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Design and Development of a Robotic Platform Based on Virtual Reality Scenarios and Wearable Sensors for Upper Limb Rehabilitation and Visuomotor Coordination

  • Stefano MazzoleniEmail author
  • Elena Battini
  • Domenico Buongiorno
  • Daniele Giansanti
  • Mauro Grigioni
  • Giovanni Maccioni
  • Federico Posteraro
  • Francesco Draicchio
  • Vitoantonio Bevilacqua
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11645)

Abstract

The work reintegration following shoulder biomechanical overload illness is a multidimensional process, especially for those tasks requiring strength, movement control and arm dexterity. Currently different robotic devices used for upper limb rehabilitation are available on the market, but these devices are not based on activities focused on the work reintegration. Furthermore, the rehabilitation programmes aimed to the work reintegration are insufficiently focused on the recovery of the necessary skills for the re-employment.

In this study the details of the design of an innovative robotic platform integrated with wearable sensors and virtual reality scenarios for upper limbs motor rehabilitation and visuomotor coordination is presented. The design of control strategy will also be introduced. The robotic platform is based on a robotic arm characterized by seven degrees of freedom and by an adaptive control, wearable sensorized insoles, virtual reality (VR) scenarios and the Leap Motion device to track the hand gestures during the rehabilitation training. Future works will address the application of deep learning techniques for the analysis of the acquired big amount of data in order to automatically adapt both the difficulty level of the VR serious games and amount of motor assistance provided by the robot.

Keywords

Robotic devices Wearable sensors Virtual reality Upper limb rehabilitation Pattern recognition Deep learning 

Notes

Acknowledgments

This study has been funded by Istituto Nazionale per l’Assicurazione contro gli Infortuni sul Lavoro (INAIL) under the framework of Bando BRiC INAIL 2016 (project ROBOVIR).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Stefano Mazzoleni
    • 1
    Email author
  • Elena Battini
    • 1
  • Domenico Buongiorno
    • 2
  • Daniele Giansanti
    • 3
  • Mauro Grigioni
    • 3
  • Giovanni Maccioni
    • 3
  • Federico Posteraro
    • 4
  • Francesco Draicchio
    • 5
  • Vitoantonio Bevilacqua
    • 2
  1. 1.The BioRobotics InstituteScuola Superiore Sant’AnnaPisaItaly
  2. 2.Department of Electrical and Information Engineering (DEI)Polytechnic University of BariBariItaly
  3. 3.Istituto Superiore di SanitàRomeItaly
  4. 4.UOC Recupero e Rieducazione FunzionaleLido di CamaioreItaly
  5. 5.Department of Occupational and Environmental Medicine, Epidemiology and HygieneINAILRomeItaly

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