AI Medical Compendium Topic:
Stroke

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Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting.

Journal of medical Internet research
BACKGROUND: Smartphones contain sensors that measure movement-related data, making them promising tools for monitoring physical activity after a stroke. Activity recognition (AR) systems are typically trained on movement data from healthy individuals...

Effects of robot-assisted upper limb rehabilitation in stroke patients: a systematic review with meta-analysis.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Technology-supported training is emerging as a solution to support therapists in their efforts providing high-intensity, repetitive, and task-specific treatment, in order to enhance the recovery process. The aim of this review is to assess the effect...

An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images.

Computer methods and programs in biomedicine
OBJECTIVE: This paper presents a Radial Basis Functions Neural Network (RBFNN) based detection system, for automatic identification of Cerebral Vascular Accidents (CVA) through analysis of Computed Tomographic (CT) images.

Flexion synergy overshadows flexor spasticity during reaching in chronic moderate to severe hemiparetic stroke.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Pharmaceutical intervention targets arm flexor spasticity with an often-unsuccessful goal of improving function. Flexion synergy is a related motor impairment that may be inadvertently neglected. Here, flexor spasticity and flexion synergy...

Validity of Robot-Based Assessments of Upper Extremity Function.

Archives of physical medicine and rehabilitation
OBJECTIVE: To examine the validity of 5 robot-based assessments of arm motor function poststroke.

Novel Screening Tool for Stroke Using Artificial Neural Network.

Stroke
BACKGROUND AND PURPOSE: The timely diagnosis of stroke at the initial examination is extremely important given the disease morbidity and narrow time window for intervention. The goal of this study was to develop a supervised learning method to recogn...

Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients.

Journal of medical Internet research
BACKGROUND: The pronator drift test (PDT), a neurological examination, is widely used in clinics to measure motor weakness of stroke patients.

Quantification of task-dependent cortical activation evoked by robotic continuous wrist joint manipulation in chronic hemiparetic stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Cortical damage after stroke can drastically impair sensory and motor function of the upper limb, affecting the execution of activities of daily living and quality of life. Motor impairment after stroke has been thoroughly studied, howeve...

Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its co...

Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.

Stroke
BACKGROUND AND PURPOSE: This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulan...