Case Study on Human Walking during Wearing a Powered Prosthetic Device: Effectiveness of the System “Human-Robot”

It is known that force exchanges between a robotic assistive device and the end-user have a direct impact on the quality and performance of a particular movement task. This knowledge finds a special reflective importance in prosthetic industry due to the close human-robot collaboration. Although lower-extremity prostheses are currently better able to provide assistance as their upper-extremity counterparts, specific locomotion problems still remain. In a framework of this contribution the authors introduce the multibody dynamic modelling approach of the transtibial prosthesis wearing on a human body model. The obtained results are based on multibody dynamic simulations against the real experimental data using AMP-Foot 2.0, an energy efficient powered transtibial prosthesis for actively assisted walking of amputees

A Generalized Method for Predictive Simulation-Based Lower Limb Prosthesis Design

Lower limb prostheses are designed to replace the functions and form of the missing biological anatomy. These functions are hypothesized to improve user outcome measures which are negatively affected by receiving an amputation – such as metabolic cost of transport, preferred walking speed, and perceived discomfort during walking. However, the effect of these design functions on the targeted outcome measures is highly variable, suggesting that these relationships are not fully understood. Biomechanics simulation and modeling tools are increasingly capable of analyzing the effects of a design on the resulting user gait. In this work, prothesis-aided gait is optimized in simulation to reduce both muscle effort and peak loads on the residual limb using a generalized prosthesis model. Compared to a traditional revolute powered ankle joint model, a two degree-of freedom generalized model reduced muscle activations by 50% and peak loads by 15%. Simulated prosthesis behaviors corresponding to the optimal gait patterns were translated into a two degree-of-freedom ankle-foot prosthesis design with powered bidirectional linear translation and plantarflexion. The prototype is capable of delivering up to 171 N-m of plantarflexion torque and 499 N of translation force, with 15° dorsi-/35° plantarflexion and 10 cm translation range of motion. The mass and height of the ankle-foot are 2.29 kg and 19.5 cm, respectively. The mass of the entire system including the wearable offboard system is 8.58 kg. This platform is designed to emulate the behavior of the simulated prosthesis, as well as be configurable to emulate alternate behaviors obtained from simulations with different optimization objectives. The prototype is controlled to replicate simulated walking patterns using a high level finite state controller, mid-level stiffness controller, and low level load controller. Closed loop load control has bandwidth of 15 Hz in translation and 7.2 Hz in flexion. Load tracking during walking with a single able-bodied human subject ranges from 93 to 159 N in translation and 4.6 to 21.3 N-m in flexion. The contribution of this work is to provide a framework for predictive simulation-based prosthesis design, evidence of its practical implementation, and the experimental tools to validate future predictive simulation studies

A Biomimetic Approach to Controlling Restorative Robotics

Movement is the only way a person can interact with the world around them. When trauma to the neuromuscular systems disrupts the control of movement, quality of life suffers. To restore limb functionality, active robotic interventions and/or rehabilitation are required. Unfortunately, the primary obstacle in a person’s recovery is the limited robustness of the human-machine interfaces. Current systems rely on control approaches that rely on the person to learn how the system works instead of the system being more intuitive and working with the person naturally. My research goal is to design intuitive control mechanisms based on biological processes termed the biomimetic approach. I have applied this control scheme to problems with restorative robotics focused on the upper and lower limb control. Operating an advanced active prosthetic hand is a two-pronged problem of actuating a high-dimensional mechanism and controlling it with an intuitive interface. Our approach attempts to solve these problems by going from muscle activity, electromyography (EMG), to limb kinematics calculated through dynamic simulation of a musculoskeletal model. This control is more intuitive to the user because they attempt to move their hand naturally, and the prosthetic hand performs that movement. The key to this approach was validating simulated muscle paths using both experimental measurements and anatomical constraints where data is missing. After the validation, simulated muscle paths and forces are used to decipher the intended movement. After we have calculated the intended movement, we can move a prosthetic hand to match. This approach required minimal training to give an amputee the ability to control prosthetic hand movements, such as grasping. A more intuitive controller has the potential to improve how people interact and use their prosthetic hands. Similarly, the rehabilitation of the locomotor system in people with damaged motor pathways or missing limbs require appropriate interventions. The problem of decoding human motor intent in a treadmill walking task can be solved with a biomimetic approach. Estimated limb speed is essential for this approach according to the theoretical input-output computation performed by spinal central pattern generators (CPGs), which represents neural circuitry responsible for autonomous control of stepping. The system used the locomotor phases, swing and stance, to estimate leg speeds and enable self-paced walking as well as steering in virtual reality with congruent visual flow. The unique advantage of this system over the previous state-of-art is the independent leg speed control, which is required for multidirectional movement in VR. This system has the potential to contribute to VR gait rehab techniques. Creating biologically-inspired controllers has the potential to improve restorative robotics and allow people a better opportunity to recover lost functionality post-injury. Movement is the only way a person can interact with the world around them. When trauma to the neuromuscular systems disrupts the control of movement, quality of life suffers. To restore limb functionality, active robotic interventions and/or rehabilitation are required. Unfortunately, the primary obstacle in a person’s recovery is the limited robustness of the human-machine interfaces. Current systems rely on control approaches that rely on the person to learn how the system works instead of the system being more intuitive and working with the person naturally. My research goal is to design intuitive control mechanisms based on biological processes termed the biomimetic approach. I have applied this control scheme to problems with restorative robotics focused on the upper and lower limb control.Operating an advanced active prosthetic hand is a two-pronged problem of actuating a high-dimensional mechanism and controlling it with an intuitive interface. Our approach attempts to solve these problems by going from muscle activity, electromyography (EMG), to limb kinematics calculated through dynamic simulation of a musculoskeletal model. This control is more intuitive to the user because they attempt to move their hand naturally, and the prosthetic hand performs that movement. The key to this approach was validating simulated muscle paths using both experimental measurements and anatomical constraints where data is missing. After the validation, simulated muscle paths and forces are used to decipher the intended movement. After we have calculated the intended movement, we can move a prosthetic hand to match. This approach required minimal training to give an amputee the ability to control prosthetic hand movements, such as grasping. A more intuitive controller has the potential to improve how people interact and use their prosthetic hands.Similarly, the rehabilitation of the locomotor system in people with damaged motor pathways or missing limbs require appropriate interventions. The problem of decoding human motor intent in a treadmill walking task can be solved with a biomimetic approach. Estimated limb speed is essential for this approach according to the theoretical input-output computation performed by spinal central pattern generators (CPGs), which represents neural circuitry responsible for autonomous control of stepping. The system used the locomotor phases, swing and stance, to estimate leg speeds and enable self-paced walking as well as steering in virtual reality with congruent visual flow. The unique advantage of this system over the previous state-of-art is the independent leg speed control, which is required for multidirectional movement in VR. This system has the potential to contribute to VR gait rehab techniques.Creating biologically-inspired controllers has the potential to improve restorative robotics and allow people a better opportunity to recover lost functionality post-injury

Biomechanics of Prosthetic Knee Systems : Role of Dampening and Energy Storage Systems

One significant drawback of the commercial passive and microprocessored prosthetic devices, the inability of delivering positive energy when needed, is due to the absence of the knee flexion during stance phase. Moreover, consequences such as circumduction and disturbed gait pattern take place due to the improper energy flow at the knee and the absence of the positive energy delivery during the swing phase. Current generation powered design has solved these problems by delivering the needed energy with heavy battery demanding motors, which increase the mass of the device significantly. Hence, the gait quality of transfemoral amputees has not improved significantly in the last 50 years due to the inefficient energy flow distribution causing the patient to hike his/her pelvis, which leads to back pain in the long run. In this context, state-of-art prosthetics technology is trending toward creating energy regenerative devices, which are able to harvest/ return energy during ambulation by a spring mechanism, since a spring not only permits significant power demand reduction but also provides high power-to-weight ratio. This study will examine the sagittal plane knee moment versus knee flexion angle properties robotically, clinically and theoretically to explore the functional stiffness of a healthy knee as well as a prosthetic knee during the energy return and harvest phases of gait. With this intention, a prosthetic knee test method will be developed for investigating the torque-angle properties of the knee by iteratively modifying the hip trajectory until achieving the closest to healthy knee biomechanics by a 3-Degree of Freedom (DOF) Simulator. This research reveals that constant spring stiffness is suboptimal to varying gait requirements for different types of activity, due to the variability of the power requirements of the knee caused by the passive, viscous and elastic characteristics and the activation dependent properties of the muscles. Exploring this variation is crucial for the design of tran

Biomechanics of Prosthetic Knee Systems : Role of Dampening and Energy Storage Systems

One significant drawback of the commercial passive and microprocessored prosthetic devices, the inability of delivering positive energy when needed, is due to the absence of the knee flexion during stance phase. Moreover, consequences such as circumduction and disturbed gait pattern take place due to the improper energy flow at the knee and the absence of the positive energy delivery during the swing phase. Current generation powered design has solved these problems by delivering the needed energy with heavy battery demanding motors, which increase the mass of the device significantly. Hence, the gait quality of transfemoral amputees has not improved significantly in the last 50 years due to the inefficient energy flow distribution causing the patient to hike his/her pelvis, which leads to back pain in the long run. In this context, state-of-art prosthetics technology is trending toward creating energy regenerative devices, which are able to harvest/ return energy during ambulation by a spring mechanism, since a spring not only permits significant power demand reduction but also provides high power-to-weight ratio. This study will examine the sagittal plane knee moment versus knee flexion angle properties robotically, clinically and theoretically to explore the functional stiffness of a healthy knee as well as a prosthetic knee during the energy return and harvest phases of gait. With this intention, a prosthetic knee test method will be developed for investigating the torque-angle properties of the knee by iteratively modifying the hip trajectory until achieving the closest to healthy knee biomechanics by a 3-Degree of Freedom (DOF) Simulator. This research reveals that constant spring stiffness is suboptimal to varying gait requirements for different types of activity, due to the variability of the power requirements of the knee caused by the passive, viscous and elastic characteristics and the activation dependent properties of the muscles. Exploring this variation is crucial for the design of tran

An adaptive hybrid control architecture for an active transfemoral prosthesis

The daily usage of a prosthesis for people with an amputation consists of phases of intermittent and continuous walking patterns. Based on this observation, this paper introduces a novel hybrid architecture to control a transfemoral prosthesis, where separate algorithms are used depending on these two different types of movement. For intermittent walking, an interpolation-based algorithm generates control signals for the ankle and knee joints, whereas, for continuous walking, the control signals are generated utilizing an adaptive frequency oscillator. A switching strategy that allows for smooth transitioning from one controller to another is also presented in the design of the architecture. The individual algorithms for the generation of the joints angles’ references, along with the switching strategy were experimentally validated on a pilot test with a healthy subject wearing an able-bodied adapter and a designed transfemoral prosthesis. The results demonstrate the capability of the individual algorithms to generate the required control signals while undergoing smooth transitions when required. Through the use of a combination of interpolation and adaptive frequency oscillator-based methods, the controller also demonstrates its response adaptation capability to various walking speeds

An adaptive hybrid control architecture for an active transfemoral prosthesis

The daily usage of a prosthesis for people with an amputation consists of phases of intermittentand continuous walking patterns. Based on this observation, this paper introduces a novel hybrid architectureto control a transfemoral prosthesis, where separate algorithms are used depending on these two differenttypes of movement. For intermittent walking, an interpolation-based algorithm generates control signals forthe ankle and knee joints, whereas, for continuous walking, the control signals are generated utilizing anadaptive frequency oscillator. A switching strategy that allows for smooth transitioning from one controllerto another is also presented in the design of the architecture. The individual algorithms for the generation ofthe joints angles’ references, along with the switching strategy were experimentally validated on a pilottest with a healthy subject wearing an able-bodied adapter and a designed transfemoral prosthesis. Theresults demonstrate the capability of the individual algorithms to generate the required control signals whileundergoing smooth transitions when required. Through the use of a combination of interpolation and adaptivefrequency oscillator-based methods, the controller also demonstrates its response adaptation capability tovarious walking speeds

EMG-driven control in lower limb prostheses: a topic-based systematic review

Background The inability of users to directly and intuitively control their state-of-the-art commercial prosthesis contributes to a low device acceptance rate. Since Electromyography (EMG)-based control has the potential to address those inabilities, research has flourished on investigating its incorporation in microprocessor-controlled lower limb prostheses (MLLPs). However, despite the proposed benefits of doing so, there is no clear explanation regarding the absence of a commercial product, in contrast to their upper limb counterparts. Objective and methodologies This manuscript aims to provide a comparative overview of EMG-driven control methods for MLLPs, to identify their prospects and limitations, and to formulate suggestions on future research and development. This is done by systematically reviewing academical studies on EMG MLLPs. In particular, this review is structured by considering four major topics: (1) type of neuro-control, which discusses methods that allow the nervous system to control prosthetic devices through the muscles; (2) type of EMG-driven controllers, which defines the different classes of EMG controllers proposed in the literature; (3) type of neural input and processing, which describes how EMG-driven controllers are implemented; (4) type of performance assessment, which reports the performance of the current state of the art controllers. Results and conclusions The obtained results show that the lack of quantitative and standardized measures hinders the possibility to analytically compare the performances of different EMG-driven controllers. In relation to this issue, the real efficacy of EMG-driven controllers for MLLPs have yet to be validated. Nevertheless, in anticipation of the development of a standardized approach for validating EMG MLLPs, the literature suggests that combining multiple neuro-controller types has the potential to develop a more seamless and reliable EMG-driven control. This solution has the promise to retain the high performance of the currently employed non-EMG-driven controllers for rhythmic activities such as walking, whilst improving the performance of volitional activities such as task switching or non-repetitive movements. Although EMG-driven controllers suffer from many drawbacks, such as high sensitivity to noise, recent progress in invasive neural interfaces for prosthetic control (bionics) will allow to build a more reliable connection between the user and the MLLPs. Therefore, advancements in powered MLLPs with integrated EMG-driven control have the potential to strongly reduce the effects of psychosomatic conditions and musculoskeletal degenerative pathologies that are currently affecting lower limb amputees

Design and Implementation of the Powered Self-Contained AMPRO Prostheses

This thesis presents a complete methodology for translating robotic walking to powered prostheses, and demonstrates this framework on two novel custom built powered prostheses, AMPRO. Motivated by methods that have successfully generated dynamically stable walking gaits on bipedal robots, reference human locomotion data is collected via Inertial Measurement Units (IMU) and stable walking gaits are generated using the framework of human-inspired optimization and control. Next two novel transfemoral protheses are designed and custom built based on the understanding obtained from the collection of human data and gait generation. For experimental realization, the IMUs are mounted on the healthy human leg to estimate human intention during walking on-line, and serves as the feedback interaction point between human and prosthesis. The end result is the experimental verification of the proposed methodology in achieving stable and robust locomotion on a powered prosthesis. Furthermore it is concluded that reducing the weight of AMPRO I, through the design of AMPRO II, improves the performance of the prosthesis and comfort of the human subject