AIMC Topic: Fatigue

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Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Human factors are important contributors to accidents, especially human error induced by fatigue. In this study, field tests and analyses were conducted on physiological indexes extracted from electrocardiography (ECG) and e...

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.

Predicting Fatigue in Long Duration Mountain Events with a Single Sensor and Deep Learning Model.

Sensors (Basel, Switzerland)
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.

Neural and computational mechanisms of momentary fatigue and persistence in effort-based choice.

Nature communications
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...

Determination of Bridge Prestress Loss under Fatigue Load Based on PSO-BP Neural Network.

Computational intelligence and neuroscience
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...

Factors to improve distress and fatigue in Cancer survivorship; further understanding through text analysis of interviews by machine learning.

BMC cancer
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...

Pixel-Level Fatigue Crack Segmentation in Large-Scale Images of Steel Structures Using an Encoder-Decoder Network.

Sensors (Basel, Switzerland)
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...

Soft pneumatic elbow exoskeleton reduces the muscle activity, metabolic cost and fatigue during holding and carrying of loads.

Scientific reports
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 ...

A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data.

IEEE journal of biomedical and health informatics
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...