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Fatigue

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Multilevel attention mechanism for motion fatigue recognition based on sEMG and ACC signal fusion.

PloS one
This study aims to develop a cost-effective and reliable motion monitoring device capable of comprehensive fatigue analysis. It achieves this objective by integrating surface electromyography (sEMG) and accelerometer (ACC) signals through a feature f...

Research on low-power driving fatigue monitoring method based on spiking neural network.

Experimental brain research
Fatigue driving is one of the leading causes of traffic accidents, and the rapid and accurate detection of driver fatigue is of paramount importance for enhancing road safety. However, the application of deep learning models in fatigue driving detect...

Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.

BMC gastroenterology
PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defecation. The condition is classified as a disorder of the gut-brain interaction (DGBI), and patients w...

Automatic Detection of Fatigued Gait Patterns in Older Adults: An Intelligent Portable Device Integrating Force and Inertial Measurements with Machine Learning.

Annals of biomedical engineering
PURPOSE: This study aimed to assess the feasibility of early detection of fatigued gait patterns for older adults through the development of a smart portable device.

Development and validation of machine learning models for predicting cancer-related fatigue in lymphoma survivors.

International journal of medical informatics
BACKGROUND: New cases of lymphoma are rising, and the symptom burden, like cancer-related fatigue (CRF), severely impacts the quality of life of lymphoma survivors. However, clinical diagnosis and treatment of CRF are inadequate and require enhanceme...

Risk factors for depression in China based on machine learning algorithms: A cross-sectional survey of 264,557 non-manual workers.

Journal of affective disorders
BACKGROUND: Factors related to depression differ depending on the population studied, and studies focusing on the population of non-manual workers are lacking. Thus, we aimed to identify the risk factors related to depression in non-manual workers in...

Research on fatigue detection of flight trainees based on face EMF feature model combination with PSO-CNN algorithm.

Scientific reports
Even though the capability of aircraft manufacturing has improved, human factors still play a pivotal role in flight accidents. For example, fatigue-related accidents are a common factor in human-led accidents. Hence, pilots' precise fatigue detectio...

Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection.

Sensors (Basel, Switzerland)
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and ...

Real-Time Fatigue Detection Algorithms Using Machine Learning for Yawning and Eye State.

Sensors (Basel, Switzerland)
Drowsiness while driving is a major factor contributing to traffic accidents, resulting in reduced cognitive performance and increased risk. This article gives a complete analysis of a real-time, non-intrusive sleepiness detection system based on con...

Application of Additive Manufacturing and Deep Learning in Exercise State Discrimination.

Sensors (Basel, Switzerland)
With the rapid development of sports technology, smart wearable devices play a crucial role in athletic training and health management. Sports fatigue is a key factor affecting athletic performance. Using smart wearable devices to detect the onset of...