Latest AI and machine learning research in strokes for healthcare professionals.
Advances in predictive analytics and machine learning supported by an ever-increasing wealth of data...
PURPOSE: Previous studies have suggested that upper limb rehabilitation using therapeutic robots imp...
BACKGROUND: Upper-limb robotic-assisted therapy (RAT) is promising for stroke rehabilitation, partic...
The hand extension robot orthosis (HERO) glove was iteratively designed with occupational therapists...
OBJECTIVE: To compare the activity and fatigue of upper extremity muscles, pain levels, subject sati...
BACKGROUND: New technologies to improve post-stroke rehabilitation outcomes are of great interest an...
This study aims to analyse the long-term effects (6 months follow-up) of upper limb Robot-assisted T...
BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research ...
Early detection of Atrial Fibrillation (AFib) is crucial to prevent stroke recurrence. New tools for...
BACKGROUND: In a clinical setting, an individual subject classification model rather than a group an...
BACKGROUND: Stroke is one of the most common diseases that cause mortality. Detecting the risk of st...
Explainable artificial intelligence (AI) is attracting much interest in medicine. Technically, the p...
OBJECTIVE: To identify the rehabilitative effects of robot-assisted therapy on balance function amon...
BACKGROUND: Intensive robot-assisted training of the upper limb after stroke can reduce motor impair...
BACKGROUND: Intelligent decision support systems (IDSS) have been applied to tasks of disease manage...
This study examined the treatment effects between unilateral hybrid therapy (UHT; unilateral robot-a...
BACKGROUND AND PURPOSE: This project assessed performance of natural language processing (NLP) and m...
Current clinical practice relies on clinical history to determine the time since stroke (TSS) onset....
Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment...
During robot-aided motion rehabilitation training, inappropriate difficulty of the training task usu...
In this paper, we present a deep learning framework "Rehab-Net" for effectively classifying three up...