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Internet of Sensing Things-Based Machine Learning Approach to Predict Parkinson

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dc.contributor.author Afroz, Sohana
dc.contributor.author Ullah Akhund, Tajim Md. Niamat
dc.contributor.author Khan, Tarikuzzaman
dc.contributor.author Hasan, Md. Umaid
dc.contributor.author Jesmin, Rashida
dc.contributor.author Sarker, M. Mesbahuddin
dc.date.accessioned 2026-04-05T04:26:10Z
dc.date.available 2026-04-05T04:26:10Z
dc.date.issued 2023-09-15
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/16563
dc.description Conference Paper en_US
dc.description.abstract With the help of the Internet of things, therapeutic science has progressed surprisingly. Lots of elderly individuals are affected by Parkinson’s disease. This work proposed an Internet of sensing things-based system to collect data from Parkinson’s affected people analyze the collected data in a cloud server with machine learning algorithms and predict the condition of the patient. Multiple types of sensors are used and tested. Micro-controllers are used to collect data from sensors and send them to a cloud server. Then, multiple machine learning algorithms are used to predict the patient’s condition. Results between several methods are also compared. en_US
dc.language.iso en_US en_US
dc.subject Internet of things (IoT) en_US
dc.subject Parkinson prediction en_US
dc.subject Internet of sensing things (IoST) en_US
dc.subject Machine learning (ML) en_US
dc.subject Neurodegenerative disorder (NDD) en_US
dc.title Internet of Sensing Things-Based Machine Learning Approach to Predict Parkinson en_US
dc.type Other en_US


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