Neurology

"She Had a Smile on Her Face as Wide as the Great Australian Bite": A Qualitative Examination of Family Perceptions of a Therapeutic Robot and a Plush Toy.

BACKGROUND AND OBJECTIVES: Recent years have seen social robotic pets introduced as a means of treating behavioral and psychological symptoms of dementia, and many show promising potential. In this study, we sought to explore family members' perceptions of the Japanese-developed baby harp seal, Paro (version 9), and a look-alike, nonrobotic Plush Toy, when used by their relative with dementia for ...

The State of Nanorobotics in Medicine.

From ant-man to the Incredible Shrinking Machine, society has long envisioned developing devices tiny enough to enter human cells. Such nanotechnology could revolutionize the diagnosis of diseases like cancer and neurodegeneration, span new methods of precise drug delivery, and even directly repair damaged organs.

Feasibility of an Electromyography-Triggered Hand Robot for People After Chronic Stroke.

IMPORTANCE: Effective treatment of the affected hand after stroke is crucial for improved functional independence and recovery.

The Decision Decoding ToolBOX (DDTBOX) - A Multivariate Pattern Analysis Toolbox for Event-Related Potentials.

In recent years, neuroimaging research in cognitive neuroscience has increasingly used multivariate pattern analysis (MVPA) to investigate higher cogn...

Using Deep Learning Algorithms to Automatically Identify the Brain MRI Contrast: Implications for Managing Large Databases.

Neuroimaging science has seen a recent explosion in dataset size driving the need to develop database management with efficient processing pipelines. ...

A Multi-View Deep Learning Framework for EEG Seizure Detection.

The recent advances in pervasive sensing technologies have enabled us to monitor and analyze the multi-channel electroencephalogram (EEG) signals of e...

[Artificial Intelligence in Psychiatry].

Diagnosis of psychiatric disorders is based primarily on subjective symptoms, and neuroimaging or other biological examinations are used for excluding...

Fusion of WPT and MFCC feature extraction in Parkinson's disease diagnosis.

BACKGROUND: Parkinson's disease (PD) is a neurological disorder, progressive in nature. In order to provide customized patient care, diagnosis and mon...

Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder affecting 1 in 59 children. While noncoding genetic variation has been shown...

Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolution Neural Network.

Automated emotion recognition plays a vital role in problem solving, decision making and social activities of human life. An emotion is a set of react...

Machine Learning Algorithm Helps Identify Non-Diagnosed Prodromal Alzheimer's Disease Patients in the General Population.

BACKGROUND: Recruiting patients for clinical trials of potential therapies for Alzheimer's disease (AD) remains a major challenge, with demand for tri...

Improvement of motor performance in children with cerebral palsy treated with exoskeleton robotic training: A retrospective explorative analysis.

BACKGROUND: Robot-assisted gait training (RAGT) is widely used in children with cerebral palsy (CP), but information about optimal intervention freque...

Fuzzy Classification Methods Based Diagnosis of Parkinson's disease from Speech Test Cases.

BACKGROUND: Together with the Alzheimer's disease, Parkinson's disease is considered as one of the two serious known neurodegenerative diseases. Physi...

Implementation of Bagged SVM Ensemble Model for Classification of Epileptic States Using EEG.

BACKGROUND: To decipher EEG (Electroencephalography), intending to locate inter-ictal and ictal discharges for supporting the diagnoses of epilepsy an...

Detecting Alzheimer's Disease from Continuous Speech Using Language Models.

BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling...

Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.

Machine learning (ML) algorithms have found increasing utility in the medical imaging field and numerous applications in the analysis of digital bioma...

Validation of a robot serious game assessment protocol for upper limb motor impairment in children with cerebral palsy.

BACKGROUND: The ROBiGAME project aims to implement serious games on robots to rehabilitate upper limb (UL) motor function in children with cerebral pa...

Efficacy of end-effector Robot-Assisted Gait Training in subacute stroke patients: Clinical and gait outcomes from a pilot bi-centre study.

BACKGROUND: End-effector robots allow intensive gait training in stroke subjects and promote a successful rehabilitation. A comparison between convent...

Screening for Alzheimer's Disease Using Saliva: A New Approach Based on Machine Learning and Raman Hyperspectroscopy.

BACKGROUND: Alzheimer's disease and related dementias (ADRDs) are being diagnosed at epidemic rates, with incidence to triple from 35 to 115 million c...

Volumetric Histogram-Based Alzheimer's Disease Detection Using Support Vector Machine.

In this research work, machine learning techniques are used to classify magnetic resonance imaging brain scans of people with Alzheimer's disease. Thi...