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A Cross-Sectional Study Using Wireless Electrocardiogram to Investigate Physical Workload of Wheelchair Control in Real World Environments

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Advances in Neuroergonomics and Cognitive Engineering (AHFE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 953))

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Abstract

The wheelchair is a key invention that provides individuals with limitations in mobility increased independence and participation in society. However, wheelchair control is a complicated motor task that increases physical and mental workload. New wheelchair interfaces, including power-assisted devices can further enable users by reducing the required effort especially in more demanding environments. The protocol engaged novice wheelchair users to push a wheelchair with and without power assist in a simple and complex environment using wireless Electrocardiogram (ECG) to approximate heart rate (HR). Results indicated that HR determined from ECG data, decreased with use of the power-assist. The use of power-assist however did reduce behavioral performance, particularly within obstacles that required more control.

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Acknowledgments

We would like to thank Jamie Whitty and Joel Chappell of the School of Architecture from Oxford Brookes University, for constructing our ramps, Ian Allen, the Oxford Brookes sports booking coordinator, for helping us with numerous appointments, and our research assistants Cyrus Goodger, Jessica Andrich, and JoJo Dawes. This research was funded through the Adaptive Assistive Rehabilitative Technologies – Beyond the Clinic grant by the Engineering and Physical Sciences Research Council (EP/M025543/1). SJ is additionally supported by the Fulbright US-UK Commission. HD is supported by the Elizabeth Casson Trust and received support from the NIHR Oxford health Biomedical Research Centre. Additional support provided by CONACYT (National Council of Science and Technology in Mexico).

Author information

Authors and Affiliations

  1. School of Biomedical Engineering, Science & Health Systems, Drexel University, Philadelphia, PA, USA

    Shawn Joshi & Hasan Ayaz

  2. College of Medicine, Drexel University, Philadelphia, PA, USA

    Shawn Joshi

  3. Movement Science Group, Oxford Brookes University, Oxford, UK

    Shawn Joshi, Daniella Nicole Springett, Benjamin David Weedon & Helen Dawes

  4. Oxford Institute of Nursing, Midwifery, and Allied Health Research, Oxford, UK

    Shawn Joshi, Daniella Nicole Springett, Benjamin David Weedon & Helen Dawes

  5. Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK

    Shawn Joshi, Daniella Nicole Springett, Benjamin David Weedon & Helen Dawes

  6. UCL Interaction Centre, University College London, London, UK

    Roxana Ramirez Herrera, Dafne Zuleima Morgado Ramirez & Catherine Holloway

  7. Global Disability Innovation Hub, London, UK

    Dafne Zuleima Morgado Ramirez & Catherine Holloway

  8. Department of Family and Community Health, University of Pennsylvania, Philadelphia, PA, USA

    Hasan Ayaz

  9. Center for Injury Research and Prevention, Children’s Hospital of Philadelphia, Phialdelphia, PA, USA

    Hasan Ayaz

  10. Drexel Business Solution Institute, Drexel University, Philadelphia, PA, USA

    Hasan Ayaz

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  1. Shawn Joshi
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  2. Roxana Ramirez Herrera
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Correspondence to Shawn Joshi .

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Editors and Affiliations

  1. Drexel University, Philadelphia, PA, USA

    Hasan Ayaz

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Joshi, S. et al. (2020). A Cross-Sectional Study Using Wireless Electrocardiogram to Investigate Physical Workload of Wheelchair Control in Real World Environments. In: Ayaz, H. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 953. Springer, Cham. https://doi.org/10.1007/978-3-030-20473-0_2

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