the IMU sensor-based approach which consist of the device structure, sensors fusion algorithm and calibration method, and finally gesture recognition and classification method. The device structure includes the number and placement of the sensors to cover the degrees of freedom. Sensors fusion algorithms, such as complementary filter, Kalman filter, and EKF are implemented to combine a variety of sensors used for data acquisition. Several gesture classification and recognition methods are also reviewed in this paper. Some of the limitations related to sensor-based technique such as device structure and classification technique are discussed as a research gap for future references. Universiti Teknikal Malaysia Melaka 2017 Article PeerReviewed Abdullah, A. and Abdul-Kadir, N. A. and Che Harun, F. K. (2017) Research and development of IMU sensors-based approach for sign language gesture recognition. Journal of Telecommunication, Electronic and Computer Engineering, 9 (3-9). pp. 33-39. ISSN 2180-1843 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041849519&partnerID=40&md5=e047ac8ca61593d1554ec02bc3a62d8b
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Abdullah, A.
Abdul-Kadir, N. A.
Che Harun, F. K.
Research and development of IMU sensors-based approach for sign language gesture recognition
title Research and development of IMU sensors-based approach for sign language gesture recognition
title_full Research and development of IMU sensors-based approach for sign language gesture recognition
title_fullStr Research and development of IMU sensors-based approach for sign language gesture recognition
title_full_unstemmed Research and development of IMU sensors-based approach for sign language gesture recognition
title_short Research and development of IMU sensors-based approach for sign language gesture recognition
title_sort research and development of imu sensors based approach for sign language gesture recognition
topic TK Electrical engineering. Electronics Nuclear engineering
work_keys_str_mv AT abdullaha researchanddevelopmentofimusensorsbasedapproachforsignlanguagegesturerecognition
AT abdulkadirna researchanddevelopmentofimusensorsbasedapproachforsignlanguagegesturerecognition
AT cheharunfk researchanddevelopmentofimusensorsbasedapproachforsignlanguagegesturerecognition