Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2022 | OriginalPaper | Chapter

Wearable Ultrasound Interface for Prosthetic Hand Manipulation

Authors : Zongtian Yin, Hanwei Chen, Xingchen Yang, Yifan Liu, Ning Zhang, Jianjun Meng, Honghai Liu

Published in: Intelligent Robotics and Applications

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Ultrasound can non-invasively detect muscle deformations, which has great potential applications in prosthetic hand control. This research developed a miniaturized ultrasound device that could be integrated into a prosthetic hand socket. This compact system included four A-mode ultrasound transducers, a signal processing module, and a prosthetic hand control module. The size of the ultrasound system was 65 * 75 * 25 mm, weighing only 85 g. For the first time, we integrated the ultrasound system into a prosthetic hand socket to evaluate its performance in practical prosthetic hand control. We designed an experiment to perform six commonly used gestures, and the classification accuracy was \(95.33\%\,\pm \, 7.26\%\) for a participant. These experimental results demonstrated the efficacy of the designed prosthetic system based on the miniaturized A-mode ultrasound device, paving the way for an effective HMI system that could be widely used in prosthetic hand control.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter 3D Printed Soft Robotic Hand Combining Post-Stroke Rehabilitation and Stiffness Evaluation
Literature
1.
Smith, S.: MO-F-220-02: imaging educational course - ultrasound miniaturization. Med. Phys. 38(6), 3732–3732 (2011)CrossRef
2.
Loram, I.D., Maganaris, C.N., Lakie, M.: Use of ultrasound to make noninvasive in vivo measurement of continuous changes in human muscle contractile length. J. Appl. Physiol. 100(4), 1311–1323 (2006)CrossRef
3.
Botter, A., Vieira, T.M.M., Loram, I.D., Merletti, R., Hodson-Tole, E.F.: A novel system of electrodes transparent to ultrasound for simultaneous detection of myoelectric activity and B-mode ultrasound images of skeletal muscles. J. Appl. Physiol. 115(8), 1203–1214 (2013)CrossRef
4.
Shi, J., Guo, J.Y., Hu, S.X., Zheng, Y.P.: Recognition of finger flexion motion from ultrasound image: a feasibility study. Ultrasound Med. Biol. 38(10), 1695–704 (2012)CrossRef
5.
Akhlaghi, N., et al.: Real-time classification of hand motions using ultrasound imaging of forearm muscles. IEEE Trans. Biomed. Eng. 63(8), 1687–98 (2016)CrossRef
6.
Castellini, C., Passig, G., Zarka, E.: Using ultrasound images of the forearm to predict finger positions. IEEE Trans. Neural Syst. Rehabil. Eng. 20(6), 788–797 (2012)CrossRef
7.
Bimbraw, K., Nycz, C.J., Schueler, M., Zhang, Z., Zhang, H.K.: Prediction of Metacarpophalangeal joint angles and Classification of Hand configurations based on Ultrasound Imaging of the Forearm. arXiv:​2109.​11093 [cs] (2021)
8.
Huang, Y., Yang, X., Li, Y., Zhou, D., He, K., Liu, H.: Ultrasound-based sensing models for finger motion classification. IEEE J. Biomed. Health Inform. 22(5), 1395–1405 (2018)CrossRef
9.
Manbachi, A., Cobbold, R.S.C.: Development and application of piezoelectric materials for ultrasound generation and detection. Ultrasound 19(4), 187–196 (2011)CrossRef
10.
Mason, W.P.: Piezoelectricity, its history and applications. J. Acoust. Soc. Am. 70(6), 1561–1566 (1980)CrossRef
11.
Huang, Y., Englehart, K.B., Hudgins, B., Chan, A.D.: A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses. IEEE Trans. Biomed. Eng. 52(11), 1801–1811 (2005)CrossRef
12.
Kevin Englehart, K.B., Englehart, K., Englehart, B.H., Hudgins, B.: A robust, real-time control scheme for multifunction myoelectric control. IEEE Trans. Biomed. Eng. 50(7), 848–854 (2003)CrossRef
13.
Aldrich, J.E.: Basic physics of ultrasound imaging. Critical Care Med. 35(Suppl), S131–S137 (2007)CrossRef
14.
Waris, A., Niazi, I.K., Jamil, M., Englehart, K., Jensen, W., Kamavuako, E.N.: Multiday evaluation of techniques for EMG-based classification of hand motions. IEEE J. Biomed. Health Inform. 23(4), 1526–1534 (2019)CrossRef
15.
Narayan, Y., Mathew, L., Chatterji, S.: SEMG signal classification with novel feature extraction using different machine learning approaches. J. Intell. Fuzzy Syst. 35, 1–11 (2018)
16.
Parker, P., Englehart, K., Hudgins, B.: Myoelectric signal processing for control of powered limb prostheses. J. Electromyogr. Kinesiol. 16(6), 541–548 (2006)CrossRef
17.
He, J., Luo, H., Jia, J., Yeow, J.T.W., Jiang, N.: Wrist and finger gesture recognition with single-element ultrasound signals: a comparison with single-channel surface electromyogram. IEEE Trans. Biomed. Eng. 66(5), 1277–1284 (2019)CrossRef
18.
Zeng, J., Zhou, Y., Yang, Y., Yan, J., Liu, H.: Fatigue-sensitivity comparison of sEMG and a-mode ultrasound based hand gesture recognition. IEEE J. Biomed. Health Inform. 26, 1–8 (2021)
19.
Piech, D.K., Kay, J.E., Boser, B.E., Maharbiz, M.M.: Rodent wearable ultrasound system for wireless neural recording. In: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 221–225 (2017)
20.
Protopappas, V., Baga, D., Fotiadis, D., Likas, A., Papachristos, A., Malizos, K.: An ultrasound wearable system for the monitoring and acceleration of fracture healing in long bones. IEEE Trans. Biomed. Eng. 52(9), 1597–1608 (2005)CrossRef
21.
Yang, X., Chen, Z., Hettiarachchi, N., Yan, J., Liu, H.: A wearable ultrasound system for sensing muscular morphological deformations. IEEE Trans. Syst. Man Cybern. Syst. 51, 1–10 (2019)
22.
Shi, J., Zhou, S., Liu, X., Zhang, Q., Lu, M., Wang, T.: Stacked deep polynomial network based representation learning for tumor classification with small ultrasound image dataset. Neurocomputing 194, 87–94 (2016)CrossRef
Metadata
Title
Wearable Ultrasound Interface for Prosthetic Hand Manipulation
Authors
Zongtian Yin
Hanwei Chen
Xingchen Yang
Yifan Liu
Ning Zhang
Jianjun Meng
Honghai Liu
Copyright Year
2022
Book
Intelligent Robotics and Applications

Print ISBN: 978-3-031-13834-8

Electronic ISBN: 978-3-031-13835-5

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-031-13835-5_1

Premium Partner

    Image Credits