Skip to main content

Prototype Upper Limb Prosthetic Controlled by Myoelectric Signals Using a Digital Signal Processor Platform

  • Conference paper
  • First Online:
Interdisciplinary Applications of Kinematics

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 26))

  • 1062 Accesses

Abstract

In this research project, we aimed to design and implement an upper limb prosthesis controlled by myoelectric signals using a digital signal processor platform. To emulate the seven main movements of a human arm, a robotic arm was produced that was capable of using the control signals generated by a human arm, where we captured the electrical pulses to design a silver/silver chloride contact type surface electrode using a plating process in a chemical laboratory. This method is an alternative technological support for amputees or partially paralyzed muscles, which typically remain intact so they can exercise control. The signals produced by these muscles can operate a prosthesis or a robotic device. Therefore, the prototype arm design process comprised the following steps. The dimensions and joints of a human arm were determined and reproduced as a robotic arm, where software was designed to run simulations of the robotic arm to make corrections before the final prototype design was produced. The robotic arm was implemented according to the specifications obtained and a motor control circuit was produced to replicate each of the seven movements of the robotic arm. Finally, a validation was performed for each of the movements performed by the robotic arm by considering the position, speed of flexion, and extension of the joints.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Acosta M (2000) Tutorial sobre redes neuronales aplicadas en Ingeniera eléctrica y su implementación. Universidad Tecnológica de Pereira

    Google Scholar 

  • Betancourt G, Suárez E, Franco, J (2004) Reconocimiento de patrones de movimiento a partir de señales electromiografícas. In: Scientia et Technica Año X, vol 53, no 26. UTP. ISSN 0122–1701

    Google Scholar 

  • Du S, Vuskovic M (2003) Temporal vs. spectral approach to feature extraction from prehensile EMG signals. Department of Computer Science, San Diego State University, San Diego

    Google Scholar 

  • Englehart K (1998) Signal representation for classification of the transient myoelectric signal. Doctoral Thesis

    Google Scholar 

  • Englehart K, Hudgins B, Parker P (2001) A wavelet-based continuous classification scheme for multifunction myoelectric control. IEEE Trans Biomed Eng 48(3):302–311

    Google Scholar 

  • Farfan F, Polittiy J, Felice C (2005) Evaluación de patrones temporales y espectrales para el control Mioeléctrico. XV Congreso de Bioingeniería, Argentina

    Google Scholar 

  • Guyton A, John M, Hall E (2006) Textbook of Medical Physiology. Elsevier, Philadelphia

    Google Scholar 

  • Khushaba R, Al-Juamily A (2007) Fuzzy wavelet packet based feature extraction method for multifunction myoelectric control. Int J Biomed Sci 2(3)

    Google Scholar 

  • Kuo S, Lee B (2010) Real-time digital signal processor. Implementations, applications and experiments with TMS320C55x. In: Nilsj N (ed) The quest for artificial intelligence: a history of ideas and achievements. Stanford University

    Google Scholar 

  • López N, di Sciascio F, Soria C, Valentinuzzi M (2009) Robust EMG sensing system based on data fusion for myoelectric control of a robotic arm. Facultad Ingeniería, Universidad Nacional de San Juan, Gabinete de Tecnología Médica, Argentina

    Google Scholar 

  • Romo H, Realpe EJ, Jojoa P (2007) Análisis de Señales EMG Superficiales y su Aplicación en Control de Prótesis de Mano PhD. Universidad del Cauca

    Google Scholar 

  • Shadow Robot Company (2011) http://www.shadowrobot.com/

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nancy I. Orihuela Ordoñez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Zapana, U.G., Apaza, R.M.C., Ordoñez, N.I.O., Rivera, A.C. (2015). Prototype Upper Limb Prosthetic Controlled by Myoelectric Signals Using a Digital Signal Processor Platform. In: Kecskeméthy, A., Geu Flores, F. (eds) Interdisciplinary Applications of Kinematics. Mechanisms and Machine Science, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-10723-3_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10723-3_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10722-6

  • Online ISBN: 978-3-319-10723-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics