A new approach to a powered knee prosthesis: Layering powered assistance onto strictly passive prosthesis behavior

This article describes a novel approach to the control of a powered knee prosthesis where the control system provides passive behavior for most activities and then provides powered assistance only for those activities that require them. The control approach presented here is based on the categorization of knee joint function during activities into four behaviors: resistive stance behavior, active stance behavior, ballistic swing, and non-ballistic swing. The approach is further premised on the assumption that healthy non-perturbed swing-phase is characterized by a ballistic swing motion, and therefore, a replacement of that function should be similarly ballistic. The control system utilizes a six-state finite-state machine, where each state provides different constitutive behaviors (concomitant with the four aforementioned knee behaviors) which are appropriate for a range of activities. Transitions between states and torque control within states is controlled by user motion, such that the control system provides, to the extent possible, knee torque behavior as a reaction to user motion, including for powered behaviors. The control system is demonstrated on a novel device that provides a sufficiently low impedance to enable a strictly passive ballistic swing-phase, while also providing sufficiently high torque to offer powered stance-phase knee-extension during activities such as step-over stair ascent. Experiments employing the knee and control system on an individual with transfemoral amputation are presented that compare the functionality of the power-supplemented nominally passive system with that of a conventional passive microprocessor-controlled knee prosthesis

Gait Analysis Methods for Assessing Fall Risk in Older Adults with Unilateral Transfemoral Amputation

The risk of falling in older adults has been widely investigated among the able-bodied population but there is little evidence identifying fall risk among older adults who have a unilateral transfemoral amputation. Older adult amputees have a loss of muscular control at the ankle and knee joints in the prosthetic limb and decreased muscle strength in the sound limb from aging. Previous research has investigated minimum foot clearance (MFC) to understand the risk of tripping while walking, and results show MFC decreases with age in able-bodied individuals. Changes in MFC have not been examined for older adults with unilateral transfemoral amputation, and in general, the methods for determining MFC must be modified for deviations in amputee gait. The first objective of this thesis was to develop a methodology for identifying MFC in older adult unilateral transfemoral amputees while walking over a level surface and during stair ambulation. Comparisons were made between the prosthetic limb and sound limb. Six older adult unilateral transfemoral amputees completed multiple walking and stair ambulation trials. Results showed 4 of 6 subjects had smaller MFC with the prosthetic limb compared to the sound limb while walking over a level surface. During stair ascent and descent, horizontal clearance of the prosthetic foot with respect to the step edge was typically greater than the sound limb. The methodology developed in this thesis allowed for identification of MFC regardless of unilateral transfemoral amputee gait style. The second objective was to investigate stumble recovery following obstruction of the prosthetic limb during swing. Results showed an elevating recovery strategy yielded a shorter recovery duration and smaller trunk deviation in the sagittal and frontal planes in comparison to a lowering strategy. The final objective was to develop a geometric model of the prosthetic limb for determining the mass, center of mass, and mass moment of inertia of its segments. Published anthropometric methods for determining these inertial properties in able-bodied individuals are inaccurate due to the amputation. The developed geometric model of the prosthetic limb successfully produced the inertial properties, and the model results were comparable to direct measurements taken for each segment

Sensor-Based Adaptive Control and Optimization of Lower-Limb Prosthesis.

Recent developments in prosthetics have enabled the development of powered prosthetic ankles (PPA). The advent of such technologies drastically improved impaired gait by increasing balance and reducing metabolic energy consumption by providing net positive power. However, control challenges limit performance and feasibility of today’s devices. With addition of sensors and motors, PPA systems should continuously make control decisions and adapt the system by manipulating control parameters of the prostheses. There are multiple challenges in optimization and control of PPAs. A prominent challenge is the objective setup of the system and calibration parameters to fit each subject. Another is whether it is possible to detect changes in intention and terrain before prosthetic use and how the system should react and adapt to it. In the first part of this study, a model for energy expenditure was proposed using electromyogram (EMG) signals from the residual lower-limbs PPA users. The proposed model was optimized to minimize energy expenditure. Optimization was performed using a modified Nelder-Mead approach with a Latin Hypercube sampling. Results of the proposed method were compared to expert values and it was shown to be a feasible alternative for tuning in a shorter time. In the second part of the study, the control challenges regarding lack of adaptivity for PPAs was investigated. The current PPA system used is enhanced with impedance-controlled parameters that allow the system to provide different assistance. However, current systems are set to a fixed value and fail to acknowledge various terrain and intentions throughout the day. In this study, a pseudo-real-time adaptive control system was proposed to predict the changes in the gait and provide a smoother gait. The proposed control system used physiological, kinetic, and kinematic data and fused them to predict the change. The prediction was done using machine learning-based methods. Results of the study showed an accuracy of up to 89.7 percent for prediction of change for four different cases

Evaluation of transfemoral prosthesis performance control using artificial neural network controllers

Transfemoral (Above-knee) amputation of the leg of an individual as a result of traumatic injury or due to complications arising out of diabetes or vascular disorders is a common occurrence worldwide. Following the surgical amputation procedure, the subject is fitted with prosthetic leg to help regain mobility. Prosthetic sockets are designed to transfer the body weight to the leg during locomotion. During normal human gait, the lower limbs perform four major functions: balance, positioning, support, and power. Prosthetic legs currently available in the market are mostly passive devices that provide limited support and functionality during walking. These devices also have limited adaptability during walking or to enable a more active lifestyle. The common problems of the existing above-knee prosthesis for the unilateral amputees include asymmetry between motion of the prosthetic leg with the intact leg, reduced speed along with increased energy expenditure. Not only that, but there are also different types of forces, counter forces and errors associated with gait which was ignored in some active prosthesis designs. If these technical problems are left un-addressed, they may end up with secondary medical issues requiring further surgery. While it is desirable for the prosthetic limb to have similar or close efficiency or tracking to the intact limb, it is more important for the prosthetic leg to be able to replicate the movement of a normal human leg as much as possible. Most of the studies earlier were limited to pathological gait tests in laboratory environments using inertial sensor/motion trackers which restricted the mobility of the individuals. Recently, smarter data acquisition systems are designed to capture the human locomotion in an easier and effective way. Combination of these factors result in greater advancement of prosthetic research. Prior research in lower-limb amputee gait has focused mostly trans-tibial (below knee) amputees as they are the highest in number. In general, available prostheses for people with lower limb amputation are primarily passive devices whose performance cannot be adjusted or optimized to meet the requirements of different users. The adverse complications of wearing poorly functioning prosthetic devices include asymmetric gait, increased metabolic energy consumption, limited blood flow, instability, sores, and joint pain. The amputees might have to undergo further joint (knee/hip) replacement procedure and that increases the chance of the increased number of trans femoral amputee in the long run. There exists a high and increasing demand for an advanced prosthetic foot that is comfortable and able to replicate the function of the biological foot. Trans-femoral amputees are the second highest and the research is more challenging as the amputees lost two of their vital joints (ankle and knee). So, to design an efficient prosthetic ankle-knee system, (including all the challenges for transtibial amputees) it is very important to consider the coupling effects of the two joints and different associated errors, or force associated with the gait like ground reaction force. Currently available prosthetic knees are either simple mechanical hinges or sophisticated computer controlled. Development of active powered prosthetic knees (focused on the control with little emphasis) results in uncomfortable, low efficient, low energy consuming device. The inherent nonlinearities of the actuators make it difficult to control. Again, interaction forces between residual limb and the socket are dynamic in nature and are a result of gait pattern of individuals, interaction of the feet with the terrain, and the transfer of rest of the body weight during gait. These factors made the prosthetic device control and design advancement challenging for researchers. Earlier literatures address assessing gait symmetry, movement of the healthy joints, activities of the residual muscles and the metabolic energy consumption in individuals who had undergone traditional amputation. There were research studies done showing considerable residual muscle activity in the transtibial and transfemoral amputees and minimal or random muscle activity based on the co-relation between residuum socket interface (RSI) force and EMG to the type of gait. These forces are a source of interest for researchers to investigate for better controlling. Adaptive controllers like PD, PID and combinations are used in the development of active prosthetic devices. But PID and other traditional adaptive controllers cannot handle these nonlinearities and challenges of human locomotion properly. Moreover, most of the designs do not have consistent performance over the total gait cycle or consecutive steps. All prostheses require some sort of stability mechanism, either manual or a weight-activated locking system. The main joints made of mechanical hinges should control the flexion and extension motion to mimic human gait. For unilateral amputee, the development of Artificial optimized neural network controller is important in this regard as it can train the neurons with the input data from the intact leg and mimic similar trajectory for the residual limb to follow. This dissertation addresses the limitations of traditional controllers in an orderly fashion by building a strong platform to develop intelligent knee-ankle prosthesis system. The following are the key steps adopted in this dissertation. • First, a mathematical model will be developed for a leg movement during normal gait. Algorithms for gait analysis will be developed to study the gait of people with above-knee amputation in real time during work-related activities. Simulations will be done to observe the performance of the controller. • A more reliable and realistic learning-based control strategy will be developed to adaptively compensate for the unknown, changing ankle-knee dynamics and drive the prosthetic ankle-knee joint along the desired trajectories. Different combinations of control parameters will be changed to see the performance improvement and error reduction. Comparative results will be shown for different controllers. • Finally, a framework for experimental transfemoral amputee gait study will be proposed to collect data using force sensors and EMG sensors attached to the residual limbs and muscles during work related activities and normal gait. It is anticipated that the learning capabilities of the control strategies will enable the prosthetic ankle-knee joints to not only replicate the movement of the healthy knee-ankle system, but also improve the stability of the gait and optimize the performance to a great extent. Learning-based control of the prosthetic ankle-knee joint algorithms used here consider the ankle-knee dynamics, foot-ground interaction, and the movement of the rest of the body to make it appropriate to be used for transfemoral unilateral amputee. The first strategy uses an artificial neural network-based controller to learn the unknown and changing dynamics of the ankle-knee joint and to track a desired ankle knee displacement profile. In the subsequent strategies, the neural dynamic programming-based controller is improvised by increasing the number of neurons and other parameters, comparative performance was shown for two joints also. Later a centralized controller is used to control both the joints. Additional PID is used and comparative analysis between controller schemes are presented to have a balanced and better control. Actual gait data (obtained from the healthy human subjects) of this dissertation is used to study the effectiveness of the controller. It will be interesting to see the performance of the adaptive neural network controller for unilateral transfemoral amputee with changes in terrain and in user requirements. It is anticipated that the strategy developed in this dissertation will help build an intelligent prosthetic system that can significantly improve the mobility and long-term health of people with lower limb amputation followed by proper rehabilitation

Development of a knee prosthesis powered by electro-hydrostatic actuation

L'abstract è presente nell'allegato / the abstract is in the attachmen

Biomechanical risk factors and reduced bone health in lower limb amputees

Bone constantly adapts to its surroundings through the formation and resorption of material, controlled by bone modelling and remodelling. Strains produced by mechanical loading are one factor that drive these processes and thus determine bone health. Lower limb amputees (LLA) adopt an asymmetrical movement pattern to compensate for the loss of a limb, resulting in a change in mechanical loading and subsequently a degradation in bone health. The aetiology of the majority of amputations is vascular diseases, which affect bone health. Therefore, it is not clear whether the asymmetrical loading, or comorbidities cause the degradation in bone health in LLA. Finite element models (FEM) are used to generate strain plots and predict the bone's response to mechanical loading. To understand the relationship between the degradation in bone health and asymmetrical loads in LLAs the asymmetrical loads can be applied to a healthy bone using FEMs, or simulated within a healthy population using restrictive devices. Therefore, the overall aim was to investigate the relationship between asymmetrical loading, as observed in LLA’s, and bone health, through the use of semi-subject specific FEMs and restrictive lower limb devices. Study one established a novel image processing method to convert peripheral quantative computed tomography (pQCT) scan images into binary and segment the tibia. The outer perimeter of the tibia was identified and sectioned to produce landmarks. The outer geometry landmarks were used to morph a base FEM, constructed from open source scan images to create semi-subject tibia FEM. Study two applied subject-specific joint reaction and muscle forces to the semi-subject tibia FEM. The strain plots output from Study two were validated against longitudinal geometrical changes from Study three. Study three, used 3D motion capture, pQCT and dual energy x-ray absorptiometry (DXA) to investigate gait and tibial geometry within a lower limb amputee and able-bodied population across twelve months. The coefficient of variation (CV) for able bodied subjects was less than 10% for ground reaction force (GRF) in level walking and less than 4% for bone total area. Study four, used a rigid foot orthosis and a trans-femoral prosthesis, to restrict able-bodied gait. Results showed participants walked significantly slower (p<0.01) in the restricted conditions, with a longer non-restricted step length (p<0.001). The loading rate and maximum GRF were higher in the non-restricted limb (p<0.05). Larger knee adductor moments were shown in the un-restricted leg in the trans-tibial condition (p<0.05). This thesis presents a novel method of constructing semi-subject specific FEMs from pQCT scans. This can be used to further investigate the link between asymmetrical loading and bone health in LLA's and other populations with asymmetrical gait. The use of restrictive devices allow investigation into LLA's specifically, without the interference of prosthetic variability, or comorbidities

Improving Intelligence of Robotic Lower-Limb Prostheses to Enhance Mobility for Individuals with Limb Loss

The field of wearable robotics is an emerging field that seeks to create smarter and intuitive devices that can assist users improve their overall quality of life. Specifically, individuals with lower limb amputation tend to have significantly impaired mobility and asymmetric gait patterns that result in increased energy expenditure than able-bodied individuals over a variety of tasks. Unfortunately, most of the commercial devices are passive and lack the ability to easily adapt to changing environmental contexts. Powered prostheses have shown promise to help restore the necessary power needed to walk in common ambulatory tasks. However, there is a need to infer/detect the user's movement to appropriately provide seamless and natural assistance. To achieve this behavior, a better understanding is required of adding intelligence to powered prostheses. This dissertation focuses on three key research objectives: 1) developing and enhancing offline intent recognition systems for both classification and regression tasks using embedded prosthetic mechanical sensors and machine learning, 2) deploying intelligent controllers in real-time to directly modulate assistive torque in a knee and ankle prosthetic device, and 3) quantifying the biomechanical and clinical effects of a powered prosthesis compared to a passive device. The findings conducted show improvement in developing powered prostheses to better enhance mobility for individuals with transfemoral amputation and show a step forward towards clinical acceptance.Ph.D

Use of stance control knee-ankle-foot orthoses : a review of the literature

The use of stance control orthotic knee joints are becoming increasingly popular as unlike locked knee-ankle-foot orthoses, these joints allow the limb to swing freely in swing phase while providing stance phase stability, thus aiming to promote a more physiological and energy efficient gait. It is of paramount importance that all aspects of this technology is monitored and evaluated as the demand for evidence based practice and cost effective rehabilitation increases. A robust and thorough literature review was conducted to retrieve all articles which evaluated the use of stance control orthotic knee joints. All relevant databases were searched, including The Knowledge Network, ProQuest, Web of Knowledge, RECAL Legacy, PubMed and Engineering Village. Papers were selected for review if they addressed the use and effectiveness of commercially available stance control orthotic knee joints and included participant(s) trialling the SCKAFO. A total of 11 publications were reviewed and the following questions were developed and answered according to the best available evidence: 1. The effect SCKAFO (stance control knee-ankle-foot orthoses) systems have on kinetic and kinematic gait parameters 2. The effect SCKAFO systems have on the temporal and spatial parameters of gait 3. The effect SCKAFO systems have on the cardiopulmonary and metabolic cost of walking. 4. The effect SCKAFO systems have on muscle power/generation 5. Patient’s perceptions/ compliance of SCKAFO systems Although current research is limited and lacks in methodological quality the evidence available does, on a whole, indicate a positive benefit in the use of SCKAFOs. This is with respect to increased knee flexion during swing phase resulting in sufficient ground clearance, decreased compensatory movements to facilitate swing phase clearance and improved temporal and spatial gait parameters. With the right methodological approach, the benefits of using a SCKAFO system can be evidenced and the research more effectively converted into clinical practice