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Multiple Sclerosis

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Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection.

Investigative radiology
OBJECTIVES: The aim of the study was to implement a deep-learning tool to produce synthetic double inversion recovery (synthDIR) images and compare their diagnostic performance to conventional sequences in patients with multiple sclerosis (MS).

Factors affecting the usability of an assistive soft robotic glove after stroke or multiple sclerosis.

Journal of rehabilitation medicine
OBJECTIVE: To explore the usability and effects of an assistive soft robotic glove in the home setting after stroke or multiple sclerosis.

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry.

Brain imaging and behavior
Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). To determine whether pattern class...

Beyond therapists: Technology-aided physical MS rehabilitation delivery.

Multiple sclerosis (Houndmills, Basingstoke, England)
In the last decade, rehabilitation technology has been developed, investigated, and entered specialized clinical settings. In this chapter, we first discuss the potential of rehabilitation technology to support the achievement of key factors in motor...

Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Prediction of disability progression in multiple sclerosis patients is a critical component of their management. In particular, one challenge is to identify and characterize a patient profile who may benefit of efficient treatments. However, it is no...

Design and Characterization of a Robotic Device for the Assessment of Hand Proprioceptive, Motor, and Sensorimotor Impairments.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Hand function is often impaired after neurological injuries such as stroke. In order to design patient-specific rehabilitation, it is essential to quantitatively assess those deficits. Current clinical scores cannot provide the required level of deta...

Automated Rating of Multiple Sclerosis Test Results Using a Convolutional Neural Network.

Studies in health technology and informatics
This work concerns methods for automated rating of the progression of Multiple Sclerosis (MS). Often, MS patients develop cognitive deficits. The Brief Visuospatial Memory Test-Revised (BVMT-R) is a recognized method to measure optical recognition de...

The role of robotic gait training coupled with virtual reality in boosting the rehabilitative outcomes in patients with multiple sclerosis.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
Motor impairment is the most common symptom in multiple sclerosis (MS). Thus, a variety of new rehabilitative strategies, including robotic gait training, have been implemented, showing their effectiveness. The aim of our study was to investigate whe...

Robot-Assisted Body-Weight-Supported Treadmill Training in Gait Impairment in Multiple Sclerosis Patients: A Pilot Study.

Advances in experimental medicine and biology
This study deals with the use of a robot-assisted body-weight-supported treadmill training in multiple sclerosis (MS) patients with gait dysfunction. Twenty MS patients (10 men and 10 women) of the mean of 46.3 ± 8.5 years were assigned to a six-week...