The rise in online interactions has introduced multiple challenges, including confusion during virtual meetings and fatigue associated with prolonged video conferencing. To address these issues, this study advocates using computer graphics (CG) avata...
The selection of the most efficient actuator for biohybrid robots necessitates the implementation of precise and reliable decision-making (DM) methods. Dynamic aggregation operators (AOs) provide flexibility and consistency in DM by embracing time-de...
This study evaluated the discriminative potential of a machine learning model using movement features during functional tasks to distinguish between patients with non-traumatic chronic neck pain and asymptomatic controls. The study included patients ...
The importance of using Brain-Computer Interface (BCI) systems based on electro encephalography (EEG) signal to decode Motor Imagery(MI) is very impressive because of the possibility of analyzing and translating brain signals related to movement inte...
The gradual research in integrating artificial intelligence in the Dielectrophoresis system is rapid since the evolution of AI in every aspect of technology since the early 2020s. The benefits of AI integration into DEP systems include improving posi...
BACKGROUND: The integration of machine learning and deep learning methodologies has transformed data analytics in biomechanics. However, the field faces challenges such as limited large-scale data sets, high data acquisition costs, and restricted par...
Brain-machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by 'decoding' neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studi...
Body movements and posture provide valuable insights into stress responses, yet their relationship with endocrine biomarkers of the stress response remains underexplored. This study investigates whether movement patterns during the Trier Social Stres...
OBJECTIVE: The therapeutic management of neoplasm employs high level energy beam to ablate malignant cells, which can cause collateral damage to adjacent normal tissue. Furthermore, respiration-induced organ motion, during radiotherapy can lead to si...
Applying machine learning algorithms to physical signals is always challenging since undesirable events can occur when signals are acquired outside a controlled environment. Among several applications, movement recognition through sEMG signals is esp...
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