Abstract.A review study was conducted on existing lower-limb orthosis systems for rehabilitation which implemented pneumatic muscle type of actuators with the aim to clarify the current and on-going research in this field. The implementation of pneumatic artificial muscle will play an important role for the development of the advanced robotic system. In this research a derivation model for the antagonistic mono-and bi-articular muscles using pneumatic artificial muscles of a lower limb orthosis will be verified with actual human's muscle activities models. A healthy and young male 29 years old subject with height 174cm and weight 68kg was used as a test subject. Two mono-articular muscles Vastus Medialis (VM) and Vastus Lateralis (VL) were selected to verify the mono-articular muscle models and muscle synergy between anterior muscles. Two biarticular muscles Rectus Femoris (RF) and Bicep Femoris (BF) were selected to verify the bi-articular muscle models and muscle co-contraction between anterior-posterior muscles. The test was carried out on a treadmill with a speed of 4.0 km/h, which approximately around 1.25 m/s for completing one cycle of walking motion. The data was collected for about one minute on a treadmill and 20 complete cycles of walking motion were successfully recorded. For the evaluations, the mathematical model obtained from the derivation and the actual human muscle activation patterns obtained using the surface electromyography (sEMG) system were compared and analysed. The results shown that, high correlation values ranging from 0.83 up to 0.93 were obtained in between the derivation model and the actual human muscle's model for both mono-and biarticular muscles. As a conclusion, based on the verification with the sEMG muscle activities data and its correlation values, the proposed derivation models of the antagonistic mono-and bi-articular muscles were suitable to simulate and controls the pneumatic muscles actuated lower limb orthosis.
Nowadays, medical rehabilitation system has become a requirement due to increment in national rehabilitation centres and medical hospitals. An assistive rehabilitation orthosis becomes essential and was used for rehabilitation therapy, condition monitoring, and physical strengthening. This study focused on the lower limb assistive rehabilitation orthosis development using pneumatic artificial muscle. To successfully control this orthosis system which consists of antagonistic mono-and biarticular muscle actuators, it is necessary to construct a reliable control algorithm. The suitable control scheme and strategy to manoeuvre this orthosis system similar to human musculoskeletal system have yet to be fully developed and established. Based on the review study, it is said that the co-contraction controls of anterior-posterior pneumatic muscles was able to improve the joint stiffness and stability of the orthosis as well as good manoeuvrability. Therefore, a characterization model of an antagonistic mono-and bi-articular muscles activities of human's lowerlimb during walking motion will be necessary. A healthy young male subject was used as test subject to obtain the sEMG muscle activities for antagonistic mono-and bi-articular muscles (i.e., Vastus Medialis-VM, Vastus Lateralis-VL, Rectus Femoris-RF, and Bicep Femoris-BF). The tests were carried out at different speeds of 2km/h, 3km/h, and 4km/h for one minute walking motion on a treadmill. Then, the patterns of the sEMG muscle activities were modelled and characterised using fifth order polynomial equation. Based on the results, it is shown that the anterior and posterior muscles were exhibited a muscle synergy in-between multiple anterior or posterior muscles and muscle co-contraction between anteriorposterior muscles in order to control the movements at the joints during walking motion. As conclusion, it is proven that the sEMG muscle activities of the antagonistic mono-and bi-articular muscles were follow a certain contraction-expansion patterns during walking motion even when it were tested at different gait cycle speeds.
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