Control and Evaluation of a Powered Transfemoral Prosthesis for Stair Ascent

Data-Driven Phase-Based Control of a Powered Knee-Ankle Prosthesis for Variable-Incline Stair Ascent and Descent

Powered knee-ankle prostheses can offer benefits over conventional passive devices during stair locomotion by providing biomimetic net-positive work and active control of joint angles. However, many modern control approaches for stair ascent and descent are often limited by time-consuming hand-tuning of user/task-specific parameters, predefined trajectories that remove user volition, or heuristic approaches that cannot be applied to both stair ascent and descent. This work presents a phase-based hybrid kinematic and impedance controller (HKIC) that allows for semi-volitional, biomimetic stair ascent and descent at a variety of step heights. We define a unified phase variable for both stair ascent and descent that utilizes lower-limb geometry to adjust to different users and step heights. We extend our prior data-driven impedance model for variable-incline walking, modifying the cost function and constraints to create a continuously-varying impedance parameter model for stair ascent and descent over a continuum of step heights. Experiments with above-knee amputee participants (N=2) validate that our HKIC controller produces biomimetic ascent and descent joint kinematics, kinetics, and work across four step height configurations. We also show improved kinematic performance with our HKIC controller in comparison to a passive microprocessor-controlled device during stair locomotion.

Toward the Development of User-Centered Neurointegrated Lower Limb Prostheses

The last few years witnessed radical improvements in lower-limb prostheses. Researchers have presented innovative solutions to overcome the limits of the first generation of prostheses, refining specific aspects which could be implemented in future prostheses designs. Each aspect of lower-limb prostheses has been upgraded, but despite these advances, a number of deficiencies remain and the most capable limb prostheses fall far short of the capabilities of the healthy limb. This article describes the current state of prosthesis technology; identifies a number of deficiencies across the spectrum of lower limb prosthetic components with respect to users' needs; and discusses research opportunities in design and control that would substantially improve functionality concerning each deficiency. In doing so, the authors present a roadmap of patients related issues that should be addressed in order to fulfill the vision of a next-generation, neurally-integrated, highly-functional lower limb prosthesis.

A Scientometric Analysis and Visualization of Prosthetic Foot Research Work: 2000 to 2022

This study aims to highlight recent research work on topics around prosthetic feet through a scientometric analysis and historical review. The most cited publications from the Clarivate Analytics Web of Science Core Collection database were identified and analyzed from 1 January 2000 to 31 October 2022. Original articles, reviews with full manuscripts, conference proceedings, early access documents, and meeting abstracts were included. A scientometric visualization analysis of the bibliometric information related to the publications, including the countries, institutions, journals, references, and keywords, was conducted. A total of 1827 publications met the search criteria in this study. The related publications grouped by year show an overall trend of increase during the two decades from 2000 to 2022. The United States is ranked first in terms of overall influence in this field (n = 774). The Northwestern University has published the most papers on prosthetic feet (n = 84). Prosthetics and Orthotics International has published the largest number of studies on prosthetic feet (n = 151). During recent years, a number of studies with citation bursts and burst keywords (e.g., diabetes, gait, pain, and sensor) have provided clues on the hotspots of prosthetic feet and prosthetic foot trends. The findings of this study are based on a comprehensive analysis of the literature and highlight the research topics on prosthetic feet that have been primarily explored. The data provide guidance to clinicians and researchers to further studies in this field.

Towards Personalized Control for Powered Knee Prostheses: Continuous Impedance Functions and PCA-Based Tuning Method

Optimizing control parameters is crucial for personalizing prosthetic devices. The current method of finite state machine impedance control (FSM-IC) allows interaction with the user but requires time-consuming manual tuning. To improve efficiency, we propose a novel approach for tuning knee prostheses using continuous impedance functions (CIFs) and Principal Component Analysis (PCA). The CIFs, which represent stiffness, damping, and equilibrium angle, are modeled as fourth-order polynomials and optimized through convex optimization. By applying PCA to the CIFs, we extract principal components (PCs) that capture common features. The weights of these PCs serve as tuning parameters, allowing us to reconstruct various impedance functions. We validated this approach using data from 10 able-bodied individuals walking. The contributions of this study include: i) generating CIFs via convex optimization; ii) introducing a new tuning space based on the obtained CIFs; and iii) evaluating the feasibility of this tuning space.

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.

Powered knee and ankle prosthesis use with a K2 level ambulator: a case report

Powered prosthetic knees and ankles have the capability of restoring power to the missing joints and potential to provide increased functional mobility to users. Nearly all development with these advanced prostheses is with individuals who are high functioning community level ambulators even though limited community ambulators may also receive great benefit from these devices. We trained a 70 year old male participant with a unilateral transfemoral amputation to use a powered knee and powered ankle prosthesis. He participated in eight hours of therapist led in-lab training (two hours per week for four weeks). Sessions included static and dynamic balance activities for improved stability and comfort with the powered prosthesis and ambulation training on level ground, inclines, and stairs. Assessments were taken with both the powered prosthesis and his prescribed, passive prosthesis post-training. Outcome measures showed similarities in velocity between devices for level-ground walking and ascending a ramp. During ramp descent, the participant had a slightly faster velocity and more symmetrical stance and step times with the powered prosthesis compared to his prescribed prosthesis. For stairs, he was able to climb with reciprocal stepping for both ascent and descent, a stepping strategy he is unable to do with his prescribed prosthesis. More research with limited community ambulators is necessary to understand if further functional improvements are possible with either additional training, longer accommodation periods, and/or changes in powered prosthesis control strategies.

Data-Driven Variable Impedance Control of a Powered Knee-Ankle Prosthesis for Adaptive Speed and Incline Walking

Most impedance-based walking controllers for powered knee-ankle prostheses use a finite state machine with dozens of user-specific parameters that require manual tuning by technical experts. These parameters are only appropriate near the task (e.g., walking speed and incline) at which they were tuned, necessitating many different parameter sets for variable-task walking. In contrast, this paper presents a data-driven, phase-based controller for variable-task walking that uses continuously-variable impedance control during stance and kinematic control during swing to enable biomimetic locomotion. After generating a data-driven model of variable joint impedance with convex optimization, we implement a novel task-invariant phase variable and real-time estimates of speed and incline to enable autonomous task adaptation. Experiments with above-knee amputee participants (N=2) show that our data-driven controller 1) features highly-linear phase estimates and accurate task estimates, 2) produces biomimetic kinematic and kinetic trends as task varies, leading to low errors relative to able-bodied references, and 3) produces biomimetic joint work and cadence trends as task varies. We show that the presented controller meets and often exceeds the performance of a benchmark finite state machine controller for our two participants, without requiring manual impedance tuning.

Can a powered knee-ankle prosthesis improve weight-bearing symmetry during stand-to-sit transitions in individuals with above-knee amputations?

BACKGROUND

After above-knee amputation, the missing biological knee and ankle are replaced with passive prosthetic devices. Passive prostheses are able to dissipate limited amounts of energy using resistive damper systems during "negative energy" tasks like sit-down. However, passive prosthetic knees are not able to provide high levels of resistance at the end of the sit-down movement when the knee is flexed, and users need the most support. Consequently, users are forced to over-compensate with their upper body, residual hip, and intact leg, and/or sit down with a ballistic and uncontrolled movement. Powered prostheses have the potential to solve this problem. Powered prosthetic joints are controlled by motors, which can produce higher levels of resistance at a larger range of joint positions than passive damper systems. Therefore, powered prostheses have the potential to make sitting down more controlled and less difficult for above-knee amputees, improving their functional mobility.

METHODS

Ten individuals with above-knee amputations sat down using their prescribed passive prosthesis and a research powered knee-ankle prosthesis. Subjects performed three sit-downs with each prosthesis while we recorded joint angles, forces, and muscle activity from the intact quadricep muscle. Our main outcome measures were weight-bearing symmetry and muscle effort of the intact quadricep muscle. We performed paired t-tests on these outcome measures to test for significant differences between passive and powered prostheses.

RESULTS

We found that the average weight-bearing symmetry improved by 42.1% when subjects sat down with the powered prosthesis compared to their passive prostheses. This difference was significant (p = 0.0012), and every subject's weight-bearing symmetry improved when using the powered prosthesis. Although the intact quadricep muscle contraction differed in shape, neither the integral nor the peak of the signal was significantly different between conditions (integral p > 0.01, peak p > 0.01).

CONCLUSIONS

In this study, we found that a powered knee-ankle prosthesis significantly improved weight-bearing symmetry during sit-down compared to passive prostheses. However, we did not observe a corresponding decrease in intact-limb muscle effort. These results indicate that powered prosthetic devices have the potential to improve balance during sit-down for individuals with above-knee amputation and provide insight for future development of powered prosthetics.

A Review of Current State-of-the-Art Control Methods for Lower-Limb Powered Prostheses

Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb amputations. While the design of lower-limb prostheses is important, this paper focuses on the complementary challenge - the control of lower-limb prostheses. Specifically, we focus on powered prostheses, a subset of lower-limb prostheses, which utilize actuators to inject mechanical power into the walking gait of a human user. In this paper, we present a review of existing control strategies for lower-limb powered prostheses, including the control objectives, sensing capabilities, and control methodologies. We separate the various control methods into three main tiers of prosthesis control: high-level control for task and gait phase estimation, mid-level control for desired torque computation (both with and without the use of reference trajectories), and low-level control for enforcing the computed torque commands on the prosthesis. In particular, we focus on the high- and mid-level control approaches in this review. Additionally, we outline existing methods for customizing the prosthetic behavior for individual human users. Finally, we conclude with a discussion on future research directions for powered lower-limb prostheses based on the potential of current control methods and open problems in the field.

Advances in additive manufacturing processes and their use for the fabrication of lower limb prosthetic devices

INTRODUCTION

Traditional methods of prosthesis fabrication are not efficient and user centric and are made for common purposes without focusing on individual demands of user which leads to rejection of prosthesis for long-term use. Utilizing advanced additive manufacturing techniques for fabrication of prosthesis makes the development process user centric and covers all the user demands thus providing better fit, comfort, and more stable gait rehabilitation for the user.

AREAS COVERED

The articles reporting fabrication of lower limb prosthesis and its socket are included in the study. Standard fabrication and additive manufacturing method are both systematically assessed by the reviewers. The review also covers the advanced methods of additive manufacturing that are presently being used for fabrication of rehabilitation devices.

EXPERT OPINION

Additive manufacturing method of fabrication of prosthesis provides more flexibility for manufacturing prosthesis parts as per demand of the user. The fabrication method takes into account the residual limb and thus makes the prosthesis user-specific providing better comfort and fit.

A Primarily-Passive Knee Prosthesis with Powered Stance and Swing Assistance

This paper describes a knee prosthesis that provides primarily-passive behavior akin to a state-of-the-art modulated passive microprocessor-controlled knee prosthesis (MPK), but also offers powered stance and swing assistance, which are layered on top of the passive functionality. The combination of both passive and powered behaviors is enabled by a unique electronically-selectable two-speed transmission, which enables the combination of very low output impedance and high resistive torques necessary for passive functionality, while also enabling the generative torque-speed characteristics suitable for stance and swing phase assistance. A control system is described that consolidates behaviors appropriate for a wide range of activities of daily living (ADLs) into six states, with each state providing adaptive torque behaviors appropriate for different phases of gait, whether powered or passive. Experimental results on an individual with transfemoral amputation suggest that the prosthesis and controller provide similar or improved passive behaviors relative to a commercially-available MPK, in addition to providing powered functionality commensurate with a powered prosthesis.

Powered Knee and Ankle Prosthesis with Adaptive Control Enables Climbing Stairs with Different Stair Heights, Cadences, and Gait Patterns

Powered prostheses can enable individuals with above-knee amputations to ascend stairs step-over-step. To accomplish this task, available stair ascent controllers impose a pre-defined joint impedance behavior or follow a pre-programmed position trajectory. These control approaches have proved successful in the laboratory. However, they are not robust to changes in stair height or cadence, which is essential for real-world ambulation. Here we present an adaptive stair ascent controller that enables individuals with above-knee amputations to climb stairs of varying stair heights at their preferred cadence and with their preferred gait pattern. We found that modulating the prosthesis knee and ankle position as a function of the user's thigh in swing provides toe clearance for varying stair heights. In stance, modulating the torque-angle relationship as a function of the prosthesis knee position at foot contact provides sufficient torque assistance for climbing stairs of different heights. Furthermore, the proposed controller enables individuals to climb stairs at their preferred cadence and gait pattern, such as step-by-step, step-over-step, and two-steps. The proposed adaptive stair controller may improve the robustness of powered prostheses to environmental and human variance, enabling powered prostheses to more easily move from the lab to the real-world.

Stair Ascent Phase-Variable Control of a Powered Knee-Ankle Prosthesis

Passive prostheses cannot provide the net positive work required at the knee and ankle for step-over stair ascent. Powered prostheses can provide this net positive work, but user synchronization of joint motion and power input are critical to enabling natural stair ascent gaits. In this work, we build on previous phase variable-based control methods for walking and propose a stair ascent controller driven by the motion of the user's residual thigh. We use reference kinematics from an able-bodied dataset to produce knee and ankle joint trajectories parameterized by gait phase. We redefine the gait cycle to begin at the point of maximum hip flexion instead of heel strike to improve the phase estimate. Able-bodied bypass adapter experiments demonstrate that the phase variable controller replicates normative able-bodied kinematic trajectories with a root mean squared error of 12.66° and 2.64° for the knee and ankle, respectively. The knee and ankle joints provided on average 0.39 J/kg and 0.21 J/kg per stride, compared to the normative averages of 0.34 J/kg and 0.21 J/kg, respectively. Thus, this controller allows powered knee-ankle prostheses to perform net positive mechanical work to assist stair ascent.

Locomotion Mode Transition Prediction Based on Gait-Event Identification Using Wearable Sensors and Multilayer Perceptrons

People walk on different types of terrain daily; for instance, level-ground walking, ramp and stair ascent and descent, and stepping over obstacles are common activities in daily life. Movement patterns change as people move from one terrain to another. The prediction of transitions between locomotion modes is important for developing assistive devices, such as exoskeletons, as the optimal assistive strategies may differ for different locomotion modes. The prediction of locomotion mode transitions is often accompanied by gait-event detection that provides important information during locomotion about critical events, such as foot contact (FC) and toe off (TO). In this study, we introduce a method to integrate locomotion mode prediction and gait-event identification into one machine learning framework, comprised of two multilayer perceptrons (MLP). Input features to the framework were from fused data from wearable sensors—specifically, electromyography sensors and inertial measurement units. The first MLP successfully identified FC and TO, FC events were identified accurately, and a small number of misclassifications only occurred near TO events. A small time difference (2.5 ms and −5.3 ms for FC and TO, respectively) was found between predicted and true gait events. The second MLP correctly identified walking, ramp ascent, and ramp descent transitions with the best aggregate accuracy of 96.3%, 90.1%, and 90.6%, respectively, with sufficient prediction time prior to the critical events. The models in this study demonstrate high accuracy in predicting transitions between different locomotion modes in the same side’s mid- to late stance of the stride prior to the step into the new mode using data from EMG and IMU sensors. Our results may help assistive devices achieve smooth and seamless transitions in different locomotion modes for those with motor disorders.

Effect of a Swing-Assist Knee Prosthesis on Stair Ambulation

This paper describes stair ambulation control and functionality of a semi-powered knee prosthesis that supplements nominally passive prosthesis behavior with swing-phase assistance. A set of stair ascent and descent controllers are described. The controllers were implemented in a semi-powered prosthesis prototype, and the prospective benefits of swing assist in stair ambulation were assessed on a group of three participants with unilateral, transfemoral amputation, relative to their respective daily-use prostheses. Results indicate that ambulation with the semi-powered knee resulted in improved stair ascent gait symmetry when compared to the participants' passive daily-use devices, and increased similitude to healthy stair ascent movement.

Design and Validation of a Powered Knee-Ankle Prosthesis with High-Torque, Low-Impedance Actuators

We present the design of a powered knee-ankle prosthetic leg, which implements high-torque actuators with low-reduction transmissions. The transmission coupled with a high-torque and low-speed motor creates an actuator with low mechanical impedance and high backdrivability. This style of actuation presents several possible benefits over modern actuation styles in emerging robotic prosthetic legs, which include free-swinging knee motion, compliance with the ground, negligible unmodeled actuator dynamics, less acoustic noise, and power regeneration. Benchtop tests establish that both joints can be backdriven by small torques (~1-3 Nm) and confirm the small reflected inertia. Impedance control tests prove that the intrinsic impedance and unmodeled dynamics of the actuator are sufficiently small to control joint impedance without torque feedback or lengthy tuning trials. Walking experiments validate performance under the designed loading conditions with minimal tuning. Lastly, the regenerative abilities, low friction, and small reflected inertia of the presented actuators reduced power consumption and acoustic noise compared to state-of-art powered legs.

Lower limb joint biomechanics-based identification of gait transitions in between level walking and stair ambulation

Lower limb exoskeletons and lower limb prostheses have the potential to reduce gait limitations during stair ambulation. To develop robotic assistance devices, the biomechanics of stair ambulation and the required transitions to level walking have to be understood. This study aimed to identify the timing of these transitions, to determine if transition phases exist and how long they last, and to investigate if there exists a joint-related order and timing for the start and end of the transitions. Therefore, this study analyzed the kinematics and kinetics of both transitions between level walking and stair ascent, and between level walking and stair descent (12 subjects, 25.4 yrs, 74.6 kg). We found that transitions primarily start within the stance phase and end within the swing phase. Transition phases exist for each limb, all joints (hip, knee, ankle), and types of transitions. They have a mean duration of half of one stride and they do not last longer than one stride. The duration of the transition phase for all joints of a single limb in aggregate is less than 35% of one stride in all but one case. The distal joints initialize stair ascent, while the proximal joints primarily initialize the stair descent transitions. In general, the distal joints complete the transitions first. We believe that energy- and balance-related processes are responsible for the joint-specific transition timing. Regarding the existence of a transition phase for all joints and transitions, we believe that lower limb exoskeleton or prosthetic control concepts should account for these transitions in order to improve the smoothness of the transition and to thus increase the user comfort, safety, and user experience. Our gait data and the identified transition timings can provide a reference for the design and the performance of stair ambulation- related control concepts.

Wearer-Prosthesis Interaction for Symmetrical Gait: A Study Enabled by Reinforcement Learning Prosthesis Control

With advances in robotic prostheses, rese-archers attempt to improve amputee's gait performance (e.g., gait symmetry) beyond restoring normative knee kinematics/kinetics. Yet, little is known about how the prosthesis mechanics/control influence wearer-prosthesis' gait performance, such as gait symmetry, stability, etc. This study aimed to investigate the influence of robotic transfemoral prosthesis mechanics on human wearers' gait symmetry. The investigation was enabled by our previously designed reinforcement learning (RL) supplementary control, which simultaneously tuned 12 control parameters that determined the prosthesis mechanics throughout a gait cycle. The RL control design facilitated safe explorations of prosthesis mechanics with the human in the loop. Subjects were recruited and walked with a robotic transfemoral prosthesis on a treadmill while the RL controller tuned the control parameters. Stance time symmetry, step length symmetry, and bilateral anteroposterior (AP) impulses were measured. The data analysis showed that changes in robotic knee mechanics led to movement variations in both lower limbs and therefore gait temporal-spatial symmetry measures. Consistent across all the subjects, inter-limb AP impulse measurements explained gait symmetry: the stance time symmetry was significantly correlated with the net inter-limb AP impulse, and the step length symmetry was significantly correlated with braking and propulsive impulse symmetry. The results suggest that it is possible to personalize transfemoral prosthesis control for improved temporal-spatial gait symmetry. However, adjusting prosthesis mechanics alone was insufficient to maximize the gait symmetry. Rather, achieving gait symmetry may require coordination between the wearer's motor control of the intact limb and adaptive control of the prosthetic joints. The results also indicated that the RL-based prosthesis tuning system was a potential tool for studying wearer-prosthesis interactions.

Techniques for Improving the Reliability of Prosthesis Wearer Muscle Signals Using Pressure and EMG Sensors

In this study, we propose a technique to increase the reliability of muscle signals in case of weak muscle signal measurements using pressure sensors in a prosthesis wearer for measuring the degree of contraction of the muscle. This technique is applied when determining the intention of the wearer of an intelligent prosthesis. Through this technique, it is possible to determine the intention of a prosthesis wearer, which was previously not possible.

Preliminary Design of an Environment Recognition System for Controlling Robotic Lower-Limb Prostheses and Exoskeletons

Drawing inspiration from autonomous vehicles, using future environment information could improve the control of wearable biomechatronic devices for assisting human locomotion. To the authors knowledge, this research represents the first documented investigation using machine vision and deep convolutional neural networks for environment recognition to support the predictive control of robotic lower-limb prostheses and exoskeletons. One participant was instrumented with a battery-powered, chest-mounted RGB camera system. Approximately 10 hours of video footage were experimentally collected while ambulating throughout unknown outdoor and indoor environments. The sampled images were preprocessed and individually labelled. A deep convolutional neural network was developed and trained to automatically recognize three walking environments: level-ground, incline staircases, and decline staircases. The environment recognition system achieved 94.85% overall image classification accuracy. Extending these preliminary findings, future research should incorporate other environment classes (e.g., incline ramps) and integrate the environment recognition system with electromechanical sensors and/or surface electromyography for automated locomotion mode recognition. The challenges associated with implementing deep learning on wearable biomechatronic devices are discussed.

Impedance Control Strategies for Enhancing Sloped and Level Walking Capabilities for Individuals with Transfemoral Amputation Using a Powered Multi-Joint Prosthesis

INTRODUCTION

Powered prostheses are a promising new technology that may help people with lower-limb loss improve their ability to perform locomotion tasks. Developing active prostheses requires robust design methodologies and intelligent controllers to appropriately provide assistance to the user for varied tasks in different environments. The purpose of this study was to validate an impedance control strategy for a powered knee and ankle prosthesis using an embedded sensor suite of encoders and a six-axis load cell that would aid an individual in performing common locomotion tasks, such as level walking and ascending/descending slopes.

MATERIALS AND METHODS

Three amputees walked on a treadmill and four amputees walked on a ramp circuit to test whether a dual powered knee and ankle prosthesis could generate appropriate device joint kinematics across users.

RESULTS

Investigators found that tuning 2-3 subject-specific parameters per ambulation mode was necessary to render individualized assistance. Furthermore, the kinematic profiles demonstrate invariance to walking speeds ranging from 0.63 to 1.07 m/s and incline/decline angles ranging from 7.8° to 14°.

CONCLUSION

This work presents a strategy that requires minimal tuning for a powered knee & ankle prosthesis that scales across a nominal range of both walking speeds and ramp slopes.

Effects of extended powered knee prosthesis stance time via visual feedback on gait symmetry of individuals with unilateral amputation: a preliminary study

BACKGROUND

Establishing gait symmetry is a major aim of amputee rehabilitation and may be more attainable with powered prostheses. Though, based on previous work, we postulate that users transfer a previously-learned motor pattern across devices, limiting the functionality of more advanced prostheses. The objective of this study was to preliminarily investigate the effect of increased stance time via visual feedback on amputees' gait symmetry using powered and passive knee prostheses.

METHODS

Five individuals with transfemoral amputation or knee disarticulation walked at their self-selected speed on a treadmill. Visual feedback was used to promote an increase in the amputated-limb stance time. Individuals were fit with a commercially-available powered prosthesis by a certified prosthetist and practiced walking during a prior visit. The same protocol was completed with a passive knee and powered knee prosthesis on separate days. We used repeated-measures, two-way ANOVA (alpha = 0.05) to test for significant effects of the feedback and device factors. Our main outcome measures were stance time asymmetry, peak anterior-posterior ground reaction forces, and peak anterior propulsion asymmetry.

RESULTS

Increasing the amputated-limb stance time via visual feedback significantly improved the stance time symmetry (p = 0.012) and peak propulsion symmetry (p = 0.036) of individuals walking with both prostheses. With the powered knee prosthesis, the highest feedback target elicited 36% improvement in stance time symmetry, 22% increase in prosthesis-side peak propulsion, and 47% improvement in peak propulsion symmetry compared to a no feedback condition. The changes with feedback were not different with the passive prosthesis, and the main effects of device/ prosthesis type were not statistically different. However, subject by device interactions were significant, indicating individuals did not respond consistently with each device (e.g. prosthesis-side propulsion remained comparable to or was greater with the powered versus passive prosthesis for different subjects). Overall, prosthesis-side peak propulsion averaged across conditions was 31% greater with the powered prosthesis and peak propulsion asymmetry improved by 48% with the powered prosthesis.

CONCLUSIONS

Increasing prosthesis-side stance time via visual feedback favorably improved individuals' temporal and propulsive symmetry. The powered prosthesis commonly enabled greater propulsion, but individuals adapted to each device with varying behavior, requiring further investigation.

A Comparison of Control Strategies in Commercial and Research Knee Prostheses

GOAL

To provide an overview of control strategies in commercial and research microprocessor-controlled prosthetic knees (MPKs).

METHODS

Five commercially available MPKs described in patents, and five research MPKs reported in scientific literature were compared. Their working principles, intent recognition, and walking controller were analyzed. Speed and slope adaptability of the walking controller was considered as well.

RESULTS

Whereas commercial MPKs are mostly passive, i.e., do not inject energy in the system, and employ heuristic rule-based intent classifiers, research MPKs are all powered and often utilize machine learning algorithms for intention detection. Both commercial and research MPKs rely on finite state machine impedance controllers for walking. Yet while commercial MPKs require a prosthetist to adjust impedance settings, scientific research is focused on reducing the tunable parameter space and developing unified controllers, independent of subject anthropometrics, walking speed, and ground slope.

CONCLUSION

The main challenges in the field of powered, active MPKs (A-MPKs) to boost commercial viability are first to demonstrate the benefit of A-MPKs compared to passive MPKs or mechanical non-microprocessor knees using biomechanical, performance-based and patient-reported metrics. Second, to evaluate control strategies and intent recognition in an uncontrolled environment, preferably outside the laboratory setting. And third, even though research MPKs favor sophisticated algorithms, to maintain the possibility of practical and comprehensible tuning of control parameters, considering optimal control cannot be known a priori.

SIGNIFICANCE

This review identifies main challenges in the development of A-MPKs, which have thus far hindered their broad availability on the market.

Environmental Features Recognition for Lower Limb Prostheses Toward Predictive Walking

This paper aims to present a robust environmental features recognition system (EFRS) for lower limb prosthesis, which can assist the control of prosthesis by predicting the locomotion modes of amputees and estimating environmental features in the following steps. A depth sensor and an inertial measurement unit are combined to stabilize the point cloud of environments. Subsequently, the 2D point cloud is extracted from origin 3D point cloud and is classified through a neural network. Environmental features, including slope of road, width, and height of stair, were also estimated via the 2D point cloud. Finally, the EFRS is evaluated through classifying and recognizing five kinds of common environments in simulation, indoor experiments, and outdoor experiments by six healthy subjects and three transfemoral amputees, and databases of five healthy subjects and three amputees are used to validate without training. The classification accuracy of five kinds of common environments reach up to 99.3% and 98.5% for the amputees in the indoor and outdoor experiments, respectively. The locomotion modes are predicted at least 0.6 s before the switch of actual locomotion modes. Most estimation errors of indoor and outdoor environments features are lower than 5% and 10%, respectively. The overall process of EFRS takes less than 0.023 s. The promising results demonstrate the robustness and the potential application of the presented EFRS to help the control of lower limb prostheses.

Design, development, and testing of a lightweight hybrid robotic knee prosthesis

We present a lightweight robotic knee prosthesis with a novel hybrid actuation system that enables passive and active operation modes. The proposed hybrid knee uses a spring-damper system in combination with an electric motor and transmission system, which can be engaged to provide a stair ambulation capability. In comparison to fully powered prostheses that power all ambulation activities, a hybrid knee prosthesis can achieve significant weight reduction by focusing the design of the actuator on a subset of activities without losing the ability to produce equivalent torque and mechanical power in the active mode. The hybrid knee prototype weighs 1.7 kg, including battery and control, and can provide up to 125 Nm of repetitive torque. Experiments with two transfemoral amputee subjects show that the proposed hybrid knee prosthesis can support walking on level ground in the passive mode, as well as stair ambulation with a reciprocal gait pattern in the active mode.