2 papers
cs.LG2024
Objective Features Extracted from Motor Activity Time Series for Food Addiction Analysis Using Machine Learning -- A Pilot Study
Mikhail Borisenkov, Maksim Belyaev, Nithya Rekha Sivakumar +6
Wearable sensors and IoT/IoMT platforms enable continuous, real-time monitoring, but objective digital markers for eating disorders are limited. In this study, we examined whether…
eess.SP2023
Entropy-based machine learning model for diagnosis and monitoring of Parkinson's Disease in smart IoT environment
Maksim Belyaev, Murugappan Murugappan, Andrei Velichko +1
The study presents the concept of a computationally efficient machine learning (ML) model for diagnosing and monitoring Parkinson's disease (PD) in an Internet of Things (IoT) envi…