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Intelligent User Interface to Control a Powered Wheelchair Using Infrared Sensors

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Intelligent Systems and Applications (IntelliSys 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 294))

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Abstract

This paper presents a new system to steer a powered wheelchair using a Sharp IR sensor and a Raspberry Pi. Interviews with occupational therapists, helpers and carers at Chailey Heritage Foundation/School revealed that clicking noises generated from closing switch contact used to operate powered wheelchairs disturbed the attention and reduced the focus of young wheelchair users having cognitive or physical disability. Also switches often slipped away and became unreachable. The new system replaced lever-switches used to steer powered wheelchairs by an electronic circuit. The circuit consisted of a Sharp IR sensor, Analogue to Digital converter, relays, and a Raspberry Pi. The sharp IR sensor detected movement in its range and the Raspberry Pi interpreted the data and generated commands to steer a powered wheelchair. Two modes were used to overcome the problem of sensors slip** from position: Click to Calibrate and Auto-Calibrate. A technical User Interface was created to modify sensitivity, user and detection settings. Practical testing showed the system behaved satisfactorily. It detected users’ voluntary movements and used them to steer a powered wheelchair and overcome the problem of switches slip** from position. Clinical trials will be conducted at Chailey Heritage Foundation.

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Acknowledgment

This research was supported by an EPSRC EP/S005927/1 project titled “Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system”. Investigators: Sanders, DA and Gegov, AE. Senior Researchers Haddad MJ and Langner MC.

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Authors and Affiliations

  1. University of Portsmouth, Portsmouth, PO1 3DJ, UK

    Malik Haddad, David Sanders, Giles Tewkesbury & Sarinova Simandjuntak

  2. Chailey Heritage Foundation, North Chailey, BN8 4EF, UK

    Martin Langner

Authors
  1. Malik Haddad
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  2. David Sanders
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  3. Giles Tewkesbury
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  4. Martin Langner
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  5. Sarinova Simandjuntak
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Corresponding author

Correspondence to Malik Haddad .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Haddad, M., Sanders, D., Tewkesbury, G., Langner, M., Simandjuntak, S. (2022). Intelligent User Interface to Control a Powered Wheelchair Using Infrared Sensors. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-82193-7_43

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