An autonomous wheelchair with health monitoring system based on Internet of Thing
Abstract Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-56357-y |
| _version_ | 1797259363444850688 |
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| author | Lei Hou Jawwad Latif Pouyan Mehryar Stephen Withers Angelos Plastropoulos Linlin Shen Zulfiqur Ali |
| author_facet | Lei Hou Jawwad Latif Pouyan Mehryar Stephen Withers Angelos Plastropoulos Linlin Shen Zulfiqur Ali |
| author_sort | Lei Hou |
| collection | DOAJ |
| description | Abstract Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditions. This research proposes an autonomous wheelchair prototype system integrated with biophysical sensors based on Internet of Thing (IoT). A powered wheelchair system was developed with three biophysical sensors to collect, transmit and analysis users’ four vital signs to provide real-time feedback to users and clinicians. A user interface software embedded with the cloud artificial intelligence (AI) algorithms was developed for the data visualization and analysis. An improved data compression algorithm Minimalist, Adaptive and Streaming R-bit (O-MAS-R) was proposed to achieve a higher compression ratio with minimum 7.1%, maximum 45.25% compared with MAS algorithm during the data transmission. At the same time, the prototype wheelchair, accompanied with a smart-chair app, assimilates data from the onboard sensors and characteristics features within the surroundings in real-time to achieve the functions including obstruct laser scanning, autonomous localization, and point-to-point route planning and moving within a predefined area. In conclusion, the wheelchair prototype uses AI algorithms and navigation technology to help patients and elderly maintain their independent mobility and monitor their healthcare information in real-time. |
| first_indexed | 2024-04-24T23:08:14Z |
| format | Article |
| id | doaj.art-84c7b9257a474e9eb434ab48c12b8f21 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T23:08:14Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-84c7b9257a474e9eb434ab48c12b8f212024-03-17T12:23:25ZengNature PortfolioScientific Reports2045-23222024-03-0114111110.1038/s41598-024-56357-yAn autonomous wheelchair with health monitoring system based on Internet of ThingLei Hou0Jawwad Latif1Pouyan Mehryar2Stephen Withers3Angelos Plastropoulos4Linlin Shen5Zulfiqur Ali6Healthcare Innovation Centre, School of Health & Life Sciences, Teesside UniversityHealthcare Innovation Centre, School of Health & Life Sciences, Teesside UniversityHealthcare Innovation Centre, School of Health & Life Sciences, Teesside UniversityInnovative Technology and Science LtdInnovative Technology and Science LtdCollege of Computer Science and Software Engineering, Shenzhen UniversityHealthcare Innovation Centre, School of Health & Life Sciences, Teesside UniversityAbstract Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditions. This research proposes an autonomous wheelchair prototype system integrated with biophysical sensors based on Internet of Thing (IoT). A powered wheelchair system was developed with three biophysical sensors to collect, transmit and analysis users’ four vital signs to provide real-time feedback to users and clinicians. A user interface software embedded with the cloud artificial intelligence (AI) algorithms was developed for the data visualization and analysis. An improved data compression algorithm Minimalist, Adaptive and Streaming R-bit (O-MAS-R) was proposed to achieve a higher compression ratio with minimum 7.1%, maximum 45.25% compared with MAS algorithm during the data transmission. At the same time, the prototype wheelchair, accompanied with a smart-chair app, assimilates data from the onboard sensors and characteristics features within the surroundings in real-time to achieve the functions including obstruct laser scanning, autonomous localization, and point-to-point route planning and moving within a predefined area. In conclusion, the wheelchair prototype uses AI algorithms and navigation technology to help patients and elderly maintain their independent mobility and monitor their healthcare information in real-time.https://doi.org/10.1038/s41598-024-56357-yAutonomous drivingHealthcare monitoringInternet of ThingsSmart wheelchair |
| spellingShingle | Lei Hou Jawwad Latif Pouyan Mehryar Stephen Withers Angelos Plastropoulos Linlin Shen Zulfiqur Ali An autonomous wheelchair with health monitoring system based on Internet of Thing Scientific Reports Autonomous driving Healthcare monitoring Internet of Things Smart wheelchair |
| title | An autonomous wheelchair with health monitoring system based on Internet of Thing |
| title_full | An autonomous wheelchair with health monitoring system based on Internet of Thing |
| title_fullStr | An autonomous wheelchair with health monitoring system based on Internet of Thing |
| title_full_unstemmed | An autonomous wheelchair with health monitoring system based on Internet of Thing |
| title_short | An autonomous wheelchair with health monitoring system based on Internet of Thing |
| title_sort | autonomous wheelchair with health monitoring system based on internet of thing |
| topic | Autonomous driving Healthcare monitoring Internet of Things Smart wheelchair |
| url | https://doi.org/10.1038/s41598-024-56357-y |
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