AIMC Topic: Exercise

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Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach.

JMIR mHealth and uHealth
BACKGROUND: Mental health disorders affect multiple aspects of patients' lives, including mood, cognition, and behavior. eHealth and mobile health (mHealth) technologies enable rich sets of information to be collected noninvasively, representing a pr...

Out-of-Distribution Detection of Human Activity Recognition with Smartwatch Inertial Sensors.

Sensors (Basel, Switzerland)
Out-of-distribution (OOD) in the context of Human Activity Recognition (HAR) refers to data from activity classes that are not represented in the training data of a Machine Learning (ML) algorithm. OOD data are a challenge to classify accurately for ...

The potential of artificial intelligence in enhancing adult weight loss: a scoping review.

Public health nutrition
OBJECTIVE: To present an overview of how artificial intelligence (AI) could be used to regulate eating and dietary behaviours, exercise behaviours and weight loss.

On the Impact of Biceps Muscle Fatigue in Human Activity Recognition.

Sensors (Basel, Switzerland)
Nowadays, Human Activity Recognition (HAR) systems, which use wearables and smart systems, are a part of our daily life. Despite the abundance of literature in the area, little is known about the impact of muscle fatigue on these systems' performance...

The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining.

Frontiers in public health
Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of mul...

Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests.

European journal of sport science
The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and VT2) from cardiopulmonary exercise test (CPET) still leads to controversy. The reliability of the gold standard methodology (i.e. expert visual inspect...

Analyzing Description, User Understanding and Expectations of AI in Mobile Health Applications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Previous research has studied medical professionals' perception of artificial intelligence (AI). However, there has been a limited understanding of how healthcare consumers perceive and use AI-powered technologies such as mobile health apps. We colle...

Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Wrist accelerometers for assessing hallmark measures of physical activity (PA) are rapidly growing with the advent of smartwatch technology. Given the growing popularity of wrist-worn accelerometers, there needs to be a rigorous evaluation for recogn...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

Scientific reports
The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potenti...

Validity and precision of the International Physical Activity Questionnaire for climacteric women using computational intelligence techniques.

PloS one
This study aimed to evaluate the validity and precision of the International Physical Activity Questionnaire (IPAQ) for climacteric women using computational intelligence techniques. The instrument was applied to 873 women aged between 40 and 65 year...