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Stroke Rehabilitation

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A Novel Soft Robotic Supernumerary Hand for Severely Affected Stroke Patients.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Upper limb functions are severely affected in 23% of the chronic stroke patients, compromising their life quality. To re-enable hand use, providing a degree of functionality and motivating against learned non-use, we propose a robotic supernumerary l...

Effects of robotic gait training after stroke: A meta-analysis.

Annals of physical and rehabilitation medicine
BACKGROUND: Robotic devices are often used in rehabilitation and might be efficient to improve walking capacity after stroke.

Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke.

Neurorehabilitation and neural repair
. Accurate prediction of clinical impairment in upper-extremity motor function following therapy in chronic stroke patients is a difficult task for clinicians but is key in prescribing appropriate therapeutic strategies. Machine learning is a highly ...

Impact of initial flexor synergy pattern scores on improving upper extremity function in stroke patients treated with adjunct robotic rehabilitation: A randomized clinical trial.

Topics in stroke rehabilitation
 Robot-assisted rehabilitation is an appealing strategy for patients after stroke, as it generates repetitive movements in a consistent, precise, and automated manner.  To identify patients who will benefit most from robotic rehabilitation for upper ...

Robot-assisted therapy for arm recovery for stroke patients: state of the art and clinical implication.

Expert review of medical devices
: Robot-assisted therapy is an emerging approach that performs highly repetitive, intensive, task oriented and quantifiable neuro-rehabilitation. In the last decades, it has been increasingly used in a wide range of neurological central nervous syste...

A randomized controlled study incorporating an electromechanical gait machine, the Hybrid Assistive Limb, in gait training of patients with severe limitations in walking in the subacute phase after stroke.

PloS one
Early onset, intensive and repetitive, gait training may improve outcome after stroke but for patients with severe limitations in walking, rehabilitation is a challenge. The Hybrid Assistive Limb (HAL) is a gait machine that captures voluntary action...

Human arm weight compensation in rehabilitation robotics: efficacy of three distinct methods.

Journal of neuroengineering and rehabilitation
BACKGROUND: Arm weight compensation with rehabilitation robots for stroke patients has been successfully used to increase the active range of motion and reduce the effects of pathological muscle synergies. However, the differences in structure, perfo...

Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

Computer methods and programs in biomedicine
INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to reach shared after-care decisions for recovery or rehabilita...

Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial.

Acta neurologica Belgica
The purpose of this study was to investigate the effects of robot-assisted gait training (RAGT) on mobility, activities of daily living (ADLs), and quality of life (QoL) in stroke rehabilitation. Fifty-one stroke patients randomly assigned to Group 1...

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders.

Journal of neuroengineering and rehabilitation
BACKGROUND: In clinical practice, therapists choose the amount of assistance for robot-assisted training. This can result in outcomes that are influenced by subjective decisions and tuning of training parameters can be time-consuming. Therefore, vari...