SOFTWARE IN EXOSKELETON ROBOTIC HAND (EXOHAND) FOR MIRROR NEURON THERAPY

Stroke is a condition that occurs when the blood supply to the brain is interrupted. Without blood, some of the nerve cells in the brain will die. As a result, stroke sufferers are threatened with death or paralysis. In the case of stroke patients who experience paralysis, paralysis only occurs i...

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Bibliographic Details
Main Author: Josephine Ovani, Cheryl
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/50316
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Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:Stroke is a condition that occurs when the blood supply to the brain is interrupted. Without blood, some of the nerve cells in the brain will die. As a result, stroke sufferers are threatened with death or paralysis. In the case of stroke patients who experience paralysis, paralysis only occurs in one of the sagittal parts of the body, that is the left or right halves only. In mirror neuron therapy, stroke patients are asked to do a grasping motion on both hands simultaneously. In front of the paralyzed hand, a mirror is given to give the illusion that the paralyzed hand is also moving. This moving illusion can stimulate nerve cells in the brain to "transfer" the function of the dead nerve cells to the new one. This ability becomes very active only in the first three months after stroke attacks (golden time period). Unfortunately, mirror neuron therapy with mirrors only provides visual feedback where the utilization of the post-stroke golden time period is not optimal. Exoskeleton robotic hand (ExoHand) was created to provide movement feedback to the patient's paralyzed left hand while doing mirror neuron therapy. This report describes the software for the ExoHand system. Simply put, ExoHand will take the bending data of the right hand as a set point and the bending data of the left hand as an input. Both of these data are used as inputs for controlling the DC motor position until the input value is the same as the set point value. The results showed that ExoHand was able to reflect the movement of the healthy right hand to the paralyzed left hand with a maximum delay of 500 ms (for the thumb) and 2000 ms (for the other 4 fingers). Based on the results obtained, it can be concluded that ExoHand fulfills its main characteristics and features, that is reflecting the grasping motion of the right hand to the left hand.