A Linear Optimization Procedure for an EMG-driven NeuroMusculoSkeletal Model Parameters Adjusting: Validation Through a Myoelectric Exoskeleton Control

  • Domenico Buongiorno
  • Francesco Barone
  • Massimiliano Solazzi
  • Vitoantonio Bevilacqua
  • Antonio Frisoli
Conference paper

DOI: 10.1007/978-3-319-42324-1_22

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9775)
Cite this paper as:
Buongiorno D., Barone F., Solazzi M., Bevilacqua V., Frisoli A. (2016) A Linear Optimization Procedure for an EMG-driven NeuroMusculoSkeletal Model Parameters Adjusting: Validation Through a Myoelectric Exoskeleton Control. In: Bello F., Kajimoto H., Visell Y. (eds) Haptics: Perception, Devices, Control, and Applications. EuroHaptics 2016. Lecture Notes in Computer Science, vol 9775. Springer, Cham

Abstract

This paper presents a linear optimization procedure able to adapt a simplified EMG-driven NeuroMusculoSkeletal (NMS) model to the specific subject. The optimization procedure could be used to adjust a NMS model of a generic human articulation in order to predict the joint torque by using ElectroMyoGraphic (EMG) signals. The proposed approach was tested by modeling the human elbow joint with only two muscles. Using the cross-validation method, the adjusted elbow model has been validated in terms of both torque estimation performance and predictive ability. The experiments, conducted with healthy people, have shown both good performance and high robustness. Finally, the model was used to control directly and continuously a exoskeleton rehabilitation device through EMG signals. Data acquired during free movements prove the model ability to detect the human’s intention of movement.

Keywords

Myoelectric control NeuroMusculoSkeletal model Rehabilitation Exoskeleton EMG signals 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Domenico Buongiorno
    • 1
  • Francesco Barone
    • 2
  • Massimiliano Solazzi
    • 1
  • Vitoantonio Bevilacqua
    • 2
  • Antonio Frisoli
    • 1
  1. 1.PERCRO Lab, Tecip InstituteScuola Superiore Sant’AnnaPisaItaly
  2. 2.Dipartimento di Ingegneria Elettrica e dell’Informazione (DEI)Politecnico di BariBariItaly

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