scholarly journals Simulation of an ankle rehabilitation system based on scotch- yoke mechanism

Author(s):  
C M Racu (Cazacu) ◽  
I Doroftei ◽  
Ghe Plesu ◽  
I A Doroftei
Author(s):  
Amir B. Farjadian ◽  
Mohsen Nabian ◽  
Maureen K. Holden ◽  
Constantinos Mavroidis

2017 ◽  
Vol 79 (6) ◽  
Author(s):  
Lim Ch Ee Chin ◽  
Shafriza Nisha Basah ◽  
Marwan Affandi ◽  
Muhammad Nazrin Shah ◽  
Sazali Yaacob ◽  
...  

Ankle sprain Injury is one of the most common ankle injuries due to domestic or sporting accidents. There is a need for greater demand for quick and effective ankle rehabilitation system (ARS). Nowadays, research on ARS has gained a great attention than manual clinical method in medical areas such as orthopedic injuries, pediatrics sport medicine and industrial services. It can improve the treatment conditions by reducing the dependency of doctors’ supervision, help patient with less movable to have home-based rehab exercise and help to speeds up recovery. There are currently available ARS that can provide effective ankle rehabilitation treatment such as Visual, Non-Visual and Robot-aided. In this paper, the critical review of ARS is conducted to evaluate the effectiveness of ARS in terms of provided setting criteria. The strengths, weaknesses, opportunities and threats of each ARS is discussed and compared to identify the most suitable home application of ARS for ankle sprain patient. From the comparison, the most suitable home application ARS is the visual marker-less based ARS system which give user-friendly, efficiency, validity in performance and cheaper cost. 


2019 ◽  
Vol 9 (12) ◽  
pp. 2429
Author(s):  
Norihiko Saga ◽  
Yasuto Tanaka ◽  
Atsushi Doi ◽  
Teruo Oda ◽  
Suguru N. Kudoh ◽  
...  

Neurorehabilitation using a brain–computer interface (BCI) requires machine learning, for which calculations take a long time, even days. However, the demands of actual rehabilitation are becoming increasingly rigorous, requiring that processes be completed within tens of minutes. Therefore, we developed a new effective rehabilitation system for treating patients such as those with stroke hemiplegia. The system can smoothly perform rehabilitation training on the day of admission to the hospital. We designed a heuristic BCI with simplified fuzzy reasoning, which can detect motor intention signals from an electroencephalogram (EEG) within several tens of minutes. The detected signal is sent to the newly developed ankle rehabilitation device (ARD), and the patient repeats the dorsiflexion motion by the ARD.


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