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Eye and Voice-Controlled Human Machine Interface System for Wheelchairs Using Image Gradient Approach.

Saba Anwer1, Asim Waris1, Hajrah Sultan1

  • 1School of Mechanical and Manufacturing Engineering, National University of Sciences and Technology, Islamabad 45200, Pakistan.

Sensors (Basel, Switzerland)
|September 30, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel eye-tracking and voice-controlled wheelchair system for individuals with severe mobility impairments. The system offers precise control, enhancing independence and usability for people with quadriplegia and paralysis.

Keywords:
AMR voiceOpen-CVRaspberry Pihuman machine interface (HMI)image gradientimage processingquadriplegiarehabilitationwheelchair

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Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Rehabilitation Technology

Background:

  • Electromechanical mobility aids, particularly wheelchairs, require advanced human-machine interfaces (HMIs) for effective control by individuals with severe physical disabilities.
  • Existing biosignal-based control systems face challenges in providing precise commands for users with conditions like quadriplegia and paralysis.

Purpose of the Study:

  • To develop and evaluate a novel optical signal-driven system for controlling electromechanical wheelchairs.
  • To address the control limitations of conventional wheelchairs for individuals with high levels of physical impairment.

Main Methods:

  • A two-part system was developed: optical signal processing for eye movement detection and a mechanical module for wheelchair control.
  • Real-time image capture using a web camera and processing via a Raspberry-Pi with a Linux operating system.
  • Incorporation of a voice-controlled mode for enhanced reliability and user-friendliness.

Main Results:

  • The system demonstrated successful operation with an average response time of 3 seconds for eye control and 3.4 seconds for voice control.
  • Performance was evaluated using a wheelchair skill test (WST), analyzing basic movements on various surfaces and turning capabilities.
  • The system's control mechanisms, compatibility, design, and usability were assessed for diverse conditions.

Conclusions:

  • The developed optical and voice-controlled wheelchair system offers a viable and effective solution for individuals with severe mobility impairments.
  • The system enhances user independence and provides precise control, outperforming existing setups in usability and diverse condition applicability.