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Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces.

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Title: Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces.
Authors: Yu, Tianshi1, tianshiy@student.unimelb.edu.au, Mohammadi, Alireza1, alireza.mohammadi@unimelb.edu.au, Tan, Ying1, yingt@unimelb.edu.au, Choong, Peter2, pchoong@unimelb.edu.au, Oetomo, Denny1, doetomo@unimelb.edu.au
Source: IEEE Transactions on Neural Systems & Rehabilitation Engineering; 2024, Vol. 31, p1732-1742, 11p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces.
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Neural+Systems+%26+Rehabilitation+Engineering%22">IEEE Transactions on Neural Systems & Rehabilitation Engineering</searchLink>; 2024, Vol. 31, p1732-1742, 11p
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1109/TNSRE.2023.3258225
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 1732
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      – TitleFull: Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces.
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      – PersonEntity:
          Name:
            NameFull: Yu, Tianshi
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            NameFull: Mohammadi, Alireza
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            NameFull: Tan, Ying
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            NameFull: Choong, Peter
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            NameFull: Oetomo, Denny
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            – D: 01
              M: 07
              Text: 2024
              Type: published
              Y: 2023
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              Value: 15344320
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              Value: 31
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            – TitleFull: IEEE Transactions on Neural Systems & Rehabilitation Engineering
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