AIMC Topic: Fatigue

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

Computers in biology and medicine Sep 6, 2021
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.
Biomechanical Phenomena Exercise Rotation Fatigue Humans Neural Networks, Computer
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Predicting Fatigue in Long Duration Mountain Events with a Single Sensor and Deep Learning Model.

Sensors (Basel, Switzerland) Aug 12, 2021
AIM: To determine whether an AI model and single sensor measuring acceleration and ECG could model cognitive and physical fatigue for a self-paced trail run.
Humans Neural Networks, Computer Deep Learning Walking Fatigue
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Neural and computational mechanisms of momentary fatigue and persistence in effort-based choice.

Nature communications Jul 28, 2021
From a gym workout, to deciding whether to persevere at work, many activities require us to persist in deciding that rewards are 'worth the effort' even as we become fatigued. However, studies examining effort-based decisions typically assume that th...
Frontal Lobe Choice Behavior Ventral Striatum Adult Brain Male Humans Female Magnetic Resonance Imaging Neural Networks, Computer Reward Adolescent Young Adult Decision Making Fatigue
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Determination of Bridge Prestress Loss under Fatigue Load Based on PSO-BP Neural Network.

Computational intelligence and neuroscience Jul 12, 2021
During the service period of a prestressed concrete bridge, as the number of cyclic loads increases, cumulative fatigue damage and prestress loss will occur inside the structure, which will affect the safety, durability, and service life of the struc...
Fatigue Humans Neural Networks, Computer Algorithms
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Factors to improve distress and fatigue in Cancer survivorship; further understanding through text analysis of interviews by machine learning.

BMC cancer Jun 27, 2021
BACKGROUND: From patient-reported surveys and individual interviews by health care providers, we attempted to identify the significant factors related to the improvement of distress and fatigue for cancer survivors by text analysis with machine learn...
Interview, Psychological Machine Learning Female Psychological Distress Humans Middle Aged Aged Surveys and Questionnaires Adult Fatigue Male Survivorship
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Pixel-Level Fatigue Crack Segmentation in Large-Scale Images of Steel Structures Using an Encoder-Decoder Network.

Sensors (Basel, Switzerland) Jun 16, 2021
Fatigue cracks are critical types of damage in steel structures due to repeated loads and distortion effects. Fatigue crack growth may lead to further structural failure and even induce collapse. Efficient and timely fatigue crack detection and segme...
Neural Networks, Computer Image Processing, Computer-Assisted Fatigue Steel Humans
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Soft pneumatic elbow exoskeleton reduces the muscle activity, metabolic cost and fatigue during holding and carrying of loads.

Scientific reports Jun 15, 2021
To minimize fatigue, sustain workloads, and reduce the risk of injuries, the exoskeleton Carry was developed. Carry combines a soft human-machine interface and soft pneumatic actuation to assist the elbow in load holding and carrying. We hypothesize ...
Exoskeleton Device Muscle Fatigue Gait Energy Metabolism Fatigue Electromyography Workload Walking Humans Robotics Elbow Biomechanical Phenomena Muscle, Skeletal
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Predicting anxiety in cancer survivors presenting to primary care - A machine learning approach accounting for physical comorbidity.

Cancer medicine Jun 2, 2021
BACKGROUND: The purpose of this study was to explore predictors for anxiety as the most common form of psychological distress in cancer survivors while accounting for physical comorbidity.
Stress, Psychological Primary Health Care Regression Analysis Predictive Value of Tests Middle Aged Anxiety Comorbidity Sleep Initiation and Maintenance Disorders Fatigue Cancer Pain Cancer Survivors Prostatic Neoplasms Colonic Neoplasms Supervised Machine Learning Humans Breast Neoplasms Male Female Aged Muscle Weakness
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A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data.

IEEE journal of biomedical and health informatics Apr 6, 2021
Multiple sclerosis (MS) affects the central nervous system with a wide range of symptoms. MS can, for example, cause pain, changes in mood and fatigue, and may impair a person's movement, speech and visual functions. Diagnosis of MS typically involve...
Multiple Sclerosis Fatigue Neural Networks, Computer Humans Deep Learning Smartphone
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Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences Jan 6, 2021
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...
Sleep Affect Physical Conditioning, Human Physical Exertion Football Motivation Soccer Myalgia Geographic Information Systems Cricket Sport Regression Analysis Humans Perception Decision Trees Surveys and Questionnaires Machine Learning Fatigue Stress, Psychological Sports Wearable Electronic Devices Health Status
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