Smart Health System to Detect Dementia Disorders Using Virtual Reality
Smart health technology includes physical sensors, intelligent sensors, and output advice to help monitor patients’ health and adjust their behavior. Virtual reality (VR) plays an increasingly larger role to improve health outcomes, being used in a variety of medical specialties including robotic su...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Healthcare |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9032/9/7/810 |
| _version_ | 1797411666884820992 |
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| author | Areej Y. Bayahya Wadee Alhalabi Sultan H. AlAmri |
| author_facet | Areej Y. Bayahya Wadee Alhalabi Sultan H. AlAmri |
| author_sort | Areej Y. Bayahya |
| collection | DOAJ |
| description | Smart health technology includes physical sensors, intelligent sensors, and output advice to help monitor patients’ health and adjust their behavior. Virtual reality (VR) plays an increasingly larger role to improve health outcomes, being used in a variety of medical specialties including robotic surgery, diagnosis of some difficult diseases, and virtual reality pain distraction for severe burn patients. Smart VR health technology acts as a decision support system in the diseases diagnostic test of patients as they perform real world tasks in virtual reality (e.g., navigation). In this study, a non-invasive, cognitive computerized test based on 3D virtual environments for detecting the main symptoms of dementia (memory loss, visuospatial defects, and spatial navigation) is proposed. In a recent study, the system was tested on 115 real patients of which thirty had a dementia, sixty-five were cognitively healthy, and twenty had a mild cognitive impairment (MCI). The performance of the VR system was compared with Mini-Cog test, where the latter is used to measure cognitive impaired patients in the traditional diagnosis system at the clinic. It was observed that visuospatial and memory recall scores in both clinical diagnosis and VR system of dementia patients were less than those of MCI patients, and the scores of MCI patients were less than those of the control group. Furthermore, there is a perfect agreement between the standard methods in functional evaluation and navigational ability in our system where P-value in weighted Kappa statistic= 100% and between Mini-Cog-clinical diagnosis vs. VR scores where P-value in weighted Kappa statistic= 93%. |
| first_indexed | 2024-03-09T04:49:27Z |
| format | Article |
| id | doaj.art-03b3619c5ab7441e80bf4f1fff177dfd |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T04:49:27Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-03b3619c5ab7441e80bf4f1fff177dfd2023-12-03T13:11:28ZengMDPI AGHealthcare2227-90322021-06-019781010.3390/healthcare9070810Smart Health System to Detect Dementia Disorders Using Virtual RealityAreej Y. Bayahya0Wadee Alhalabi1Sultan H. AlAmri2Department of Computer Science, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Computer Science, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Family Medicine, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSmart health technology includes physical sensors, intelligent sensors, and output advice to help monitor patients’ health and adjust their behavior. Virtual reality (VR) plays an increasingly larger role to improve health outcomes, being used in a variety of medical specialties including robotic surgery, diagnosis of some difficult diseases, and virtual reality pain distraction for severe burn patients. Smart VR health technology acts as a decision support system in the diseases diagnostic test of patients as they perform real world tasks in virtual reality (e.g., navigation). In this study, a non-invasive, cognitive computerized test based on 3D virtual environments for detecting the main symptoms of dementia (memory loss, visuospatial defects, and spatial navigation) is proposed. In a recent study, the system was tested on 115 real patients of which thirty had a dementia, sixty-five were cognitively healthy, and twenty had a mild cognitive impairment (MCI). The performance of the VR system was compared with Mini-Cog test, where the latter is used to measure cognitive impaired patients in the traditional diagnosis system at the clinic. It was observed that visuospatial and memory recall scores in both clinical diagnosis and VR system of dementia patients were less than those of MCI patients, and the scores of MCI patients were less than those of the control group. Furthermore, there is a perfect agreement between the standard methods in functional evaluation and navigational ability in our system where P-value in weighted Kappa statistic= 100% and between Mini-Cog-clinical diagnosis vs. VR scores where P-value in weighted Kappa statistic= 93%.https://www.mdpi.com/2227-9032/9/7/810virtual realitysmart healthdementiageriatric medicinevisuospatialmemory |
| spellingShingle | Areej Y. Bayahya Wadee Alhalabi Sultan H. AlAmri Smart Health System to Detect Dementia Disorders Using Virtual Reality Healthcare virtual reality smart health dementia geriatric medicine visuospatial memory |
| title | Smart Health System to Detect Dementia Disorders Using Virtual Reality |
| title_full | Smart Health System to Detect Dementia Disorders Using Virtual Reality |
| title_fullStr | Smart Health System to Detect Dementia Disorders Using Virtual Reality |
| title_full_unstemmed | Smart Health System to Detect Dementia Disorders Using Virtual Reality |
| title_short | Smart Health System to Detect Dementia Disorders Using Virtual Reality |
| title_sort | smart health system to detect dementia disorders using virtual reality |
| topic | virtual reality smart health dementia geriatric medicine visuospatial memory |
| url | https://www.mdpi.com/2227-9032/9/7/810 |
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