Flexible Strain Sensor Based on Conductive Hydrogel/KC@PDMS for Neck Motion Control Wheelchair Using EMD-LSTM Algorithm
Many disabled people who are not suitable for the control of the current mainstream manual joystick-controlled wheelchair, so the study of new control methods can provide convenience for these people, including bioelectrical signal control, voice control, visual control, etc., but these control meth...
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| Vydáno v: | IEEE sensors journal Ročník 24; číslo 3; s. 1 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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IEEE
01.02.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1530-437X, 1558-1748 |
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| Abstract | Many disabled people who are not suitable for the control of the current mainstream manual joystick-controlled wheelchair, so the study of new control methods can provide convenience for these people, including bioelectrical signal control, voice control, visual control, etc., but these control methods have peripheral equipment complex or susceptible to environmental noise interference, in contrast, These problems can be solved effectively by using a wearable flexible sensor to recognize human movement signal. To collect and identify the strain signal characteristics of the moving neck muscles, based on the principle of flexible piezoresistive sensor, we designed and produced a K-Carrageenan @PDMS flexible sensor, and designed a series of experiments to explore the conductive properties, mechanical properties, air permeability of the sensor, and also designed the peripheral acquisition circuit and signal processing algorithm. Finally, the EMD-LSTM algorithm is used to classify the signal and explore the feasibility of fitting the signal to the human neck to control the wheelchair. The results show that the maximum tensile rate of the sensor designed by us is as high as 180%, and the air permeability is also improved slightly. After 1000 cycles of stretching, the sensor still has good performance and can effectively collect human neck action signals. Through the field test, the accuracy of this system is up to 95%, which provides a new idea for wheelchair control. |
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| AbstractList | Many disabled people who are not suitable for the control of the current mainstream manual joystick-controlled wheelchair, so the study of new control methods can provide convenience for these people, including bioelectrical signal control, voice control, visual control, etc., but these control methods have peripheral equipment complex or susceptible to environmental noise interference, in contrast, These problems can be solved effectively by using a wearable flexible sensor to recognize human movement signal. To collect and identify the strain signal characteristics of the moving neck muscles, based on the principle of flexible piezoresistive sensor, we designed and produced a K-Carrageenan @PDMS flexible sensor, and designed a series of experiments to explore the conductive properties, mechanical properties, air permeability of the sensor, and also designed the peripheral acquisition circuit and signal processing algorithm. Finally, the EMD-LSTM algorithm is used to classify the signal and explore the feasibility of fitting the signal to the human neck to control the wheelchair. The results show that the maximum tensile rate of the sensor designed by us is as high as 180%, and the air permeability is also improved slightly. After 1000 cycles of stretching, the sensor still has good performance and can effectively collect human neck action signals. Through the field test, the accuracy of this system is up to 95%, which provides a new idea for wheelchair control. Many disabled people are not suitable for the control of the current mainstream manual joystick-controlled wheelchair, so the study of new control methods can provide convenience for these people, including bioelectrical signal control, voice control, and visual control, but these control methods have peripheral equipment complex or susceptible to environmental noise interference, in contrast. These problems can be solved effectively by using a wearable flexible sensor to recognize human movement signal. To collect and identify the strain signal characteristics of the moving neck muscles, based on the principle of flexible piezoresistive sensor, we designed and produced a K-carrageenan at polydimethylsiloxane (PDMS) flexible sensor, designed a series of experiments to explore the conductive properties, mechanical properties, and air permeability of the sensor, and also designed the peripheral acquisition circuit and signal processing algorithm. Finally, the empirical mode decomposition (EMD)-long short-term memory (LSTM) algorithm is used to classify the signal and explore the feasibility of fitting the signal to the human neck to control the wheelchair. The results show that the maximum tensile rate of the sensor designed by us is as high as 180%, and the air permeability is also improved slightly. After 1000 cycles of stretching, the sensor still has good performance and can effectively collect human neck action signals. Through the field test, the accuracy of this system is up to 95%, which provides a new idea for wheelchair control. |
| Author | Yao, Daojin Huang, Yifeng Guo, Zhilong Wang, Xiaoming Dong, Wentao Xiong, Longbo |
| Author_xml | – sequence: 1 givenname: Xiaoming orcidid: 0000-0003-2516-4354 surname: Wang fullname: Wang, Xiaoming organization: School of Electrical and Automation Engineering, China – sequence: 2 givenname: Longbo orcidid: 0009-0004-0759-4486 surname: Xiong fullname: Xiong, Longbo organization: pursuing a Master's degree in Control Engineering from the School of Electrical and Automation, East China Jiaotong University, Nanchang, China – sequence: 3 givenname: Wentao orcidid: 0000-0002-7207-8355 surname: Dong fullname: Dong, Wentao organization: School of Electrical and Automation Engineering, China – sequence: 4 givenname: Zhilong surname: Guo fullname: Guo, Zhilong organization: pursuing a Master's degree in Control Engineering from the School of Electrical and Automation, East China Jiaotong University, Nanchang, China – sequence: 5 givenname: Yifeng orcidid: 0000-0003-2516-4354 surname: Huang fullname: Huang, Yifeng organization: School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, China – sequence: 6 givenname: Daojin surname: Yao fullname: Yao, Daojin organization: School of Electrical and Automation Engineering, China |
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| Snippet | Many disabled people who are not suitable for the control of the current mainstream manual joystick-controlled wheelchair, so the study of new control methods... Many disabled people are not suitable for the control of the current mainstream manual joystick-controlled wheelchair, so the study of new control methods can... |
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| SubjectTerms | Algorithms Background noise Bioelectricity Carrageenan Circuit design Control equipment Control methods Field tests Flexible components Flexible sensor Human motion Mechanical properties Motion control Neck neck movement recognition Permeability Polydimethylsiloxane Sensors Signal classification Signal processing signal processing algorithm Visual control Voice control wheelchair control Wheelchairs |
| Title | Flexible Strain Sensor Based on Conductive Hydrogel/KC@PDMS for Neck Motion Control Wheelchair Using EMD-LSTM Algorithm |
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