6 research outputs found
Development and Control of Hand Exoskeleton System Using Intended Movement
Hand motor impairment is a common disability among stroke survivors that severely affect their ability in activities of daily livings (ADLs), reducing independence and quality of life. Throughout the rehabilitation process, stroke patients able to regain partially or fully the hand motor function. However, the conventional rehabilitation process is limited by the insufficient number of therapists, labor-intensiveness, and low compliance. The objective of this study was to support the rehabilitation process and ADLs through the development of the Flexible Linkage Hand Exoskeleton Rehabilitation Robot (FLEXOR), a five fingers 3D printed prototype actuated by linear actuators. FLEXOR was controlled using intended movement to support the independent exercises and to assist the ADLs movement. An Arduino-based control system driven by electromyography (EMG) signal was developed for FLEXOR. The new control system protected the hand against over-flexing and excessive application of force. The control system was programmed into three different operating modes which enable FLEXOR to provide passive exercises to the fingers, assist fingers in ADLs movement with minimal efforts, and provide active exercises while assisting fingers in ADLs
Evaluation of Muscle Activities on Different Type of Exercises During Prolonged Sitting
Abstract: Electromyography (EMG) signal is an analysis of electrical signals generated during muscular contractions that have been used to measure and record electrical muscle activity usually applied for medical tests. In this research EMG signal is used to; (1) evaluate muscle activations on different gender during prolonged sitting task; (2) investigate the influence of various types of exercise during prolonged sitting on muscle activation and (3) proposed the best exercise that can help to prevent low back discomfort. Twenty subjects (10 males and 10 females) were recruited from undergraduate engineering student’s education background in UniMAP with age ranging between 20 to 24 years old. The subject must be asymptomatic back pain, normal BMI and right-handed. . Three different types of sitting, one hour per sitting were done by each subject in order to reach the goals of this study. First sitting (sitting without exercise) was conducted while second and third sitting (sitting with exercise) were done in order the investigate the effectiveness of the exercises. Two different types of exercise were performed in second and third sitting, both of exercises were chosen from Mc Kenzie’s exercise. EEGOTM sport device were used to record the EMG signal from four types of muscles which are Erector Spinae, Latissimus Dorsi, Internal Oblique and External Oblique. By comparing the Root Mean Square (RMS) values from EMG signals muscle activation during prolonged sitting and the effectiveness of performing the exercises have been evaluated based on RMS values. As the results, muscle become deactivate during prolonged sitting. The best exercise to reduce back pain discomfort is exercise type 1 (Seated Lumbar Exercise) and it is recommended to perform this exercise regularly to reduce the risk of getting hazardous disease due to prolonged sitting.
Keywords: Prolonged sitting, muscle activity, exercises on prolonged sittin
Preliminary Study on Modelling and Simulation of Virtual Reality Assistive Tool for Autism Children Using Gaming Software
Autism Spectrum Disorder (ASD) is an early childhood disorder that affects individual ability to interact and
socialize with other people. Children with ASD have problems interacting with their peers and have difficulty to exercise
their social skills. In this study, a virtual reality (VR) based assistive tool was modelled and simulated using a gaming software called Dark Basic Professional (DBPro). The assistive tool was developed to support ASD children to interact and apply the social skills. Seven tasks were designed for the VR assistive tool based on three targeted skills including facial expression recognition, reading comprehension, and task delivery. As a preliminary study, only three non-ASD children were participated in the VR assistive tool experiment to analyse the tasks. The experiment results showed that all participants successfully performed five out of seven tasks. However, all participants failed to perform the video prompting task while one participant was not able to recognize the emotion from robotics-based faces in the facial expression. The
results from pulse sensor showed that the heart rate was stable during the basic experiment using VR but unstable during the applied experiment and real-world discussion. There is a need to review the overall modelling and simulation technique, and the number of participants among ASD children should be increased for the future study