THE APPLICATION OF MACHINE LEARNING ON THE SENSORS OF SMARTPHONES TO DETECT FALLS IN REAL-TIME
Achraf Benba
achraf.benba@um5s.net.maMohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies (Morocco)
https://orcid.org/0000-0001-7939-0790
Mouna Akki
Mohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies (Morocco)
http://orcid.org/0009-0001-8532-1158
Sara Sandabad
Hassan II University of Casablanca, Ecole Normale Supérieure de l'Enseignement Technique de Mohammadia, Electrical Engineering and Intelligent Systems (Morocco)
http://orcid.org/0000-0002-0813-6178
Abstract
With the increasing prevalence of smartphones, they now come equipped with a multitude of sensors such as GPS, microphones, cameras, magnetometers, accelerators, and more, which can simplify our daily lives. When it comes to healthcare, smartphones can become indispensable. The detection of geriatric falls is crucial as even the slightest injury can have fatal consequences. Therefore, we proposed the use of accelerometers in our research to detect falls in the elderly. Our project involved the development of an automated, continuous, and reliable monitoring system that would generate a list of elderly people at risk of falling and present it on a webpage for emergency services. This approach aimed to minimize the long-term impacts and save lives promptly. We started by developing a mobile application and used MATLAB to classify the falls as either "fall" or "not fall." Finally, we created a webpage that would facilitate communication between the mobile application and MATLAB.
Keywords:
fall detection, smartphone accelerometers, SVM, KNN, machine learningReferences
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Authors
Achraf Benbaachraf.benba@um5s.net.ma
Mohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies Morocco
https://orcid.org/0000-0001-7939-0790
Authors
Mouna AkkiMohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies Morocco
http://orcid.org/0009-0001-8532-1158
Authors
Sara SandabadHassan II University of Casablanca, Ecole Normale Supérieure de l'Enseignement Technique de Mohammadia, Electrical Engineering and Intelligent Systems Morocco
http://orcid.org/0000-0002-0813-6178
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