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Analysing the Impact of Vibrations on Smart Wheelchair Systems and Users

Mohamed, Elhassan, Sirlantzis, Konstantinos, Howells, Gareth (2022) Analysing the Impact of Vibrations on Smart Wheelchair Systems and Users. In: ICPRAI 2022 - 3rd International Conference on Pattern Recognition and Artificial Intelligence, 1-3 Jun 2022, Paris, France. (In press) (KAR id:93971)

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Abstract

Mechanical vibrations due to uneven terrains can significantly impact the accuracy of computer vision systems installed on any moving vehicle. In this study, we investigate the impact of mechanical vibrations induced using artificial bumps in a controlled environment on the performance of smart computer vision systems installed on an Electrical powered Wheelchair (EPW). Besides, the impact of the vibrations on the user's health and comfort is quantified using the vertical acceleration of an Inertial Measurement Unit (IMU) sensor according to the ISO standard 2631. The proposed smart computer vision system is a semantic segmentation based on deep learning for pixels classification that provides environmental cues for visually impaired users to facilitate safe and independent navigation. In addition, it provides the EPW user with the estimated distance to objects of interest. Results show that a high level of vibrations can negatively impact the performance of the computer vision system installed on powered wheelchairs. Also, high levels of whole-body vibrations negatively impact the user's health and comfort.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: computer vision, deep learning, Mechanical vibration, pixel classification, Powered Wheelchair, semantic segmentation, semantic segmentation system performance, Smart Systems, Vibration Impact, Whole-body vibration
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Elhassan Mohamed
Date Deposited: 09 Apr 2022 15:40 UTC
Last Modified: 11 Apr 2022 14:19 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/93971 (The current URI for this page, for reference purposes)
Mohamed, Elhassan: https://orcid.org/0000-0001-9746-1564
Sirlantzis, Konstantinos: https://orcid.org/0000-0002-0847-8880
Howells, Gareth: https://orcid.org/0000-0001-5590-0880
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