Advancements in intelligent wheelchairs: a scoping review
-
Mahboube Haghpanah
Abstract
When designed to meet users’ needs and consider their environment, wheelchairs have the capability to increase participation and positively affect the users’ quality of life. The application of artificial intelligence (AI) techniques has tremendous potential to enhance the intelligence aspect of powered wheelchairs (PW) by providing solutions to predict harms, collect a variety of data, including new and existing data, and contribute to comfort improvement initiatives. However, the use of existing intelligent PW (IPW) can be challenging and can pose safety concerns while not fully meeting user needs. A literature search was conducted in July 2024, using three databases: Scopus, IEEE Xplore, and Google Scholar. Articles were included if they reported improvements in IPWs based on AI techniques and user-centered design. Technological advancements based on AI techniques will allow IPWs to offer a better quality of life to their users by addressing the challenges they face in real settings. This scoping review found that efforts are being made to provide tools for route navigation, train users to operate IPWs in various situations, offer multiple control options, and improve comfort while preventing pressure ulcers due to limited mobility.
Zusammenfassung
Wenn Rollstühle so gestaltet sind, dass sie den Bedürfnissen der Nutzer entsprechen und deren Umfeld berücksichtigen, können sie die Teilhabe erhöhen und sich positiv auf die Lebensqualität der Nutzer auswirken. Der Einsatz von Techniken der künstlichen Intelligenz (KI) birgt enormes Potenzial, den Intelligenzaspekt von elektrischen Rollstühlen (ER) zu verbessern, indem Lösungen zur Vorhersage von Gefahren bereitgestellt, eine Vielzahl von Daten - sowohl neue als auch bestehende - gesammelt und Initiativen zur Komfortverbesserung unterstützt werden. Die Nutzung bestehender intelligenter elektrischer Rollstühle (IER) kann jedoch herausfordernd sein und Sicherheitsbedenken aufwerfen, während sie die Bedürfnisse der Nutzer nicht vollständig erfüllen. Im Juli 2024 wurde eine Literaturrecherche in drei Datenbanken durchgeführt: Scopus, IEEE Xplore und Google Scholar. Artikel wurden einbezogen, wenn sie Verbesserungen von IERs auf Basis von KI-Techniken und nutzerzentriertem Design berichteten. Technologische Fortschritte auf Basis von KI-Techniken werden es IERs ermöglichen, ihren Nutzern eine bessere Lebensqualität zu bieten, indem sie die Herausforderungen adressieren, denen sie in realen Umgebungen begegnen. Diese Scoping-Übersicht ergab, dass Bemühungen unternommen werden, Werkzeuge zur Routennavigation bereitzustellen, Nutzer im Umgang mit IERs in verschiedenen Situationen zu schulen, mehrere Steuerungsoptionen anzubieten und den Komfort zu verbessern, während gleichzeitig Druckgeschwüre aufgrund eingeschränkter Mobilität verhindert werden.
About the authors
Mahboube Haghpanah is a Master’s student in Electrical Engineering at Université de Sherbrooke. Her research focuses on human-robot interaction and social navigation for intelligent powered wheelchairs. She is particularly interested in integrating computer vision and deep learning to improve safety and autonomy for people with mobility impairments.
François Ferland is an associate professor in Robotics Engineering at Université de Sherbrooke (2017-present) and the Associate Dean of Academic Affairs for the Faculty of Engineering (June 2025-present). His research interests include software architectures for autonomous robots and systems, advanced driving assistance systems and human-robot interaction.
Adina M. Panchea (Member, IEEE) is an assistant professor in Robotics Engineering at the Faculty of Engineering Université de Sherbrooke since March 2023. Her research interests focus on using mathematical tools to understand the functioning of the central nervous system to analyze human motor control, aiming to design robotic solutions and decision aids like those of humans.
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: None declared.
-
Conflict of interest: The authors state no conflict of interest.
-
Research funding: This work is supported Fonds de recherche du Québec – Nature et technologies (FRQNT) – Regroupement stratégique sur l’ingénierie de technologies interactives en réadaptation (INTER), mandates 93, 113, 113B and 145.
-
Data availability: Not applicable.
References
[1] S. K. Sahoo and B. B. Choudhury, “A review on smart robotic wheelchairs with advancing mobility and independence for individuals with disabilities,” J. Decis. Anal. Intell. Comput., vol. 3, no. 1, pp. 221–242, 2023, https://doi.org/10.31181/10001122023s.Search in Google Scholar
[2] M. C. V. Nuttin, “Design and development of a new sensor system for assistive powered wheelchairs,” Technol. Disabil., vol. 19, no. 1, pp. 7–15, 2007.10.3233/TAD-2007-19102Search in Google Scholar
[3] Y. Luo and Y. Xie, “The design and implementation of a gesture-driven system for intelligent wheelchairs based on the orientation histogram method,” Software Eng. Knowl. Eng.: Theor. Pract., vol. 115, pp. 109–113, 2012, https://doi.org/10.1007/978-3-642-25349-2-15.Search in Google Scholar
[4] L. Montesano and J. D. M. B. S. Minguez, “Towards an intelligent wheelchair system for cerebral palsy users,” IEEE Trans. Neural Syst. Rehabil. Eng. A Publ. IEEE Eng. Med. Biol. Soc., vol. 18, no. 2, pp. 193–202, 2010.10.1109/TNSRE.2009.2039592Search in Google Scholar PubMed
[5] J. Pineau, A. K. R. V. J. Atrash, R. Kaplow, and J. Villemure, “On the design and validation of an intelligent powered wheelchair: lessons from the smart wheeler project,” Brain, Body and Machine, vol. 83, pp. 259–268, 2010, https://doi.org/10.1007/978-3-642-16259-6-20.Search in Google Scholar
[6] A. Erdogan and B. Argall, “The effect of robotic wheelchair control paradigm and interface on user performance, effort and preference: an experimental assessment,” Robot. Autonom. Syst., vol. 94, pp. 282–297, 2017, https://doi.org/10.1016/j.robot.2017.04.013.Search in Google Scholar
[7] N. Padfield, A. Agius Anastasi, T. F. S. B. M. C. K C, S. Fabri, M. Bugeja, and K. Camilleri, “Bci-controlled wheelchairs: end-users’ perceptions, needs, and expectations, an interview-based study,” Disabil. Rehabil. Assist. Technol., vol. 19, no. 4, pp. 1539–1551, 2024, https://doi.org/10.1080/17483107.2023.2211602.Search in Google Scholar PubMed
[8] H. Arksey and L. O’Malley, “Scoping studies: towards a methodological framework,” Int. J. Soc. Res. Methodol., vol. 8, no. 1, pp. 19–32, 2005, https://doi.org/10.1080/1364557032000119616.Search in Google Scholar
[9] N. R. P. M. J. P. C. C. Haddaway and L. A. McGuinness, “Prisma2020: an r package and shiny app for producing prisma 2020-compliant flow diagrams, with interactivity for optimised digital transparency and open synthesis,” Campbell Syst. Rev., vol. 18, no. 2, pp. 1891–1803, 2022.10.1002/cl2.1230Search in Google Scholar PubMed PubMed Central
[10] Y.-S. Yang, A. Koontz, Y.-H. Hsiao, C.-T. Pan, and J.-J. Chang, “Assessment of wheelchair propulsion performance in an immersive virtual reality simulator,” Int. J. Environ. Res. Publ. Health, vol. 18, no. 15, p. 15, 2021.10.3390/ijerph18158016Search in Google Scholar PubMed PubMed Central
[11] S. Mascetti, G. Civitarese, O. El Malak, and C. Bettini, “Smartwheels: detecting urban features for wheelchair users’ navigation,” Pervasive and Mob. Comput., vol. 62, no. C, 2020, Art. no. 101115. https://doi.org/10.1016/j.pmcj.2020.101115.Search in Google Scholar
[12] J. Tang, Y. Liu, D. Hu, and Z. Zhou, “Towards bci-actuated smart wheelchair system,” BioMed. Eng. Online, vol. 17, no. 1, p. 1, 2018.10.1186/s12938-018-0545-xSearch in Google Scholar PubMed PubMed Central
[13] Y. Rabhi, M. Mrabet, and F. Fnaiech, “Intelligent control wheelchair using a new visual joystick,” J. Healthcare Eng., vol. 2018, no. 1, pp. 1–20, 2018. https://doi.org/10.1155/2018/6083565.Search in Google Scholar PubMed PubMed Central
[14] S. He, et al.., “A p300-based threshold-free brain switch and its application in wheelchair control,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 25, no. 6, pp. 715–725, 2017, https://doi.org/10.1109/tnsre.2016.2591012.Search in Google Scholar PubMed
[15] C. Ma, W. Li, R. Gravina, and G. Fortino, “Posture detection based on smart cushion for wheelchair users,” Sensors (Switzerland), vol. 17, no. 4, pp. 6–18, 2017.10.3390/s17040719Search in Google Scholar PubMed PubMed Central
[16] B.-F. Wu, P.-Y. Chen, and C.-H. Lin, “A new criterion of human comfort assessment for wheelchair robots by q-learning based accompanist tracking fuzzy controller,” Int. J. Fuzzy Syst., vol. 18, no. 6, pp. 1039–1053, 2016, https://doi.org/10.1007/s40815-015-0120-6.Search in Google Scholar
[17] E. Kim, “Wheelchair navigation system for disabled and elderly people,” Sensors (Basel, Switzerland), vol. 16, no. 11, p. 11, 2016.10.3390/s16111806Search in Google Scholar PubMed PubMed Central
[18] G. Jang, J. Kim, S. Lee, and Y. Choi, “Emg-based continuous control scheme with simple classifier for electric-powered wheelchair,” IEEE Trans. Ind. Electron., vol. 63, no. 6, pp. 3695–3705, 2016, https://doi.org/10.1109/tie.2016.2522385.Search in Google Scholar
[19] M. Eid, N. Giakoumidis, and A. El Saddik, “A novel eye-gaze-controlled wheelchair system for navigating unknown environments: case study with a person with als,” IEEE Access, vol. 4, pp. 558–573, 2016, https://doi.org/10.1109/access.2016.2520093.Search in Google Scholar
[20] J. Fu, M. Jones, and Y.-K. Jan, “Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: methodology and preliminary report,” J. Rehabil. Res. Dev., vol. 51, no. 5, pp. 775–788, 2014, https://doi.org/10.1682/jrrd.2013.09.0199.Search in Google Scholar PubMed
[21] T. R. Pingali, E. D. Lemaire, and N. Baddour, “Ultrasonic tethering to enable side-by-side following for powered wheelchairs,” Sensors, vol. 19, no. 1, p. 1, 2019.10.3390/s19010109Search in Google Scholar PubMed PubMed Central
[22] S. S. Abhishek Verma and J. Ramkumar, “Mapping wheelchair functions and their associated functional elements for stair climbing accessibility: a systematic review,” Disabil. Rehabil.: Assist. Technol., vol. 19, no. 1, pp. 200–221, 2024, https://doi.org/10.1080/17483107.2022.2075476.Search in Google Scholar PubMed
© 2025 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Methods
- Flachheitsanalyse nichtlinearer Systeme aus algebraischer Perspektive
- On using the output progression in unscented Kalman filtering
- Methodology for optimizing convolutional neural networks for fast production processes
- Skill-based multi-agent control for safe and effective human-robot collaboration
- Applications
- Advancements in intelligent wheelchairs: a scoping review
- Dissertations
- Industrie 4.0-angepasste Datenverkehrskonzepte für industrielle 5G-TSN-Netzwerke
- Modelling and Management of Wireless Communication Systems based on Digital Twins
Articles in the same Issue
- Frontmatter
- Methods
- Flachheitsanalyse nichtlinearer Systeme aus algebraischer Perspektive
- On using the output progression in unscented Kalman filtering
- Methodology for optimizing convolutional neural networks for fast production processes
- Skill-based multi-agent control for safe and effective human-robot collaboration
- Applications
- Advancements in intelligent wheelchairs: a scoping review
- Dissertations
- Industrie 4.0-angepasste Datenverkehrskonzepte für industrielle 5G-TSN-Netzwerke
- Modelling and Management of Wireless Communication Systems based on Digital Twins
