Related papers: An Exercise Fatigue Detection Model Based on Machi…
The utilization of digital health has increased recently, and these services provide extensive guidance to encourage users to exercise frequently by setting daily exercise goals to promote a healthy lifestyle. These comprehensive guides…
Driver fatigue is a major cause of traffic accidents and the electroencephalogram (EEG) is considered one of the most reliable predictors of fatigue. This paper proposes a novel, simple and fast method for driver fatigue detection that can…
This study introduces a novel muscle activation analysis based on surface electromyography (sEMG) signals to assess the muscle's after-fatigue condition. Previous studies have mainly focused on the before-fatigue and fatigue conditions.…
A new model is presented to predict hydrogen-assisted fatigue. The model combines a phase field description of fracture and fatigue, stress-assisted hydrogen diffusion, and a toughness degradation formulation with cyclic and hydrogen…
The surface electromyography (sEMG) analysis can provide information on muscle fatigue status by estimation of muscle fibre conduction velocity (MFCV), a measure of the travelling speed of motor unit action potentials in muscle tissue. This…
Electroencephalogram (EEG) has become increasingly popular in driver fatigue monitoring systems. Several decomposition methods have been attempted to analyze the EEG signals that are complex, nonlinear and non-stationary and improve the EEG…
Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the…
The prediction of system responses for a given fatigue test bench drive signal is a challenging task, for which linear frequency response function models are commonly used. To account for non-linear phenomena, a novel hybrid model is…
Repetitive tasks in industrial works may contribute to health problems among operators, such as musculo-skeletal disorders, in part due to insufficient control of muscle fatigue. In this paper, a predictive model of fatigue is proposed for…
The ubiquitous availability of wearable sensors is responsible for driving the Internet-of-Things but is also making an impact on sport sciences and precision medicine. While human activity recognition from smartphone data or other types of…
We present a new theoretical and numerical phase field-based formulation for predicting hydrogen-assisted fatigue. The coupled deformation-diffusion-damage model presented enables predicting fatigue crack nucleation and growth for arbitrary…
In precision sports such as archery, athletes' performance depends on both biomechanical stability and psychological resilience. Traditional motion analysis systems are often expensive and intrusive, limiting their use in natural training…
This work presents an efficient algorithmic framework for real-time identification, classification, and evaluation of human physiotherapy exercises using mobile devices. The proposed method interprets a kinetic movement as a sequence of…
The complexities of fatigue have drawn much attention from researchers across various disciplines. Short-term fatigue may cause safety issue while driving; thus, dynamic systems were designed to track driver fatigue. Long-term fatigue could…
Machine learning as a data-driven solution has been widely applied in the field of fatigue lifetime prediction. In this paper, three models for wideband fatigue life prediction are built based on three machine learning models, i.e. support…
To enhance the intelligence degree in operation and maintenance, a novel method for fault detection in power grids is proposed. The proposed GNN-based approach first identifies fault nodes through a specialized feature extraction method…
This paper investigates deteriorations in knee and ankle dynamics during running. Changes in lower limb accelerations are analyzed by a wearable musculo-skeletal monitoring system. The system employs a machine learning technique to classify…
Cumulative local muscle fatigue may lead to potential musculoskeletal disorder (MSD) risks {\color{red}, and subject-specific muscle fatigability needs to be considered to reduce potential MSD risks.} This study was conducted to determine…
The assessment of energy expenditure in real life is of great importance for monitoring the current physical state of people, especially in work, sport, elderly care, health care, and everyday life even. This work reports about application…
Monitoring physical exercises is vital for health promotion, with automated systems becoming standard in personal health surveillance. However, sensor placement variability and unconstrained movements limit their effectiveness. This study…