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Gesture recognition through HITEG data glove to provide a new way of communication

Published: 26 October 2011 Publication History

Abstract

Hands gestures recognition, by means of measuring apparatus, can provide a new way of human-computer interaction. Controlling different devices or speaking through a speech synthesizer can be time saving as well as an aid for impaired persons. In this work we performed the classification of 20 different gestures, evaluating three different methodologies: Support Vector Machines, Mahalanobis and Euclidean based classifiers.

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  • (2021)Toward the Minimum Number of Wearables to Recognize Signer-Independent Italian Sign Language With Machine-Learning AlgorithmsIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2021.310973270(1-9)Online publication date: 2021
  • (2021)A Novel Actuating–Sensing Bone Conduction-Based System for Active Hand Pose Sensing and Material Densities Evaluation Through Hand TouchIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2021.308848670(1-7)Online publication date: 2021
  • (2020)Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network AlgorithmsSensors10.3390/s2014387920:14(3879)Online publication date: 11-Jul-2020
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cover image ACM Other conferences
ISABEL '11: Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
October 2011
949 pages
ISBN:9781450309134
DOI:10.1145/2093698
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • Universitat Pompeu Fabra
  • IEEE
  • Technical University of Catalonia Spain: Technical University of Catalonia (UPC), Spain
  • River Publishers: River Publishers
  • CTTC: Technological Center for Telecommunications of Catalonia
  • CTIF: Kyranova Ltd, Center for TeleInFrastruktur

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2011

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ISABEL '11
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  • Technical University of Catalonia Spain
  • River Publishers
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  • CTIF

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Cited By

View all
  • (2021)Toward the Minimum Number of Wearables to Recognize Signer-Independent Italian Sign Language With Machine-Learning AlgorithmsIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2021.310973270(1-9)Online publication date: 2021
  • (2021)A Novel Actuating–Sensing Bone Conduction-Based System for Active Hand Pose Sensing and Material Densities Evaluation Through Hand TouchIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2021.308848670(1-7)Online publication date: 2021
  • (2020)Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network AlgorithmsSensors10.3390/s2014387920:14(3879)Online publication date: 11-Jul-2020
  • (2015)Resistive flex sensors: a surveySmart Materials and Structures10.1088/0964-1726/25/1/01300125:1(013001)Online publication date: 2-Dec-2015

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