AIMC Topic: Adult

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Hybrid BCI-based instruction set for dual robotic arm control using EEG and eye movement signals.

Biomedical physics & engineering express
A brain-computer interface (BCI) establishes a pathway for information transmission between a human (or animal) and an external device. It can be used to control devices such as prosthetic limbs and robotic arms, which in turn assist, rehabilitate, a...

High-level locomotion intent estimation from electromyography and body posture.

Journal of neural engineering
Once we learn a reliable gait, we no longer have to consciously contract individual muscles to walk, or think about the fine-grained low-level control of our joints. Instead, we mainly make decisions on where we want to end up, at what pace and throu...

Lymphocytes and related inflammatory factors as predictors of metabolic syndrome risk in shift workers: A machine learning approach based on large-scale population data.

PloS one
BACKGROUND: Metabolic syndrome (MetS) is characterized by chronic inflammation and can be worsened by circadian disruption, which is common among shift work. Machine learning can predict the risk of MetS in shift workers using inflammatory biomarkers...

An Innovative Method for Refractory Epilepsy Diagnosis Based on Microstate Analysis and Graph Convolutional Network.

Journal of medical systems
This study systematically investigates the alterations in electroencephalogram (EEG) microstates in patients with refractory epilepsy(RE) across different seizure stages. A novel EEG microstate analysis framework is proposed to address the limitation...

Development and Validation of an Interpretable Hemodynamics-Based Machine Learning Model for Predicting Cerebral Arteriovenous Malformation Rupture.

Translational stroke research
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...

Enhanced machine learning and hybrid ensemble approaches for Coronary Heart Disease prediction.

PloS one
Coronary heart disease (CHD) remains the leading cause of mortality worldwide, disproportionately affecting low- and middle-income countries where diagnostic resources are limited. Traditional statistical models often fail to deliver adequate predict...

Just-In-Time Adaptive Interventions for Weight Management Among Adults With Excess Body Weight: Scoping Review.

Journal of medical Internet research
BACKGROUND: Just-in-time adaptive interventions (JITAIs) use real-time monitoring to deliver personalized support at optimal moments, demonstrating potential for improving lifestyle behaviors in weight management.

GenEEG: Improving epileptic EEG detection through patient-adaptive latent diffusion and continual learning.

Computers in biology and medicine
Automated seizure detection systems face significant challenges due to the limited availability of clinical EEG data, a substantial class imbalance between seizure and non-seizure recordings, considerable variability among patients, and the issue of ...

A heart rate variability-driven framework for depression screening leveraging emotion-elicited autonomic divergence.

Journal of physiological anthropology
OBJECTIVE: Depression manifests significant emotional dysregulation, characterized by heightened sadness susceptibility and attenuated happiness responsiveness in individuals with depression (IWD). This study employs structured emotion induction prot...