System Identification I

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Biomechanics And Motor Control Of Human Movement

Technological advancements have led to the development of numerous wearable robotic devices for the physical assistance and restoration of human locomotion. While many challenges remain with respect to the mechanical design of such devices, it is at least equally challenging and important to develop strategies to control them in concert with the intentions of the user. This work reviews the state-of-the-art techniques for controlling portable active lower limb prosthetic and orthotic (P/O) devices in the context of locomotive activities of daily living (ADL), and considers how these can be interfaced with the user’s sensory-motor control system. This review underscores the practical challenges and opportunities associated with P/O control, which can be used to accelerate future developments in this field. Furthermore, this work provides a classification scheme for the comparison of the various control strategies. As a novel contribution, a general framework for the control of portable gait-assistance devices is proposed. This framework accounts for the physical and informatic interactions between the controller, the user, the environment, and the mechanical device itself. Such a treatment of P/Os – not as independent devices, but as actors within an ecosystem – is suggested to be necessary to structure the next generation of intelligent and multifunctional controllers. Each element of the proposed framework is discussed with respect to the role that it plays in the assistance of locomotion, along with how its states can be sensed as inputs to the controller. The reviewed controllers are shown to fit within different levels of a hierarchical scheme, which loosely resembles the structure and functionality of the nominal human central nervous system (CNS). Active and passive safety mechanisms are considered to be central aspects underlying all of P/O design and control, and are shown to be critical for regulatory approval of such devices for real-world use. The works discussed herein provide evidence that, while we are getting ever closer, significant challenges still exist for the development of controllers for portable powered P/O devices that can seamlessly integrate with the user’s neuromusculoskeletal system and are practical for use in locomotive ADL.

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Control strategies for active lower extremity prosthetics and orthotics: a review

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.

The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges

With efficiencies derived from evolution, growth and learning, humans are very well-tuned for locomotion. Metabolic energy used during walking can be partly replaced by power input from an exoskeleton, but is it possible to reduce metabolic rate without providing an additional energy source? This would require an improvement in the efficiency of the human-machine system as a whole, and would be remarkable given the apparent optimality of human gait. Here we show that the metabolic rate of human walking can be reduced by an unpowered ankle exoskeleton. We built a lightweight elastic device that acts in parallel with the user's calf muscles, off-loading muscle force and thereby reducing the metabolic energy consumed in contractions. The device uses a mechanical clutch to hold a spring as it is stretched and relaxed by ankle movements when the foot is on the ground, helping to fulfil one function of the calf muscles and Achilles tendon. Unlike muscles, however, the clutch sustains force passively. The exoskeleton consumes no chemical or electrical energy and delivers no net positive mechanical work, yet reduces the metabolic cost of walking by 7.2 ± 2.6% for healthy human users under natural conditions, comparable to savings with powered devices. Improving upon walking economy in this way is analogous to altering the structure of the body such that it is more energy-effective at walking. While strong natural pressures have already shaped human locomotion, improvements in efficiency are still possible. Much remains to be learned about this seemingly simple behaviour.

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Reducing the energy cost of human walking using an unpowered exoskeleton

Many soldiers are expected to carry heavy loads over extended distances, often resulting in physical and mental fatigue. In this study, the design and testing of an autonomous leg exoskeleton is presented. The aim of the device is to reduce the energetic cost of loaded walking. In addition, we present the Augmentation Factor, a general framework of exoskeletal performance that unifies our results with the varying abilities of previously developed exoskeletons. We developed an autonomous battery powered exoskeleton that is capable of providing substantial levels of positive mechanical power to the ankle during the push-off region of stance phase. We measured the metabolic energy consumption of seven subjects walking on a level treadmill at 1.5 m/s, while wearing a 23 kg vest. During the push-off portion of the stance phase, the exoskeleton applied positive mechanical power with an average across the gait cycle equal to 23 ± 2 W (11.5 W per ankle). Use of the autonomous leg exoskeleton significantly reduced the metabolic cost of walking by 36 ± 12 W, which was an improvement of 8 ± 3% (p = 0.025) relative to the control condition of not wearing the exoskeleton. In the design of leg exoskeletons, the results of this study highlight the importance of minimizing exoskeletal power dissipation and added limb mass, while providing substantial positive power during the walking gait cycle.

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Autonomous exoskeleton reduces metabolic cost of human walking during load carriage

Advanced upper limb prostheses capable of actuating multiple degrees of freedom (DOFs) are now commercially available. Pattern recognition algorithms that use surface electromyography (EMG) signals show great promise as multi-DOF controllers. Unfortunately, current pattern recognition systems are limited to activate only one DOF at a time. This study introduces a novel classifier based on Bayesian theory to provide classification of simultaneous movements. This approach and two other classification strategies for simultaneous movements were evaluated using nonamputee and amputee subjects classifying up to three DOFs, where any two DOFs could be classified simultaneously. Similar results were found for nonamputee and amputee subjects. The new approach, based on a set of conditional parallel classifiers was the most promising with errors significantly less ( p <; 0.05) than a single linear discriminant analysis (LDA) classifier or a parallel approach. For three-DOF classification, the conditional parallel approach had error rates of 6.6% on discrete and 10.9% on combined motions, while the single LDA had error rates of 9.4% on discrete and 14.1% on combined motions. The low error rates demonstrated suggest than pattern recognition techniques on surface EMG can be extended to identify simultaneous movements, which could provide more life-like motions for amputees compared to exclusively classifying sequential movements.

Classification of Simultaneous Movements Using Surface EMG Pattern Recognition

Currently, the mobility of above-knee amputees is limited by the lack of available prostheses that can efficiently replicate biologically accurate movements. In this study, a powered knee prosthesis was designed utilizing a novel mechanism, known as a clutchable series-elastic actuator (CSEA).The CSEA includes a low-power clutch in parallel with an electric motor within a traditional series-elastic actuator. The stiffness of the series elasticity was tuned to match the elastically conservative region of the knee's torque-angle relationship during the stance phase of locomotion. During this region, the clutch was used to efficiently store energy in the series elasticity. The fully autonomous knee prosthesis design utilized a brushless electric motor, ballscrew transmission and cable drive, as well as commercial electrical components. The knee was lighter than the eighth percentile and shorter than the first percentile male shank segment. The CSEA Knee was tested in a unilateral above-knee amputee walking at 1.3 m/s. During walking, the CSEA Knee provided biomechanically accurate torque-angle behavior, agreeing within 17% of the net work and 27% of the stance flexion angle produced by the biological knee. In addition, the process of locomotion reduced the net electrical energy consumption of the CSEA Knee. The knee's motor generated 1.8 J/stride, and the net energy consumption was 3.6 J/stride, an order of magnitude less energy than previously published powered knee prostheses.

Clutchable series-elastic actuator: Implications for prosthetic knee design

Human joint impedance is the dynamic relationship between the differential change in the position of a perturbed joint and the corresponding response torque; it is a fundamental property that governs how humans interact with their environments. It is critical to characterize ankle impedance during the stance phase of walking to elucidate how ankle impedance is regulated during locomotion, as well as provide the foundation for future development of natural, biomimetic powered prostheses and their control systems. In this study, ankle impedance was estimated using a model consisting of stiffness, damping and inertia. Ankle torque was well described by the model, accounting for 98 ±1.2% of the variance. When averaged across subjects, the stiffness component of impedance was found to increase linearly from 1.5 to 6.5 Nm/rad/kg between 20% and 70% of stance phase. The damping component was found to be statistically greater than zero only for the estimate at 70% of stance phase, with a value of 0.03 Nms/rad/kg. The slope of the ankle's torque-angle curve-known as the quasi-stiffness-was not statistically different from the ankle stiffness values, and showed remarkable similarity. Finally, using the estimated impedance, the specifications for a biomimetic powered ankle prosthesis were introduced that would accurately emulate human ankle impedance during locomotion.

Elliott J. Rouse

Papers

Autonomous exoskeleton reduces metabolic cost of human walking during load carriage

Classification of Simultaneous Movements Using Surface EMG Pattern Recognition

Clutchable series-elastic actuator: Implications for prosthetic knee design

Autonomous exoskeleton reduces metabolic cost of human walking during load carriage

Estimation of Human Ankle Impedance During the Stance Phase of Walking