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Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic...

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8230a7d56ecc4d88b6ae94a5f20db60b

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review

About this item

Full title

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review

Publisher

Switzerland: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2020-04, Vol.20 (9), p.2467

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Today, daily life is composed of many computing systems, therefore interacting with them in a natural way makes the communication process more comfortable. Human–Computer Interaction (HCI) has been developed to overcome the communication barriers between humans and computers. One form of HCI is Hand Gesture Recognition (HGR), which predicts the cla...

Alternative Titles

Full title

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_8230a7d56ecc4d88b6ae94a5f20db60b

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8230a7d56ecc4d88b6ae94a5f20db60b

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s20092467

How to access this item