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Novel approach for powered wheelchair user identification and steering

  • M. Haddad*
  • , D. Sanders
  • , A. Gharavi
  • , M. Langner
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

A new approach to improve powered wheelchairs users’ driving ability and enhance their quality of life is described. The approach installed on shared powered mobility platforms used by multiple users, reducing time and effort required by helpers to adjust user settings and increase the driving duration. This paper presents development and preliminary testing of four integrated systems based on stakeholder consultation. The development process involved interviews with helpers, caregivers and occupational therapists at Chailey Heritage Foundation, alongside clinical observations. These consultations identified that driving sessions typically lasted 50–60 min, with significant time for setup, leaving short duration for actual driving. Based on these findings, four integrated systems working collaboratively were developed: facial recognition for user identification using one-shot learning, Digital Scanning Collision Avoidance Device range control, contactless Infra-red sensor input and automated session data collection. Prototype testing was conducted. The facial recognition system successfully identified users and correctly rejected non-registered users. The digital range system provided faster response and more options than original hardware. The contactless input system operated silently without generating clicking sounds and included an auto-calibrate function. All systems demonstrated successful integration, with driving session data collected and stored for future analysis. Preliminary observations indicated reduced setup time and increased driving time. The integrated approach reduced setup time and effort required by caregivers while increasing driving time. The systems showed proficient synergy and improved user autonomy. Future controlled trials are needed to quantify these improvements and statistically analyse data.

Original languageEnglish
JournalDisability and Rehabilitation: Assistive Technology
Early online date10 Jan 2026
DOIs
Publication statusEarly online - 10 Jan 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • assistive technology
  • Disabled
  • facial recognition
  • image processing
  • powered mobility
  • Python
  • steering

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