A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements
The recognition of hand movements is an important method for human-computer interaction (HCI) technology, and it is widely used in virtual reality and other HCI areas. While many valuable efforts have been made, efficient ways to capture over 20 types of hand movements with high accuracy by one data...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/9472053 |
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| _version_ | 1832560899018194944 |
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| author | Yuhuang Zheng |
| author_facet | Yuhuang Zheng |
| author_sort | Yuhuang Zheng |
| collection | DOAJ |
| description | The recognition of hand movements is an important method for human-computer interaction (HCI) technology, and it is widely used in virtual reality and other HCI areas. While many valuable efforts have been made, efficient ways to capture over 20 types of hand movements with high accuracy by one data glove are still lacking. This paper addresses a new classification framework for 52 hand movements. This classification framework includes the following two parts: the movement detection algorithm and the movement classification algorithm. The fine K-nearest neighbor (Fine KNN) is the core of the movement detection algorithm. The movement classification algorithm is composed of downsampling in data preparation and a new deep learning network named the DBDF network. Bidirectional Long Short-Term Memory (BiLSTM) is the main part of the DBDF network. The results of experiments using the Ninapro DB1 dataset demonstrate that our work can classify more types of hand movements than related algorithms with a precision of 93.15%. |
| format | Article |
| id | doaj-art-c13cb9b7dc8f45d9920075a1fd32854d |
| institution | Kabale University |
| issn | 2090-0155 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-c13cb9b7dc8f45d9920075a1fd32854d2025-02-03T01:26:26ZengWileyJournal of Electrical and Computer Engineering2090-01552021-01-01202110.1155/2021/9472053A Noble Classification Framework for Data Glove Classification of a Large Number of Hand MovementsYuhuang Zheng0Academic Affairs OfficeThe recognition of hand movements is an important method for human-computer interaction (HCI) technology, and it is widely used in virtual reality and other HCI areas. While many valuable efforts have been made, efficient ways to capture over 20 types of hand movements with high accuracy by one data glove are still lacking. This paper addresses a new classification framework for 52 hand movements. This classification framework includes the following two parts: the movement detection algorithm and the movement classification algorithm. The fine K-nearest neighbor (Fine KNN) is the core of the movement detection algorithm. The movement classification algorithm is composed of downsampling in data preparation and a new deep learning network named the DBDF network. Bidirectional Long Short-Term Memory (BiLSTM) is the main part of the DBDF network. The results of experiments using the Ninapro DB1 dataset demonstrate that our work can classify more types of hand movements than related algorithms with a precision of 93.15%.http://dx.doi.org/10.1155/2021/9472053 |
| spellingShingle | Yuhuang Zheng A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements Journal of Electrical and Computer Engineering |
| title | A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements |
| title_full | A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements |
| title_fullStr | A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements |
| title_full_unstemmed | A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements |
| title_short | A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements |
| title_sort | noble classification framework for data glove classification of a large number of hand movements |
| url | http://dx.doi.org/10.1155/2021/9472053 |
| work_keys_str_mv | AT yuhuangzheng anobleclassificationframeworkfordatagloveclassificationofalargenumberofhandmovements AT yuhuangzheng nobleclassificationframeworkfordatagloveclassificationofalargenumberofhandmovements |