Development of gripping assistive device for training - Mohd Rais Hakim Ramlee (Kulliyyah of Engineering, International Islamic University Malaysia, 2020)
Gripping is an everyday task which goes unnoticeable. Since it is an essential daily movement, without this motion, a lot of activities involving this movement could not be done. However, due to the growing process or some injury, the grasping movement become disrupted, which cause difficulties to do some daily activities. These impacts depend on individual and also in different ways regardless of age and how the body drastically become weak and fragile, less adaptable and less impervious to sickness and damage. Patients affected with hand gripping issues typically require long term care. This also contributes towards their ability to recover much longer as their regular activity reduces and dependency on other increases. Therapy, as an early rehabilitation within the golden period (less than 3 three months prior to incident), is required to improve the gripping motion and regain back the strength of the affected joints as well as muscles. Rehabilitation also helps to improve the patient's ability to return the patient to the level of premorbid function. The current situation is that the rehabilitation process takes longer as there are few physiotherapists available in hospitals. It is anticipated that a mechatronics approach using robotics-based devices have been seen as a promising candidate to assist existing forms of the rehabilitation process. The idea is to develop a basic function rehabilitation robot to support the physiotherapist. The rehabilitation robot is designed to help with the gripping process, where the system is based on a master-slave mechanism which needs a healthy hand to control the weak hand. The system uses a leap motion sensor as an input, and the output is an exoskeleton. A gyroscope was used to indicate the finger position and placed on top of the exoskeleton. The exoskeleton has been tested by a subject for several times. The results shows the simulation of exoskeleton that can do flexion and extension process. The errors between the desired extension angle value and the extension angles on link 1 and link 2 are 5.58% and 11.02% respectively. However, this design need some improvement on the material and angle sensors selection. The material must be light and smooth surface and the angle sensor must be high in precision and accuracy.