AIMC Topic: Exercise

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Deep Learning Approaches for Continuous Authentication Based on Activity Patterns Using Mobile Sensing.

Sensors (Basel, Switzerland)
Smartphones as ubiquitous gadgets are rapidly becoming more intelligent and context-aware as sensing, networking, and processing capabilities advance. These devices provide users with a comprehensive platform to undertake activities such as socializi...

Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach.

International journal of environmental research and public health
The increasing ubiquity of smartphone data, with greater spatial and temporal coverage than achieved by traditional study designs, have the potential to provide insight into habitual physical activity patterns. This study implements and evaluates the...

Predicting Physical Exercise Adherence in Fitness Apps Using a Deep Learning Approach.

International journal of environmental research and public health
The use of mobile fitness apps has been on the rise for the last decade and especially during the worldwide SARS-CoV-2 pandemic, which led to the closure of gyms and to reduced outdoor mobility. Fitness apps constitute a promising means for promoting...

Using Artificial Intelligence for the Construction of University Physical Training and Teaching Systems.

Journal of healthcare engineering
The combination of education and artificial intelligence is the developmental direction of future educational systems. Through the participation of artificial intelligence, an educational system with sensibility and computer rationality can be create...

Model-based data augmentation for user-independent fatigue estimation.

Computers in biology and medicine
OBJECTIVE: User-independent recognition of exercise-induced fatigue from wearable motion data is challenging, due to inter-participant variability. This study aims to develop algorithms that can accurately estimate fatigue during exercise.

Acceptability, usefulness, and satisfaction with a web-based video-tailored physical activity intervention: The TaylorActive randomized controlled trial.

Journal of sport and health science
PURPOSE: This study aimed to examine the usage, acceptability, usability, perceived usefulness, and satisfaction of a web-based video-tailored physical activity (PA) intervention (TaylorActive) in adults.

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

Annals of the New York Academy of Sciences
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 multisystem measurements from the Dongfeng-Tongji cohort were used ...

Deep Learning for Classifying Physical Activities from Accelerometer Data.

Sensors (Basel, Switzerland)
Physical inactivity increases the risk of many adverse health conditions, including the world's major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are mini...

Personalized Exercise Programs Based upon Remote Assessment of Motor Fitness: A Pilot Study among Healthy People Aged 65 Years and Older.

Gerontology
BACKGROUND: The World Health Organization has recently updated exercise guidelines for people aged >65 years, emphasizing the inclusion of multiple fitness components. However, without adequate recognition of individual differences, these guidelines ...