Development of a robust myoelectric control architecture for lower limb robotic prostheses applications.

[摘要] ENGLISH ABSTRACT: Traumatic events such as accidents or vascular and circulatory disorders often lead to amputationof the lower limb. To increase mobility most amputees aretted with a passive prosthetics.However, the use of a passive foot with axed ankle has short term e ects, such as asymmetricgait, increased muscle contraction on the intact side and higher metabolic energy expenditure.The long-term e ects are osteoarthritis, osteoporosis, back pain and to a large extent musculoskeletalproblems. As a result, arti cial prosthetic limbs are regarded by the amputees as exoticlifeless attachments to the body and not as a non-biological extension of the human body. Mechatronicsystems coupled with intelligent control architectures provide the platform to restoring anamputee's overall mobility related lifestyle. However, the recovered gait is largely in uenced bythe extent of amputation and functional level of the prosthesis. The transtibial osteomyoplasticamputation technique offers residual muscles that are active throughout the gait cycle. These muscles offer potential sites for extracting surface electromyography (sEMG) signals.The study presents a novel methodology which seeks to utilise these residual signals to controlan artificial limb by predicting the human movement intentions. A protocol was developed forthe acquisition and analysis of electromyography signals from the identified muscles. The availableSENIAM and ISEK standards were found to be insuficient during the recording of signalsfrom the residual stump as some of the anatomical landmarks were missing. The Soleus muscleresponsible for plantarflexion was not accessible on the residual limb thereby providing challengeson using the SENIAM standards for selecting a muscle for the plantarflexion movement. Tibialisanterior, Medialis Gastrocnemius and Lateralis Gastrocnemius muscles were able to providesEMG signals with sufficient signal properties for developing a myoelectric pattern recognitionarchitecture. The main goal was to develop a robust intelligent control system architecture fora robotic prosthetic lower limb capable of enhancing human mobility with great stability. Thefunctionality of a robotic limb is highly governed by kinetics, kinematics and the dynamics ofthe mechanical structure when interfaced with the human body. Therefore, the structure andparameters of the actuation model for complex joint angle prediction and an intuitive neuralinterface mechanism for intention detection were developed based on experimental results from biomechanics experiments.A pattern recognition algorithm was developed based on 23 signal features. Principal componentanalysis was used for dimensionality reduction on the extracted feature set. A total of22 classifiers were tested and the Linear Support Vector Machine produced an average of 100%classification accuracy on training data with 20% of the training data being reserved for validation.The intelligent architecture produced an average of 99.25% classification accuracy on newunlabelled test data.The system was optimised using force sensitive resistors to detect heel strike, toe oandbeginning of the swing and stance phases of gait. A dual inertial measurement system was usedto predict the position of the limb in space thereby providing feedback on limb performance tothe main controller. The use of adaptivelters on signal acquisition improved signal qualityand the use of Kalmanlters on feedback sensors provided a robust system which was able toachieve the desired control objective even in the event of partial or missing input signal as theypredicted the intended signal based on the previously correct signal input. This study revealedthat the concept developed has the potential to improve the lives of many amputees as it has theability to restore normal gait to the satisfactory level of the amputee. The intuitive control of theprosthetic limb provided by the sEMG signals and the inertial sensor feedback system minimisesthe need for the situational attentiveness of the amputee with regards to the operation of thepowered prosthetic.

[发布机构] Stellenbosch University