Latest AI and machine learning research in neurology for healthcare professionals.
Powered robotic exoskeletons are an emerging technology of wearable orthoses that can be used as an assistive device to enable non-ambulatory individuals with spinal cord injury (SCI) to walk, or as a rehabilitation tool to improve walking ability in ambulatory individuals with SCI. No studies to date have systematically reviewed the literature on the efficacy of powered exoskeletons on restoring ...
We developed a machine learning methodology for automatic sleep stage scoring. Our time-frequency analysis-based feature extraction is fine-tuned to capture sleep stage-specific signal features as described in the American Academy of Sleep Medicine manual that the human experts follow. We used ensemble learning with an ensemble of stacked sparse autoencoders for classifying the sleep stages. We us...
Insect wing shapes are diverse and a renowned source of inspiration for the new generation of autonomous flapping vehicles, yet the aerodynamic conseq...
BACKGROUND: Assistive and robotic training devices are increasingly used for rehabilitation of the hemiparetic arm after stroke, although applications...
Background While recent clinical trials involving robot-assisted therapy have failed to show clinically significant improvement versus conventional th...
INTRODUCTION: Guidelines for the use of cerebrospinal fluid (CSF) biomarkers in the diagnosis of Alzheimer's disease (AD) establish that each laborato...
Flexible tactile sensors capable of detecting the magnitude and direction of the applied force together are of great interest for application in human...
Early and accurate diagnosis of Parkinson's disease (PD) remains challenging. Neuropathological studies using brain bank specimens have estimated that...
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms have been proposed in recent years, one of which is sampl...
Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicat...
BACKGROUND: Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechani...
Correct assessment of bradykinesia is a key element in the diagnosis and monitoring of Parkinson's disease. Its evaluation is based on a careful asses...
Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of ...
Robot-mediated therapy can help improve walking ability in patients following injuries to the central nervous system. However, the efficacy of this tr...
The different discrete transform techniques such as discrete cosine transform (DCT), discrete sine transform (DST), discrete wavelet transform (DWT), ...
Automatic seizure detection has played an important role in the monitoring, diagnosis and treatment of epilepsy. In this paper, a patient specific met...
The study of engagement in people with dementia is important to determine the effectiveness of interventions that aim to promote meaningful activity. ...
BACKGROUND AND PURPOSE: Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid ...
Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurologic...
BACKGROUND: Better diagnostic and prognostic tools are needed to address issues related to early diagnosis and management of concussion across the con...