Research Article
CURA: Real Time Artificial Intelligence and IoT based Fall Detection Systems for patients suffering from Dementia
@ARTICLE{10.4108/eetpht.9.3967, author={Sanket Mishra and Bernard Ngangbam and Shritik Raj and Nihar Ranjan Pradhan}, title={CURA: Real Time Artificial Intelligence and IoT based Fall Detection Systems for patients suffering from Dementia}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={9}, number={1}, publisher={EAI}, journal_a={PHAT}, year={2023}, month={9}, keywords={Fall Detection, Accelerometer, Gyroscope, Sliding Window, Timeframe, Classification, Alert, False Alarm}, doi={10.4108/eetpht.9.3967} }- Sanket Mishra
Bernard Ngangbam
Shritik Raj
Nihar Ranjan Pradhan
Year: 2023
CURA: Real Time Artificial Intelligence and IoT based Fall Detection Systems for patients suffering from Dementia
PHAT
EAI
DOI: 10.4108/eetpht.9.3967
Abstract
According to the rising concern of the effects on the families due to dementia suffering patients, we aim to provide caretakers a work-life balance in which monitoring can be done with much more ease and efficiency in real time. This device can also be used in old age homes as well as hospitals which reduces the workload of the caretakers and helps them to easily monitor the patients. We aim to contribute for the betterment of the society and provide a virtual assistance for the patients suffering from dementia. The number of elderly people living alone has been increasing all over the world. If dementia has been detected at an early stage, the progress of disease can be slowed. The patients suffering from dementia are prone to falling quite frequently so as to detect that and to alert their caretakers to take necessary actions. In this study, we proposed a system in which we detect the real time state of the elderly people living alone by using the Machine Learning and IoT (Internet of Things) technology.We installed sensors inside a finger strap which is attached to the person. These sensors can detect the motions of the patient and predict their real time state to have a 24 by 7 support to provide assistance to the patients.
Copyright © 2023 S. Mishra et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
