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author:

Zongxing, L. (Zongxing, L..) [1] (Scholars:卢宗兴) | Baizheng, H. (Baizheng, H..) [2] | Yingjie, C. (Yingjie, C..) [3] (Scholars:蔡英杰) | Bingxing, C. (Bingxing, C..) [4] (Scholars:陈炳兴) | Ligang, Y. (Ligang, Y..) [5] (Scholars:姚立纲) | Haibin, H. (Haibin, H..) [6] | Zhoujie, L. (Zhoujie, L..) [7]

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Scopus

Abstract:

The gesture recognition technology as one of the human-machine interfaces can convenient and effectively express the intention of human, and has become the hot research hotspot in recent years. Force level is a key factor while gesture recognition for more dexterous and natural prosthetic control. To provide researchers with a systematic and quick overview of the relevant and future developments in gesture recognition and force assessment techniques, this review synthesizes current commonly used sensor interfaces, data processing methods, and methods that have improved recognition performance. The experimental design and related results of gesture recognition and force assessment with various types of sensors are analyzed and compared to understand the scope of application and recognition performance of different sensors. This review summarizes the challenges and future work in the five areas of hardware, use environment, broad applicability, physiological factors, and comfort of use in practical applications. Finally, the conclusion prospects that future research may need to focus on improving model generalization and robustness to environmental, physiological factors, etc. by building large datasets and developing flexible, long-lasting, lightweight and senseless, high-performance interfaces. IEEE

Keyword:

Feature extraction Force force assessment gesture recognition Gesture recognition human-machine interaction Image segmentation Nails sensors Sensors signal acquisition Application Support vector machines

Community:

  • [ 1 ] [Zongxing L.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Baizheng H.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 3 ] [Yingjie C.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [Bingxing C.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 5 ] [Ligang Y.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 6 ] [Haibin H.]Fujian Cancer Hospital, No.420 Fuma road, Fuzhou, China
  • [ 7 ] [Zhoujie L.]First Affiliated Hospital of Fujian Medical University. No.20 Chazhong Road, Fuzhou, China

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Source :

IEEE Sensors Journal

ISSN: 1530-437X

Year: 2023

Issue: 22

Volume: 23

Page: 1-1

4 . 3

JCR@2023

4 . 3 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 13

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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