Latest AI and machine learning research in neurology for healthcare professionals.
With advancing technology, human assistive robots have been developed to enhance daily efficiency for users. Focusing on the reaching motions of the upper limb, this study aims to propose a motion classification method based on electromyographic (EMG) signals that can accurately and promptly differentiate among three distinct types of reaching motion-regular reaching, extended reaching, and weight...
Wearable technologies have been demonstrated to have value in the objective assessment of Parkinson's disease. However, certain symptoms such as freezing of gait are challenging to monitor using current approaches. Data augmentation, wherein synthetic or simulated data is added to real world training sets to increase their size and diversity, has emerged as an approach to bolster the accuracy of m...
In dementia, particularly Alzheimer's Disease (AD), communication challenges are evident, especially in vocabulary and pragmatic aspects. Affected ind...
The importance of early Alzheimer's Disease screening is becoming more apparent, given the fact that there is no way to revert the patient's status af...
Due to inter-subject variability in electroencephalogram (EEG) signals, the generalization ability of many existing brain-computer interface (BCI) mod...
In this paper, we present a robotic walker that aims to encourage the patient's voluntary movement by enabling intention-based control of the mobile b...
Robot-assisted surgical systems have shown promising results and better patient outcomes in pedicle screw instrumentation and percutaneous needle inte...
Neurodevelopmental disorders (NDDs) have arisen as one of the most prevailing chronic diseases within the US. Often associated with severe adverse i...
This paper presents a sensorized vision-enabled prosthetic hand aimed at replicating a natural hand's performance, functionality, appearance, and co...
Severe impairment of the central motor network can result in loss of motor function, clinically recognized as Locked-in Syndrome. Advances in Brain-...
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder. Due to the subtlety of symptoms in the early stages of AD, rapid and accurate cl...
Dementia is a mental illness that people live with all across the world. No one is immune. Nothing can predict its onset. The true story of dementia...
Background: Any treatment of multiple sclerosis should preserve mental function, considering how cognitive deterioration interferes with quality of ...
Omics data analysis is crucial for studying complex diseases, but its high dimensionality and heterogeneity challenge classical statistical and mach...
\textbf{Objective:} Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as Mild Cognitiv...
Neural networks, whice have had a profound effect on how researchers study complex phenomena, do so through a complex, nonlinear mathematical struct...
Closed-loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the ...
The burgeoning field of brain health research increasingly leverages artificial intelligence (AI) to interpret and analyze neurological data. This s...
Identifying and reconstructing what we see from brain activity gives us a special insight into investigating how the biological visual system repres...
Glaucoma is a chronic eye disease characterized by optic neuropathy, leading to irreversible vision loss. It progresses gradually, often remaining u...