Development of EMG-based mode and intent recognition algorithms for a computer-controlled above-knee prosthesis

Design trends in actuated lower-limb prosthetic systems: a narrative review

INTRODUCTION

Actuated lower limb prostheses, including powered (active) and semi-active (quasi-passive) joints, are endowed with controllable power and/or impedance, which can be advantageous to limb impairment individuals by improving locomotion mechanics and reducing the overall metabolic cost of ambulation. However, an increasing number of commercial and research-focused options have made navigating this field a daunting task for users, researchers, clinicians, and professionals.

AREAS COVERED

The present paper provides an overview of the latest trends and developments in the field of actuated lower-limb prostheses and corresponding technologies. Following a gentle summary of essential gait features, we introduce and compare various actuated prosthetic solutions in academia and the market designed to provide assistance at different levels of impairments. Correspondingly, we offer insights into the latest developments of sockets and suspension systems, before finally discussing the established and emerging trends in surgical approaches aimed at improving prosthetic experience through enhanced physical and neural interfaces.

EXPERT OPINION

The ongoing challenges and future research opportunities in the field are summarized for exploring potential avenues for development of next generation of actuated lower limb prostheses. In our opinions, a closer multidisciplinary integration can be found in the field of actuated lower-limb prostheses in the future.

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.

Mechanisms and component design of prosthetic knees: A review from a biomechanical function perspective

Prosthetic knees are state-of-the-art medical devices that use mechanical mechanisms and components to simulate the normal biological knee function for individuals with transfemoral amputation. A large variety of complicated mechanical mechanisms and components have been employed; however, they lack clear relevance to the walking biomechanics of users in the design process. This article aims to bridge this knowledge gap by providing a review of prosthetic knees from a biomechanical perspective and includes stance stability, early-stance flexion and swing resistance, which directly relate the mechanical mechanisms to the perceived walking performance, i.e., fall avoidance, shock absorption, and gait symmetry. The prescription criteria and selection of prosthetic knees depend on the interaction between the user and prosthesis, which includes five functional levels from K0 to K4. Misunderstood functions and the improper adjustment of knee prostheses may lead to reduced stability, restricted stance flexion, and unnatural gait for users. Our review identifies current commercial and recent studied prosthetic knees to provide a new paradigm for prosthetic knee analysis and facilitates the standardization and optimization of prosthetic knee design. This may also enable the design of functional mechanisms and components tailored to regaining lost functions of a specific person, hence providing individualized product design.

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.

Optimization of immune receptor-related hypersensitive cell death response assay using agrobacterium-mediated transient expression in tobacco plants

BACKGROUND

The study of the regulatory mechanisms of evolutionarily conserved Nucleotide-binding leucine-rich repeat (NLR) resistance (R) proteins in animals and plants is of increasing importance due to understanding basic immunity and the value of various crop engineering applications of NLR immune receptors. The importance of temperature is also emerging when applying NLR to crops responding to global climate change. In particular, studies of pathogen effector recognition and autoimmune activity of NLRs in plants can quickly and easily determine their function in tobacco using agro-mediated transient assay. However, there are conditions that should not be overlooked in these cell death-related assays in tobacco.

RESULTS

Environmental conditions play an important role in the immune response of plants. The system used in this study was to establish conditions for optimal hypertensive response (HR) cell death analysis by using the paired NLR RPS4/RRS1 autoimmune and AvrRps4 effector recognition system. The most suitable greenhouse temperature for growing plants was fixed at 22 °C. In this study, RPS4/RRS1-mediated autoimmune activity, RPS4 TIR domain-dependent cell death, and RPS4/RRS1-mediated HR cell death upon AvrRps4 perception significantly inhibited under conditions of 65% humidity. The HR is strongly activated when the humidity is below 10%. Besides, the leaf position of tobacco is important for HR cell death. Position #4 of the leaf from the top in 4-5 weeks old tobacco plants showed the most effective HR cell death.

CONCLUSIONS

As whole genome sequencing (WGS) or resistance gene enrichment sequencing (RenSeq) of various crops continues, different types of NLRs and their functions will be studied. At this time, if we optimize the conditions for evaluating NLR-mediated HR cell death, it will help to more accurately identify the function of NLRs. In addition, it will be possible to contribute to crop development in response to global climate change through NLR engineering.

Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions

Objective.Advanced robotic lower limb prostheses are mainly controlled autonomously. Although the existing control can assist cyclic movements during locomotion of amputee users, the function of these modern devices is still limited due to the lack of neuromuscular control (i.e. control based on human efferent neural signals from the central nervous system to peripheral muscles for movement production). Neuromuscular control signals can be recorded from muscles, called electromyographic (EMG) or myoelectric signals. In fact, using EMG signals for robotic lower limb prostheses control has been an emerging research topic in the field for the past decade to address novel prosthesis functionality and adaptability to different environments and task contexts. The objective of this paper is to review robotic lower limb Prosthesis control via EMG signals recorded from residual muscles in individuals with lower limb amputations.Approach.We performed a literature review on surgical techniques for enhanced EMG interfaces, EMG sensors, decoding algorithms, and control paradigms for robotic lower limb prostheses.Main results.This review highlights the promise of EMG control for enabling new functionalities in robotic lower limb prostheses, as well as the existing challenges, knowledge gaps, and opportunities on this research topic from human motor control and clinical practice perspectives.Significance.This review may guide the future collaborations among researchers in neuromechanics, neural engineering, assistive technologies, and amputee clinics in order to build and translate true bionic lower limbs to individuals with lower limb amputations for improved motor function.

Toward Minimal-Sensing Locomotion Mode Recognition for a Powered Knee-Ankle Prosthesis

OBJECTIVE

Locomotion mode recognition (LMR) enables seamless and natural transitions between low-level control systems in a powered prosthesis. We present a new optimization framework for LMR that eliminates irrelevant or redundant features and measurement signals while still maintaining performance.

METHODS

We use multi-objective biogeography-based optimization to find a compromise solution between performance and the minimization of feature set size. Experimental data are collected from four transfemoral users walking with a powered knee-ankle prosthesis. We compare the performance of LMR systems trained with the optimal feature subsets and with the full feature set using a deep neural network classifier across six locomotion modes: standing, flat-ground walking, stair up/down, and ramp up/down.

RESULTS

Statistical tests indicate that classifier performance using the optimal feature subsets is statistically equal to that using the full feature set. The LMR trained with an optimal subset results in the 1.98% steady-state and 4.09% transitional error rates, while only using approximately 41% and 53% of the available features and sensors, respectively.

CONCLUSION

Results thus indicate the capability of the proposed framework to achieve simultaneously accurate and low-complex LMR systems for transfemoral individuals with powered prostheses.

SIGNIFICANCE

This framework would potentially lead to less frequent clinical visits needed for sensor replacement and calibrations, which may save health care costs and the prosthesis user's time and energy.

IMU-Based Locomotion Mode Identification for Transtibial Prostheses, Orthoses, and Exoskeletons

Active transtibial prostheses, orthoses, and exoskeletons hold the promise of improving the mobility of lower-limb impaired or amputated individuals. Locomotion mode identification (LMI) is essential for these devices precisely reproducing the required function in different terrains. In this study, a terrain geometry-based LMI algorithm is proposed. The environment should be built according to the inclination grade of the ground. For example, when the inclination angle is between 7 degrees and 15 degrees, the environment should be a ramp. If the inclination angle is around 30 degrees, the environment is preferred to be equipped with stairs. Given that, the locomotion mode/terrain can be classified by the inclination grade. Besides, human feet always move along the surface of terrain to minimize the energy expenditure for transporting lower limbs and get the required foot clearance. Hence, the foot trajectory estimated by an IMU was used to derive the inclination grade of the terrain that we traverse to identify the locomotion mode. In addition, a novel trigger condition (an elliptical boundary) is proposed to activate the decision-making of the LMI algorithm before the next foot strike thus leaving enough time for performing preparatory work in the swing phase. When the estimated foot trajectory goes across the elliptical boundary, the decision-making will be executed. Experimental results show that the average accuracy for three healthy subjects and three below-knee amputees is 98.5% in five locomotion modes: level-ground walking, up slope, down slope, stair descent, and stair ascent. Besides, all the locomotion modes can be identified before the next foot strike.

Impact of Powered Knee-Ankle Prosthesis on Low Back Muscle Mechanics in Transfemoral Amputees: A Case Series

Regular use of prostheses is critical for individuals with lower limb amputations to achieve everyday mobility, maintain physical and physiological health, and achieve a better quality of life. Use of prostheses is influenced by numerous factors, with prosthetic design playing a critical role in facilitating mobility for an amputee. Thus, prostheses design can either promote biomechanically efficient or inefficient gait behavior. In addition to increased energy expenditure, inefficient gait behavior can expose prosthetic user to an increased risk of secondary musculoskeletal injuries and may eventually lead to rejection of the prosthesis. Consequently, researchers have utilized the technological advancements in various fields to improve prosthetic devices and customize them for user specific needs. One evolving technology is powered prosthetic components. Presently, an active area in lower limb prosthetic research is the design of novel controllers and components in order to enable the users of such powered devices to be able to reproduce gait biomechanics that are similar in behavior to a healthy limb. In this case series, we studied the impact of using a powered knee-ankle prostheses (PKA) on two transfemoral amputees who currently use advanced microprocessor controlled knee prostheses (MPK). We utilized outcomes pertaining to kinematics, kinetics, metabolics, and functional activities of daily living to compare the efficacy between the MPK and PKA devices. Our results suggests that the PKA allows the participants to walk with gait kinematics similar to normal gait patterns observed in a healthy limb. Additionally, it was observed that use of the PKA reduced the level of asymmetry in terms of mechanical loading and muscle activation, specifically in the low back spinae regions and lower extremity muscles. Further, the PKA allowed the participants to achieve a greater range of cadence than their predicate MPK, thus allowing them to safely ambulate in variable environments and dynamically control speed changes. Based on the results of this case series, it appears that there is considerable potential for powered prosthetic components to provide safe and efficient gait for individuals with above the knee amputation.

Adaptive Bayesian inference system for recognition of walking activities and prediction of gait events using wearable sensors

In this paper, a novel approach for recognition of walking activities and gait events with wearable sensors is presented. This approach, called adaptive Bayesian inference system (BasIS), uses a probabilistic formulation with a sequential analysis method, for recognition of walking activities performed by participants. Recognition of gait events, needed to identify the state of the human body during the walking activity, is also provided by the proposed method. In addition, the BasIS system includes an adaptive action-perception method for the prediction of gait events. The adaptive approach uses the knowledge gained from decisions made over time by the inference system. The action-perception method allows the BasIS system to autonomously adapt its performance, based on the evaluation of its own predictions and decisions made over time. The proposed approach is implemented in a layered architecture and validated with the recognition of three walking activities:level-ground, ramp ascent and ramp descent. The validation process employs real data from three inertial measurements units attached to the thigh, shanks and foot of participants while performing walking activities. The experiments show that mean decision times of 240 ms and 40 ms are needed to achieve mean accuracies of 99.87% and 99.82% for recognition of walking activities and gait events, respectively. The validation experiments also show that the performance, in accuracy and speed, is not significantly affected when noise is added to sensor measurements. These results show that the proposed adaptive recognition system is accurate, fast and robust to sensor noise, but also capable to adapt its own performance over time. Overall, the adaptive BasIS system demonstrates to be a robust and suitable computational approach for the intelligent recognition of activities of daily living using wearable sensors.

Depth Sensing for Improved Control of Lower Limb Prostheses

Powered lower limb prostheses have potential to improve the quality of life of individuals with amputations by enabling all daily activities. However, seamless ambulation mode recognition is necessary to achieve this goal and is not yet a clinical reality. Current intent recognition systems use mechanical and EMG sensors to estimate prosthesis and user status. We propose to complement these systems by integrating information about the environment obtained through the depth sensing. This paper presents the design, characterization, and the early validation of a novel stair segmentation system based on Microsoft Kinect. Static and dynamic tests were performed. A first experiment showed how the resolution of the depth camera affects the speed and the accuracy of segmentation. A second test proved the robustness of the algorithm to different staircases. Finally, we performed an online walking test with the stair segmentation and related measures recorded online at >5 frames/s. Experimental results show that the proposed algorithm allows for an accurate estimate of distance, angle of intersection, number of steps, stair height, and stair depth for a set of stairs in the environment. The online test produced an estimate of whether the individual was approaching stairs in real time with approximately 98.8% accuracy.

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

: 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.

EMG control of a bionic knee prosthesis: exploiting muscle co-contractions for improved locomotor function

This paper presents the development and experimental evaluation of a volitional control architecture for a powered-knee transfemoral prosthesis that affords the amputee user with direct control of knee impedance using measured electromyogram (EMG) potentials of antagonist muscles in the residual limb. The control methodology incorporates a calibration procedure performed with each donning of the prosthesis that characterizes the co-contraction levels as the user performs volitional phantom-knee flexor and extensor contractions. The performance envelope for EMG control of impedance is then automatically shaped based on the flexor and extensor calibration datasets. The result is a control architecture that is optimized to the user's current co-contraction activity, providing performance robustness to variation in sensor placement or physiological changes in the residual-limb musculature. Experimental results with a single unilateral transfemoral amputee user demonstrate consistent and repeatable control performance for level walking at self-selected speed over a multi-week, multi-session period of evaluation.

Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses

OBJECTIVE

The purpose of this study was to determine the contribution of electromyography (EMG) data, in combination with a diverse array of mechanical sensors, to locomotion mode intent recognition in transfemoral amputees using powered prostheses. Additionally, we determined the effect of adding time history information using a dynamic Bayesian network (DBN) for both the mechanical and EMG sensors.

APPROACH

EMG signals from the residual limbs of amputees have been proposed to enhance pattern recognition-based intent recognition systems for powered lower limb prostheses, but mechanical sensors on the prosthesis-such as inertial measurement units, position and velocity sensors, and load cells-may be just as useful. EMG and mechanical sensor data were collected from 8 transfemoral amputees using a powered knee/ankle prosthesis over basic locomotion modes such as walking, slopes and stairs. An offline study was conducted to determine the benefit of different sensor sets for predicting intent.

MAIN RESULTS

EMG information was not as accurate alone as mechanical sensor information (p < 0.05) for any classification strategy. However, EMG in combination with the mechanical sensor data did significantly reduce intent recognition errors (p < 0.05) both for transitions between locomotion modes and steady-state locomotion. The sensor time history (DBN) classifier significantly reduced error rates compared to a linear discriminant classifier for steady-state steps, without increasing the transitional error, for both EMG and mechanical sensors. Combining EMG and mechanical sensor data with sensor time history reduced the average transitional error from 18.4% to 12.2% and the average steady-state error from 3.8% to 1.0% when classifying level-ground walking, ramps, and stairs in eight transfemoral amputee subjects.

SIGNIFICANCE

These results suggest that a neural interface in combination with time history methods for locomotion mode classification can enhance intent recognition performance; this strategy should be considered for future real-time experiments.

A locomotion intent prediction system based on multi-sensor fusion

Locomotion intent prediction is essential for the control of powered lower-limb prostheses to realize smooth locomotion transitions. In this research, we develop a multi-sensor fusion based locomotion intent prediction system, which can recognize current locomotion mode and detect locomotion transitions in advance. Seven able-bodied subjects were recruited for this research. Signals from two foot pressure insoles and three inertial measurement units (one on the thigh, one on the shank and the other on the foot) are measured. A two-level recognition strategy is used for the recognition with linear discriminate classifier. Six kinds of locomotion modes and ten kinds of locomotion transitions are tested in this study. Recognition accuracy during steady locomotion periods (i.e., no locomotion transitions) is 99.71% ± 0.05% for seven able-bodied subjects. During locomotion transition periods, all the transitions are correctly detected and most of them can be detected before transiting to new locomotion modes. No significant deterioration in recognition performance is observed in the following five hours after the system is trained, and small number of experiment trials are required to train reliable classifiers.

Lower limb wearable capacitive sensing and its applications to recognizing human gaits

In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97:3% ± 0:5%, 97:0% ± 0:4%, 95:6% ± 0:9% and 97:0% ± 0:4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits.

Non-weight-bearing neural control of a powered transfemoral prosthesis

Lower limb prostheses have traditionally been mechanically passive devices without electronic control systems. Microprocessor-controlled passive and powered devices have recently received much interest from the clinical and research communities. The control systems for these devices typically use finite-state controllers to interpret data measured from mechanical sensors embedded within the prosthesis. In this paper we investigated a control system that relied on information extracted from myoelectric signals to control a lower limb prosthesis while amputee patients were seated. Sagittal plane motions of the knee and ankle can be accurately (>90%) recognized and controlled in both a virtual environment and on an actuated transfemoral prosthesis using only myoelectric signals measured from nine residual thigh muscles. Patients also demonstrated accurate (~90%) control of both the femoral and tibial rotation degrees of freedom within the virtual environment. A channel subset investigation was completed and the results showed that only five residual thigh muscles are required to achieve accurate control. This research is the first step in our long-term goal of implementing myoelectric control of lower limb prostheses during both weight-bearing and non-weight-bearing activities for individuals with transfemoral amputation.

Locomotion mode classification using a wearable capacitive sensing system

Locomotion mode classification is one of the most important aspects for the control of powered lower-limb prostheses. We propose a wearable capacitive sensing system for recognizing locomotion modes as an alternative solution to popular electromyography (EMG)-based systems, aiming to overcome drawbacks of the latter. Eight able-bodied subjects and five transtibial amputees were recruited for automatic classification of six common locomotion modes. The system measured ten channels of capacitance signals from the shank, the thigh, or both. With a phase-dependent linear discriminant analysis classifier and selected time-domain features, the system can achieve a satisfactory classification accuracy of 93.6% ±0.9% and 93.4% ±0.8% for able-bodied subjects and amputee subjects, respectively. The classification accuracy is comparable with that of EMG-based systems. More importantly, we verify that neuro-mechanical delay inherent in capacitive sensing does not affect the timeliness of classification decisions as the system, similar to EMG-based systems, can make multiple judgments during a gait cycle. Experimental results also indicate that capacitance signals from the thigh alone are sufficient for mode classification for both able-bodied and transtibial subjects. Our investigations demonstrate that capacitive sensing is a promising alternative to myoelectric sensing for real-time control of powered lower-limb prostheses.

A method to determine the optimal features for control of a powered lower-limb prostheses

Lower-limb prostheses are rapidly advancing with greater computing power and sensing modalities. This paper is an attempt to begin exploring the trade-off between extrinsic and intrinsic control modalities. In this case, between electromyographic (extrinsic) and several internal sensors that can be used for intrinsic control. We propose a method that will identify the particular features, taken from two trans-femoral amputee and one trans-tibial amputee, during locomotion on varying terrain, that perfectly discriminate between locomotion modes. From this we are able to identify the source of the discriminability from a large-set of features that does not depend on the type of amputation. Also, we comment on the use of this algorithm in selecting the most discriminatory and least encumbering sensor/feature combination for transitions when the ground underneath the foot is unknown for trans-tibial amputees.

Co-contraction patterns of trans-tibial amputee ankle and knee musculature during gait

Background

Myoelectric control of upper extremity powered prostheses has been used clinically for many years, however this approach has not been fully developed for lower extremity prosthetic devices. With the advent of powered lower extremity prosthetic components, the potential role of myoelectric control systems is of increasing importance. An understanding of muscle activation patterns and their relationship to functional ambulation is a vital step in the future development of myoelectric control. Unusual knee muscle co-contractions have been reported in both limbs of trans-tibial amputees. It is currently unknown what differences exist in co-contraction between trans-tibial amputees and controls. This study compares the activation and co-contraction patterns of the ankle and knee musculature of trans-tibial amputees (intact and residual limbs), and able-bodied control subjects during three speeds of gait. It was hypothesized that residual limbs would have greater ankle muscle co-contraction than intact and able-bodied control limbs and that knee muscle co-contraction would be different among all limbs. Lastly it was hypothesized that the extent of muscle co-contraction would increase with walking speed.

Methods

Nine unilateral traumatic trans-tibial amputees and five matched controls participated. Surface electromyography recorded activation from the Tibialis Anterior, Medial Gastrocnemius, Vastus Lateralis and Biceps Femoris of the residual, intact and control limbs. A series of filters were applied to the signal to obtain a linear envelope of the activation patterns. A co-contraction area (ratio of the integrated agonist and antagonist activity) was calculated during specific phases of gait.

Results

Co-contraction of the ankle muscles was greater in the residual limb than in the intact and control limbs during all phases of gait. Knee muscle co-contraction was greater in the residual limb than in the control limb during all phases of gait.

Conclusion

Co-contractions may represent a limb stiffening strategy to enhance stability during phases of initial foot-contact and single limb support. These strategies may be functionally necessary for amputee gait; however, the presence of co-contractions could confound future development of myoelectric controls and should thus be accounted for.

The Design and Initial Experimental Validation of an Active Myoelectric Transfemoral Prosthesis

This paper describes a single degree-of-freedom active-knee transfemoral prosthesis to be used as a test bed for the development of architectures for myoelectric control. The development of an active-knee transfemoral prosthesis is motivated by the inability of passive commercial prostheses to provide the joint power required at the knee for many activities of daily living such as reciprocal stair ascent, which requires knee power outputs of up to 4 W/kg. Study of myoelectric control based on surface electromyogram (EMG) measurements of muscles in the residual limb is motivated by the desire to restore direct volitional control of the knee using a minimally-invasive neuromuscular control interface. The presented work describes the design of a transfemoral prosthesis prototype including the structure, actuation, instrumentation, electronics, and real-time control architecture. The performance characteristics of the prototype are discussed in the context of the requisite knee energetics for a variety of common locomotive functions. This paper additionally describes the development of a single-subject diagnostic socket with wall-embedded surface EMG electrodes and the implementation of a control architecture for myoelectric modulation of knee impedance. Experimental results of level walking for a single subject with unilateral transfemoral amputation demonstrate the potential for direct EMG-based control of locomotive function.

Myoelectric control of a powered knee prosthesis for volitional movement during non-weight-bearing activities

This paper describes a means of controlling the knee movement of a powered knee prosthesis during non-weight-bearing activity such as sitting, by utilizing surface EMG from the quadriceps and hamstring muscle groups in the residual limb. The method was implemented on a powered prosthesis on three amputee subjects, and experimental results are presented characterizing the ability of the amputee subjects to control knee motion. A comparison of the trajectory tracking error between the amputees' prosthetic and intact knees indicates that the EMG-based volitional controller provides similar trajectory tracking capability to the native (i.e., intact) knee joint.

A strategy for identifying locomotion modes using surface electromyography

This study investigated the use of surface electromyography (EMG) combined with pattern recognition (PR) to identify user locomotion modes. Due to the nonstationary characteristics of leg EMG signals during locomotion, a new phase-dependent EMG PR strategy was proposed for classifying the user's locomotion modes. The variables of the system were studied for accurate classification and timely system response. The developed PR system was tested on EMG data collected from eight able-bodied subjects and two subjects with long transfemoral (TF) amputations while they were walking on different terrains or paths. The results showed reliable classification for the seven tested modes. For eight able-bodied subjects, the average classification errors in the four defined phases using ten electrodes located over the muscles above the knee (simulating EMG from the residual limb of a TF amputee) were 12.4% +/- 5.0%, 6.0% +/- 4.7%, 7.5% +/- 5.1%, and 5.2% +/- 3.7%, respectively. Comparable results were also observed in our pilot study on the subjects with TF amputations. The outcome of this investigation could promote the future design of neural-controlled artificial legs.

Real-time Gait Mode Intent Recognition of a Powered Knee and Ankle Prosthesis for Standing and Walking

This paper describes a real-time gait mode intent recognition approach for the supervisory control of a powered transfemoral prosthesis. The proposed approach infers user intent by recognizing patterns in the prosthesis sensor's signals in real-time, eliminating the need for sound-side instrumentation and allowing fast mode switching. Simple time based features extracted from frames of prosthesis signals are reduced to lower dimensions. Gaussian Mixture Models are trained using an experimental database for gait mode classification. A voting scheme is applied as a post-processing step to increase the robustness of decision making. The effectiveness of the proposed method is shown via gait experiments on a treadmill with a healthy subject using an able bodied adapter.

Toward the development of a neural interface for lower limb prosthesis control

Lower limb amputees form a large portion of the amputee population; however, current lower limb prostheses do not meet the needs of patients with high-level amputations who need to perform multi-joint coordinated movements. A critical missing element is an intuitive neural interface from which user intent can be determined. Surface EMG has been used as control source for upper limb prostheses for many years; for lower limb activities, however, the EMG is non-stationary and a new control strategy is required. This paper describes the work completed to date in developing a novel lower limb neural interface.

Survey on the use of smart and adaptive engineering systems in medicine

In this paper, the current published knowledge about smart and adaptive engineering systems in medicine is reviewed. The achievements of frontier research in this particular field within medical engineering are described. A multi-disciplinary approach to the applications of adaptive systems is observed from the literature surveyed. The three modalities of diagnosis, imaging and therapy are considered to be an appropriate classification method for the analysis of smart systems being applied to specified medical sub-disciplines. It is expected that future research in biomedicine should identify subject areas where more advanced intelligent systems could be applied than is currently evident. The literature provides evidence of hybridisation of different types of adaptive and smart systems with applications in different areas of medical specifications.

Using NetMeeting for remote configuration of the Otto Bock C-Leg: technical considerations

Telehealth has the potential to be a valuable tool for technical and clinical support of computer controlled prosthetic devices. This pilot study examined the use of Internet-based, desktop video conferencing for remote configuration of the Otto Bock C-Leg. Laboratory tests involved connecting two computers running Microsoft NetMeeting over a local area network (IP protocol). Over 56 Kbs(-1), DSL/Cable, and 10 Mbs(-1) LAN speeds, a prosthetist remotely configured a user's C-Leg by using Application Sharing, Live Video, and Live Audio. A similar test between sites in Ottawa and Toronto, Canada was limited by the notebook computer's 28 Kbs(-1) modem. At the 28 Kbs(-1) Internet-connection speed, NetMeeting's application sharing feature was not able to update the remote Sliders window fast enough to display peak toe loads and peak knee angles. These results support the use of NetMeeting as an accessible and cost-effective tool for remote C-Leg configuration, provided that sufficient Internet data transfer speed is available.

Optimal control for an above-knee prosthesis with two degrees of freedom

Our previous research and clinical tests of a self-contained powered above-knee prosthesis (AKP) showed that a knee joint with one degree of freedom (DOF) increases the energy cost of walking with respect to able-bodied subjects. Better symmetry of the gait can improve performance, so we suggest here the integration of a second powered DOF into the knee joint mechanism to control the internal-external rotation of the shank-foot complex. The control for the AKP with two DOFs is based on a method of optimal tracking. The data used for analysis were collected in able-bodied subjects braced with an ankle splint to experimentally duplicate a gait like that of amputees using a two-DOF prosthesis. The simulation showed the following: (1) the technique of optimal programming can be used for simulation of the artificial leg during locomotion; (2) the optimal tracking method is an efficient tool for selection of actuators for the above-knee prosthesis, ensuring that the tracking remains within limits. Limitation of joint torque is desirable in order to reduce the size of the motor, but beyond a certain point limiting maximal torques lead to tracking errors that are associated with higher energy costs and hence the need for a larger power source. The errors are also associated with higher forces at the interface between the socket and the prosthesis. The optimal tracking method allows the optimization of tracking with constraints on the size of the motor used and its energy cost.