Electromyography-Based Control of Lower Limb Prostheses: A Systematic Review

Most amputations occur in lower limbs and despite improvements in prosthetic technology, no commercially available prosthetic leg uses electromyography (EMG) information as an input for control. Efforts to integrate EMG signals as part of the control strategy have increased in the last decade. In this systematic review, we summarize the research in the field of lower limb prosthetic control using EMG. Four different online databases were searched until June 2022: Web of Science, Scopus, PubMed, and Science Direct. We included articles that reported systems for controlling a prosthetic leg (with an ankle and/or knee actuator) by decoding gait intent using EMG signals alone or in combination with other sensors. A total of 1,331 papers were initially assessed and 121 were finally included in this systematic review. The literature showed that despite the burgeoning interest in research, controlling a leg prosthesis using EMG signals remains challenging. Specifically, regarding EMG signal quality and stability, electrode placement, prosthetic hardware, and control algorithms, all of which need to be more robust for everyday use. In the studies that were investigated, large variations were found between the control methodologies, type of research participant, recording protocols, assessments, and prosthetic hardware

On the use of Phantom Motor Execution for the treatment of Phantom Limb Pain

Phantom limb pain (PLP) is a common complaint among amputees and despite having been studiedfor centuries, it remains a mysterious object of debate among researcher. To date, a vast number ofways to treat PLP has been proposed in the literature, however none of them has proven to beuniversally effective, thus creating uncertainty on how to operate clinically. The uncertainty is largelyattributable to the scarcity of well conducted randomized controlled trials (RCTs) to prove the efficacyof PLP treatments.Phantom Motor Execution (PME) -exertion of voluntary phantom limb movements – aims at restoringthe control over the phantom limb and the exercise of such control has been hypothesized to reverseneural changes implicated in PLP. Preliminary evidence supporting this hypothesis has been providedby clinical investigations on upper limb amputees. The main purpose of this Licentiate thesis was toenable a RCT on the use of PME for the treatment of PLP in order to provide robust and unbiasedevidence for clinical practice. However, the implementation and kick-off of this clinical investigationrequired to complete few preparatory steps. For example, most amputees and PLP patients have lowerlimb amputation, thus PME needed to be adapted and validated for this population. Further, the RCTprotocol needed to be carefully planned and made openly accessible, as per guidelines for conductingand publishing clinical RCT. Finally, a secondary aim of this thesis emerged with the need of providinglong term relief from PLP to patient. Preliminary evidence seemed to indicate that in order to maintainpain relief, periodic rehearsal of the phantom motor skills acquired through PME is necessary. Thisraised the question of whether it is beneficial and possible to translate the technology from clinic tohome use, question that was explored employing both quantitative and qualitative methods fromengineering, medical anthropology, and user interface design.The work conducted within this thesis resulted in the extension of PME to lower limb patients byproposal and validation of a new and more user-friendly recording configuration to record EMG signals.The use of PME was then shown to be efficacious in relieving PLP with a case study on a patient. Theprotocol for the RCT was then designed and published. These two first steps permitted theestablishment of the RCT, which is currently ongoing and expected to close in March 2021. With regardto the secondary aim of this thesis, the work conducted enabled PME to be used by the patients in thecomfort of their home, while it also allowed investigate the benefits and challenges generally faced(not only by PME) in the transition from the clinic to home and its effects on treatment adherence. Thework conducted is presented in the three appended publications.Future work includes the presentation of the results of the RCT. Further, having a way to modulate PLPis an incredibly useful tool to study the neural basis of PLP. By capitalizing on this tool, we are currentlyconducting brain imaging studies using fMRI and electroencephalography that are the main focus ofthe work that lies ahead

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

Addressing the challenges posed by human machine interfaces based on force sensitive resistors for powered prostheses

Despite the advancements in the mechatronics aspect of prosthetic devices, prostheses control still lacks an interface that satisfies the needs of the majority of users. The research community has put great effort into the advancements of prostheses control techniques to address users’ needs. However, most of these efforts are focused on the development and assessment of technologies in the controlled environments of laboratories. Such findings do not fully transfer to the daily application of prosthetic systems. The objectives of this thesis focus on factors that affect the use of Force Myography (FMG) controlled prostheses in practical scenarios. The first objective of this thesis assessed the use of FMG as an alternative or synergist Human Machine Interface (HMI) to the more traditional HMI, i.e. surface Electromyography (sEMG). The assessment for this study was conducted in conditions that are relatively close to the real use case of prosthetic applications. The HMI was embedded in the custom prosthetic prototype that was developed for the pilot participant of the study using an off-the-shelf prosthetic end effector. Moreover, prostheses control was assessed as the user moved their limb in a dynamic protocol.The results of the aforementioned study motivated the second objective of this thesis: to investigate the possibility of reducing the complexity of high density FMG systems without sacrificing classification accuracies. This was achieved through a design method that uses a high density FMG apparatus and feature selection to determine the number and location of sensors that can be eliminated without significantly sacrificing the system’s performance. The third objective of this thesis investigated two of the factors that contribute to increased errors in force sensitive resistor (FSR) signals used in FMG controlled prostheses: bending of force sensors and variations in the volume of the residual limb. Two studies were conducted that proposed solutions to mitigate the negative impact of these factors. The incorporation of these solutions into prosthetic devices is discussed in these studies.It was demonstrated that FMG is a promising HMI for prostheses control. The facilitation of pattern recognition with FMG showed potential for intuitive prosthetic control. Moreover, a method for the design of a system that can determine the required number of sensors and their locations on each individual to achieve a simpler system with comparable performance to high density FMG systems was proposed and tested. The effects of the two factors considered in the third objective were determined. It was also demonstrated that the proposed solutions in the studies conducted for this objective can be used to increase the accuracy of signals that are commonly used in FMG controlled prostheses

Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation

GAIT PERFORMANCE AND CONTROL OF A PROSTHETIC ANKLE JOINT FOR BELOW-KNEE AMPUTEES

Traumatic events such as accidents or vascular and circulatory disorders often lead to amputation of the lower limb below the knee joint. The surgery is followed by fitting of a prosthetic device and rehabilitation process to help the individual recover mobility. The recovered gait of the individual depends to a large extent on his/her health, the amputation technique, and the functional level of the prosthesis. Prior research in amputee gait has focused mostly on assessing gait symmetry, movement of the healthy joints, activities of the unaffected muscles, and the metabolic energy consumption in individuals who had undergone traditional amputation. Very little research has been carried out on the performance of individuals with non-traditional amputation procedures designed to maximize the ability of the residual limb to support body weight at the extremity and to maintain the ability of the affected muscles. Moreover, majority of the studies were limited to gait tests in laboratory environments which restricted the mobility of the individuals. Current ankle/foot prostheses for people with below-knee amputation are primarily passive devices whose performance cannot be adapted or optimized to meet the requirements of different users. The adverse consequences of wearing poorly functioning prosthetic feet include asymmetric gait, increased metabolic consumption, limited blood flow, instability, and pain. Over the long term, the amputees, especially ones with diabetes, might have to undergo hip replacement procedure and use wheel-chair on a daily basis. 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. Some of the factors hindering the development and performance validation of such an actively controlled foot are the lack of complete understanding of the gait, the interaction between the residual limb and the controller, presence of human in the control loop, unknown interaction between the terrain and the foot, and stringent requirements on the mechanical power and rigidity of the foot. This dissertation aims to address these shortcomings in a systematic fashion in order to develop an intelligent ankle/foot prosthesis system. The following are the key steps in the process adopted in this dissertation. • First, a gait monitoring device and algorithms for gait analysis will be developed to study the gait of people with below-knee amputation in real time during work-related activities. Experimental protocols are then designed to collect gait data from individuals with below-knee amputation in order to understand the activity of the residual muscles and the ability of the prosthetic device to support body weight during gait. • The dependence of the interfacial socket forces and electromyography signals from the muscles in the residual limb on the type of the gait and gait-related events will then be studied. The use of this dependence to recognize user gait and the corresponding ankle displacement pattern for the controlled prosthetic foot will be investigated. • Finally, hierarchical learning-based control strategies will be developed to adaptively compensate for the unknown, changing ankle dynamics and drive the prosthetic ankle joint along the desired trajectories. It is anticipated that the learning capabilities of these control strategies will enable the prosthetic ankle joint to not only replicate the movement of the healthy ankle, but also improve the stability of the gait and optimize the performance. The above approaches are demonstrated in this dissertation in two parts. The analysis of the gait of a group of otherwise healthy men with non-traditional amputation technique called transtibial osteomyoplastic amputation (TOA) is considered in the first part of the dissertation. The TOA procedure is prescribed for healthy, young individuals who desire a very active lifestyle. TOA offers stable bony residuum capable of bearing the weight of the individual and residual muscles that are active throughout the gait cycle. The gait study carried out in this dissertation is shown to confirm loading at the distal end-bearing area of the residual limb and active contraction of the residual muscles below the knee during gait of all participants. The interfacial forces in the socket and the activity of the residual muscles in subjects with TOA are shown to be related to and dependent on the type of gait, as well as the type of prosthetic feet used. In addition, the potential of residuum socket interface forces in recognition of the gait is also demonstrated. Learning-based control of the prosthetic ankle joint is addressed in the second part of the dissertation. Two hierarchical learning-based control algorithms that take into account the ankle dynamics, foot-ground interaction, and the movement of upper body are considered. The first strategy uses an artificial neural network-based feedback linearization controller to learn the unknown and changing dynamics of the ankle joint and to track a desired ankle displacement profile. In the second strategy, a neural dynamic programming-based controller that can track an ankle displacement profile while optimizing a cost function based on the tracking error is considered. Actual gait data obtained from the subjects in the first part of this dissertation is used to study the effectiveness of the control strategy. For the first time, an adaptive controller has been demonstrated that can address changes in terrain and in user requirements to provide consistent and stable functioning of the prosthetic ankle. It is anticipated that the strategy developed in this dissertation will help build an intelligent prosthetic foot that can significantly improve the mobility and long-term health of people with amputation of the lower limb. Keyword: Gait Analysis, Prosthetic Foot, Intelligent Contro

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research

Functional assessment after peripheral nerve injury : kinematic model of the hindlimb of the rat

Doutoramento em Motricidade Humana na especialidade de FisioterapiaGait analysis is increasingly used on research methodology to assess dynamics aspects of functional recovery after peripheral nerve injury in the rat model, which ultimately is the goal of treatment and rehabilitation. In this thesis we studied nerve regeneration using techniques of molecular and cellular biology. Functional recovery was evaluated using the sciatic functional index (SFI), the static sciatic index (SSI), the extensor postural thrust (EPT), the withdrawal reflex latency (WRL) and hindlimb kinematics. Nerve fiber regeneration was assessed by quantitative stereological analysis and electron microscopy. From our results, hybrid chitosan membranes after sciatic nerve crush, either alone or enriched with N1E-115 neural cells, may represent an effective approach for the improvement of the clinical outcome in patients receiving peripheral nerve surgery. Collagen membrane, with or without neural cell enrichment, did not lead to any significant improvement in most of functional and stereological predictors of nerve regeneration that we have assessed, with the exception of EPT. Extending the kinematic analysis during walking to the hip joint improved sensitivity of this functional test. For motor rehabilitation, either active or passive exercises positively affect sciatic nerve regeneration after a crush injury, possibly mediated by a direct mechanical effect onto the regenerating nerve.FCT- Fundação para a Ciência e Tecnologi