Your browser doesn't support javascript.
loading
Self-Powered Gesture Recognition Wristband Enabled by Machine Learning for Full Keyboard and Multicommand Input.
Tan, Puchuan; Han, Xi; Zou, Yang; Qu, Xuecheng; Xue, Jiangtao; Li, Tong; Wang, Yiqian; Luo, Ruizeng; Cui, Xi; Xi, Yuan; Wu, Le; Xue, Bo; Luo, Dan; Fan, Yubo; Chen, Xun; Li, Zhou; Wang, Zhong Lin.
Afiliação
  • Tan P; Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, P. R. China.
  • Han X; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Zou Y; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Qu X; Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China.
  • Xue J; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Li T; School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing, 100081, P. R. China.
  • Wang Y; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Luo R; School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China.
  • Cui X; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Xi Y; School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing, 100081, P. R. China.
  • Wu L; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Xue B; Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China.
  • Luo D; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Fan Y; Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China.
  • Chen X; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
  • Li Z; Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China.
  • Wang ZL; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
Adv Mater ; 34(21): e2200793, 2022 May.
Article em En | MEDLINE | ID: mdl-35344226
ABSTRACT
Virtual reality is a brand-new technology that can be applied extensively. To realize virtual reality, certain types of human-computer interaction equipment are necessary. Existing virtual reality technologies often rely on cameras, data gloves, game pads, and other equipment. These equipment are either bulky, inconvenient to carry and use, or expensive to popularize. Therefore, the development of a convenient and low-cost high-precision human-computer interaction device can contribute positively to the development of virtual reality technology. In this study, a gesture recognition wristband that can realize a full keyboard and multicommand input is developed. The wristband is convenient to wear, low in cost, and does not affect other daily operations of the hand. This wristband is based on physiological anatomy as well as aided by active sensor and machine learning technology; it can achieve a maximum accuracy of 92.6% in recognizing 26 letters. This wristband offers broad application prospects in the fields of gesture command recognition, assistive devices for the disabled, and wearable electronics.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dispositivos Eletrônicos Vestíveis / Gestos Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dispositivos Eletrônicos Vestíveis / Gestos Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article