AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Exercise

Showing 131 to 140 of 311 articles

Clear Filters

Energy Expenditure Estimation of Tabata by Combining Acceleration and Heart Rate.

Frontiers in public health
Tabata training plays an important role in health promotion. Effective monitoring of exercise energy expenditure is an important basis for exercisers to adjust their physical activities to achieve exercise goals. The input of acceleration combined wi...

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

Scientific reports
This study looked at novel data sources for cardiovascular risk prediction including detailed lifestyle questionnaire and continuous blood pressure monitoring, using ensemble machine learning algorithms (MLAs). The reference conventional risk score c...

Pruning Growing Self-Organizing Map Network for Human Physical Activity Identification.

Journal of healthcare engineering
Human physical activity identification based on wearable sensors is of great significance to human health analysis. A large number of machine learning models have been applied to human physical activity identification and achieved remarkable results....

Advanced Compliant Anti-Gravity Robot System for Lumbar Stabilization Exercise Using Series Elastic Actuator.

IEEE journal of translational engineering in health and medicine
: The lumbar stabilization exercise is one of the most recommended treatments in medical professionals for patients suffering from low back pain. However, because lumbar stabilization exercise is calisthenics, it is challenging to perform because of ...

A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss.

The international journal of behavioral nutrition and physical activity
BACKGROUND: This systematic review aimed to evaluate AI chatbot characteristics, functions, and core conversational capacities and investigate whether AI chatbot interventions were effective in changing physical activity, healthy eating, weight manag...

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...