Identification of smartwatch-collected lifelog variables affecting body mass index in middle-aged people using regression machine learning algorithms and SHapley …

J Kim, J Lee, M Park - Applied Sciences, 2022 - mdpi.com
Body mass index (BMI) plays a vital role in determining the health of middle-aged people,
and a high BMI is associated with various chronic diseases. This study aims to identify …

MedAi: A smartwatch-based application framework for the prediction of common diseases using machine learning

ST Himi, NT Monalisa, MD Whaiduzzaman… - IEEE …, 2023 - ieeexplore.ieee.org
Health information technology is one of today's fastest-growing and most powerful
technologies. This technology is used predominantly for predicting illness and obtaining …

A machine learning–based biological aging prediction and its associations with healthy lifestyles: the Dongfeng–Tongji cohort

C Wang, X Guan, Y Bai, Y Feng, W Wei… - Annals of the New …, 2022 - Wiley Online Library
This study aims to establish a biological age (BA) predictor and to investigate the roles of
lifestyles on biological aging. The 14,848 participants with the available information of …

Building a cardiovascular disease prediction model for smartwatch users using machine learning: Based on the Korea national health and nutrition examination …

MJ Kim - Biosensors, 2021 - mdpi.com
Smartwatches have the potential to support health care in everyday life by supporting self-
monitoring of health conditions and personal activities. This paper aims to develop a model …

Motion-To-BMI: Using motion sensors to predict the body mass index of smartphone users

Y Yao, L Song, J Ye - Sensors, 2020 - mdpi.com
Obesity has become a widespread health problem worldwide. The body mass index (BMI) is
a simple and reliable index based on weight and height that is commonly used to identify …

[HTML][HTML] Explainable artificial intelligence and wearable sensor-based gait analysis to identify patients with osteopenia and sarcopenia in daily life

JK Kim, MN Bae, K Lee, JC Kim, SG Hong - Biosensors, 2022 - mdpi.com
Osteopenia and sarcopenia can cause various senile diseases and are key factors related
to the quality of life in old age. There is need for portable tools and methods that can analyze …

[HTML][HTML] Usability and accuracy of a smartwatch for the assessment of physical activity in the elderly population: observational study

M Martinato, G Lorenzoni, T Zanchi… - JMIR mHealth and …, 2021 - mhealth.jmir.org
Background Regular physical activity (PA) contributes to the primary and secondary
prevention of several chronic diseases and reduces the risk of premature death. Physical …

Age-specific risk factors for the prediction of obesity using a machine learning approach

J Jeon, S Lee, C Oh - Frontiers in Public Health, 2023 - frontiersin.org
Machine Learning is a powerful tool to discover hidden information and relationships in
various data-driven research fields. Obesity is an extremely complex topic, involving …

Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction

W Huang, TW Ying, WLC Chin, L Baskaran… - Scientific Reports, 2022 - nature.com
This study looked at novel data sources for cardiovascular risk prediction including detailed
lifestyle questionnaire and continuous blood pressure monitoring, using ensemble machine …

Accurate prediction of life style based disorders by smart healthcare using machine learning and prescriptive big data analytics

M Sharma, G Singh, R Singh - Data Intensive Computing …, 2018 - ebooks.iospress.nl
IT based healthcare industry is succeeding in leaps and bounds. Nowadays, the massive
volume and variety of healthcare data is available. Numbers of procedures have been …