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A self-powered flexible piezoelectric sensor patch for deep learning-assisted motion identification and rehabilitation training system

Guo, Y. (author)
Zhang, H. (author)
Fang, L. (author)
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Wang, Z. (author)
He, W. (author)
Shi, S. (author)
Zhang, Renyun (author)
Mittuniversitetet,Institutionen för ingenjörsvetenskap, matematik och ämnesdidaktik (2023-)
Cheng, J. (author)
Wang, P. (author)
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 (creator_code:org_t)
Elsevier BV, 2024
2024
English.
In: Nano Energy. - : Elsevier BV. - 2211-2855 .- 2211-3282. ; 123
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Artificial intelligence-assisted wearable devices have attracted great interest in medical treatment and healthcare. However, wearable electronic devices are expensive to manufacture and usually depend on external power supply. Herein, a flexible self-powered piezoelectric sensor patch (SPP) using Polyvinylidene fluoride (PVDF) fibrous film as the functional layer is demonstrated for the assessment and motion identification of wrist joint rehabilitation training. PVDF fibrous film is prepared by a triboelectric nanogenerator (TENG)-driven near-field electrospinning system with a special designed synchronous mechanical switch. The results show that this flexible SPP has a high sensitivity of 0.2768 V KPa−1 at pressures from 1 to 75 kPa. Such excellent flexibility allows us to attach the SPP to the finger as a tactile sensor for rehabilitation assessment of wrist joint flexibility. In addition, long short-term memory network model is used to process the collected data from the SPP for motion identification. The test accuracy of the SPP wrist motion identification reaches 92.6%, which afford a potential way to understand the progress of the rehabilitation training of patients' wrists. Generally, this flexible SPP shows great promise for applications in the fields of motion monitoring, medical diagnosis and rehabilitation training based on artificial intelligence. 

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Keyword

Motion identification
Near-field electrospinning
Piezoelectric sensor
Rehabilitation training
Triboelectric nanogenerator

Publication and Content Type

ref (subject category)
art (subject category)

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By the author/editor
Guo, Y.
Zhang, H.
Fang, L.
Wang, Z.
He, W.
Shi, S.
show more...
Zhang, Renyun
Cheng, J.
Wang, P.
show less...
About the subject
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Electrical Engin ...
Articles in the publication
Nano Energy
By the university
Mid Sweden University

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