scholarly journals Neural Networks Controler of a Lower Limbs Robotic Rehabilitation Chair

2014 ◽  
Keyword(s):  
Neural Networks ◽  
Lower Limbs ◽  
Robotic Rehabilitation

scholarly journals Robotic Technologies and Rehabilitation: New Tools for Stroke Patients’ Therapy

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Patrizia Poli ◽  
Giovanni Morone ◽  
Giulio Rosati ◽  
Stefano Masiero
Keyword(s):  
Gait Training ◽  
Lower Limbs ◽  
Robotic Rehabilitation ◽  
Stroke Patients ◽  
Home Based ◽  
Comprehensive Search ◽  
Improve Muscle Strength ◽  
Training Protocol ◽  
Robotic Technologies

Introduction. The role of robotics in poststroke patients’ rehabilitation has been investigated intensively. This paper presents the state-of-the-art and the possible future role of robotics in poststroke rehabilitation, for both upper and lower limbs.Materials and Methods. We performed a comprehensive search of PubMed, Cochrane, and PeDRO databases using as keywords “robot AND stroke AND rehabilitation.”Results and Discussion. In upper limb robotic rehabilitation, training seems to improve arm function in activities of daily living. In addition, electromechanical gait training after stroke seems to be effective. It is still unclear whether robot-assisted arm training may improve muscle strength, and which electromechanical gait-training device may be the most effective for walking training implementation.Conclusions. In the field of robotic technologies for stroke patients’ rehabilitation we identified currently relevant growing points and areas timely for developing research. Among the growing points there is the development of new easily transportable, wearable devices that could improve rehabilitation also after discharge, in an outpatient or home-based setting. For developing research, efforts are being made to establish the ideal type of treatment, the length and amount of training protocol, and the patient’s characteristics to be successfully enrolled to this treatment.

Rehabilitation robots

2018 ◽  
Vol 45 (3) ◽  
pp. 301-306 ◽  
Author(s):  
Robert Bogue
Keyword(s):  
Computer Games ◽  
Brain Computer Interface ◽  
Hand Movement ◽  
Traumatic Injury ◽  
Lower Limbs ◽  
Computer Interface ◽  
Robotic Rehabilitation ◽  
Content Type ◽  
Rehabilitation Robots ◽  
Ambulatory Ability

Purpose This paper aims to provide an insight into the emerging use of robots in the rehabilitation of sufferers from strokes and other neurological impediments. Design/methodology/approach This considers research, clinical trials and commercial products. Following an introduction, it explains brain neuroplasticity and its role in rehabilitation and then discusses the use of robots in the restoration of upper limb and hand movement in stroke and traumatic injury patients. Robotic techniques aimed at restoring ambulatory ability are then discussed, followed by examples of the application of brain–computer interface technology to robotic rehabilitation. Finally, concluding comments are drawn. Findings Research has shown that robotic techniques can assist in the restoration of functionality to partially or fully paralysed upper and lower limbs. A growing number of commercial exoskeleton and end-effector robotic products have been launched which are augmenting conventional rehabilitation therapies. These systems frequently include interactive computer games and tasks which encourage repetitive use and allow patients to monitor their progress. Trials which combine robotics with brain–computer interface technology have yielded encouraging and unexpectedly positive results. Originality/value This provides details of the increasingly important role played by robots in the rehabilitation of patients suffering from strokes and other neurological disorders.

scholarly journals Assessing Effectiveness and Costs in Robot-Mediated Lower Limbs Rehabilitation: A Meta-Analysis and State of the Art

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Giorgio Carpino ◽  
Alessandra Pezzola ◽  
Michele Urbano ◽  
Eugenio Guglielmelli
Keyword(s):  
Meta Analysis ◽  
Cost Effective ◽  
Conventional Approach ◽  
Lower Limbs ◽  
Secondary Outcome ◽  
Robotic Rehabilitation ◽  
Wearable Robots ◽  
Cost Effective Approach ◽  
Significant Difference ◽  
The Cost

Robots were introduced in rehabilitation in the 90s to meet different needs, that is, reducing the physical effort of therapists. This work consists of a meta-analysis of robot-mediated lower limbs rehabilitation for stroke-affected patients; it aims at evaluating the effectiveness of the robotic approach through the use of wearable robots or operational machines with respect to the conventional approach (i.e., manual rehabilitation therapy). The primary assessed outcome is the patient’s ability to recover walking independence, whereas the secondary outcome is the average walking speed. The therapy acceptability and the treatment costs are also assessed. The assessment shows that the robot-mediated therapy is more effective than the conventional one in reaching the primary outcome. As for the secondary outcome, there is no significant difference between the robotic (wearable robots or operational machines) and the conventional approach. Rehabilitation using wearable robots has a greater acceptability than the conventional one. This does not apply to operational machines. The cost of robotic treatment with wearable robots ranges from double to triple the cost of the conventional approach. On the contrary, rehabilitation using operational machines costs the same as the conventional treatment. Robotic rehabilitation based on operational machines is the most cost-effective approach.

Lower Limbs Robotic Rehabilitation Case Study with Clinical Trials

2014 ◽  
pp. 31-44 ◽  
Author(s):  
M. Bouri ◽  
E. Abdi ◽  
H. Bleuler ◽  
F. Reynard ◽  
O. Deriaz
Keyword(s):  
Clinical Trials ◽  
Lower Limbs ◽  
Robotic Rehabilitation

Movement Pattern Recognition Using Neural Networks

2011 ◽  
pp. 217-237 ◽  
Author(s):  
Rezaul Begg ◽  
Joarder Kamruzzaman
Keyword(s):  
Neural Networks ◽  
Movement Pattern ◽  
Lower Limbs ◽  
Gait Patterns ◽  
Automated Recognition ◽  
Network Applications ◽  
Gait Classification ◽  
Functional Gait ◽  
Neural Network Applications

This chapter provides an overview of artificial neural network applications for the detection and classification of various gaits based on their typical characteristics. Gait analysis is routinely used for detecting abnormality in the lower limbs and also for evaluating the progress of various treatments. Neural networks have been shown to perform better compared to statistical techniques in some gait classification tasks. Various studies undertaken in this area are discussed with a particular focus on neural network’s potential in gait diagnostics. Examples are presented to demonstrate the suitability of neural networks for automated recognition of gait changes due to aging from their respective gait patterns and their potential for identification of at-risk or non-functional gait.

Determination of S-N curves with the application of artificial neural networks

1999 ◽  
Vol 22 (8) ◽  
pp. 723-728 ◽  
Author(s):  
Artymiak ◽  
Bukowski ◽  
Feliks ◽  
Narberhaus ◽  
Zenner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural
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