Within-socket Myoelectric Prediction of Continuous Ankle Kinematics for Control of a Powered Transtibial Prosthesis

Objective. Powered robotic prostheses create a need for natural-feeling user interfaces and robust control schemes. Here, we examined the ability of a nonlinear autoregressive model to continuously map the kinematics of a transtibial prosthesis and electromyographic (EMG) activity recorded within socket to the future estimates of the prosthetic ankle angle in three transtibial amputees. Approach. Model performance was examined across subjects during level treadmill ambulation as a function of the size of the EMG sampling window and the temporal \u27prediction\u27 interval between the EMG/kinematic input and the model\u27s estimate of future ankle angle to characterize the trade-off between model error, sampling window and prediction interval. Main results. Across subjects, deviations in the estimated ankle angle from the actual movement were robust to variations in the EMG sampling window and increased systematically with prediction interval. For prediction intervals up to 150 ms, the average error in the model estimate of ankle angle across the gait cycle was less than 6°. EMG contributions to the model prediction varied across subjects but were consistently localized to the transitions to/from single to double limb support and captured variations from the typical ankle kinematics during level walking. Significance. The use of an autoregressive modeling approach to continuously predict joint kinematics using natural residual muscle activity provides opportunities for direct (transparent) control of a prosthetic joint by the user. The model\u27s predictive capability could prove particularly useful for overcoming delays in signal processing and actuation of the prosthesis, providing a more biomimetic ankle response

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

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

Preliminary Investigation of Residual Limb Plantarflexion and Dorsiflexion Muscle Activity During Treadmill Walking for Trans-tibial Amputees

Background: Novel powered prosthetic ankles currently incorporate finite state control, using kinematic and kinetic sensors to differentiate stance and swing phases/sub-phases and control joint impedance and position or torque. For more intuitive control, myoelectric control of the ankle using the remnant residual limb dorsiflexors and plantarflexors, perhaps in concert with kinetic and kinematic sensors, may be possible. Objective: The specific research objective was to assess the feasibility of using myoelectric control of future active or powered prosthetic ankle joints for trans-tibial amputees. Study Design: The project involved human subject trials to determine whether current techniques of myoelectric control of upper extremity prostheses might be readily adapted for lower extremity prosthetic control. Methods: Gait analysis was conducted for three unilateral trans-tibial amputee subjects during ambulation on an instrumented split belt treadmill. Data included ankle plantarflexor and dorsiflexor activity for the residual limb, as well as lower limb kinematics and ground reaction forces and moments of both the sound and prosthetic limbs. Results: These data indicate that: 1) trans-tibial amputees retain some independent ankle plantarflexor and dorsiflexor muscle activity of their residual limb; 2) it is possible to position surface electromyographic electrodes within a trans-tibial socket that maintain contact during ambulation; 3) both the plantarflexors and dorsiflexors of the residual limb are active during gait; 4) plantarflexor and dorsiflexor activity is consistent during multiple gait cycles; and 5) with minimal training, trans-tibial amputees may be able to activate their plantarflexors during push-off. Conclusions: These observations demonstrate the potential for future myoelectric control of active prosthetic ankles. Clinical relevance This study demonstrated the feasibility of applying upper extremity prosthetic myoelectric signal acquisition, processing and control techniques to future myoelectric control of active prosthetic ankles for trans-tibial amputees

Continuous Proportional Myoelectric Control of an Experimental Powered Lower Limb Prosthesis During Walking Using Residual Muscles.

Current robotic lower limb prostheses rely on intrinsic sensing and finite state machines to control ankle mechanics during walking. State-based controllers are suitable for stereotypical cyclic locomotor tasks (e.g. walking on level ground) where joint mechanics are well defined at specific gait phases (i.e. states) and state transitions are easily detected. However, state-based controllers are not ideal for non-stereotypical acyclic tasks (e.g. freestyle dancing) where joint mechanics cannot be predefined and transitions are unpredictable. An alternative to state-based control is to utilize the amputee's nervous system for myoelectric control. A robotic lower limb prosthesis that uses continuous proportional myoelectric control would allow the amputee to adapt their ankle mechanics freely. One potential source for myoelectric control is the amputee’s residual muscles. I conducted four studies to examine the feasibility of using residual muscles for continuous myoelectric control during walking. In my first study, I demonstrated that it is possible to record residual electromyography from amputees during walking that are viable for continuous myoelectric control. My results showed that the stride-to-stride variability of residual and intact muscle activation patterns was similar. However, residual muscle activation patterns were significantly different across amputee subjects and significantly different than corresponding muscles in intact subjects. In my second study, I built and tested an experimental powered transtibial prosthesis and demonstrated that an amputee subject was able to walk using continuous proportional myoelectric control to alter prosthetic ankle mechanics. In my third study, I showed that five amputee subjects were able to adapt their residual muscles to walk using continuous proportional myoelectric control. With visual feedback of their control signal, amputees were able to generate higher peak ankle power walking with the experimental powered prosthesis compared to their prescribed prosthesis. In my fourth study, I conducted a user experience study and found that despite challenges with the device user interface, walking with continuous proportional myoelectric control gave amputees a sense of empowerment and embodiment. The results of my studies demonstrated the advantages and disadvantages of using continuous proportional myoelectric control for a powered transtibial prosthesis and suggest how next generation prostheses can build upon these findings.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110412/1/shuangz_1.pd

Step Activity and 6-Minute Walk Test Outcomes When Wearing Low-Activity or High-Activity Prosthetic Feet

Objective To determine changes in average daily step count (ADSC) and 6-minute walk test (6MWT) due to use of low-activity feet (LA) and high-activity energy-storage-and-return (ESAR) feet, and examine the sensitivity of these measures to properly classify different prosthetic feet. Design Individuals with transtibial amputations (n = 28) participated in a 6-week, randomized crossover study. During separate 3-week periods, participants wore either a LA foot (eg, solid-ankle-cushioned-heel) or an ESAR foot. Differences in 6MWT and ADSC at the end of the 3-week period were recorded. Results Subjects performed similarly in the 6MWT with the LA and ESAR foot (P = 0.871) and ADSC (P = 0.076). The correct classification of ESAR is only 51.9% and 61.5% with 6MWT and ADSC, respectively. For the LA foot, correct classification is less than 50% for both tests. Conclusions Neither ADSC or 6MWT are responsive to changes in prosthetic feet. The pitfalls and shortcomings of these instruments with regard to their ability to detect differences in prosthetic feet are outlined. Based on these results, it is not recommended that the 6MWT and ADSC are used as a means to assess outcomes for different prosthetic feet

Peak Trailing Limb Angle and Propulsion Symmetry in Individuals with Below Knee Amputation

Background: Individuals with lower extremity amputation often present with kinematic and kinetic gait asymmetries and often have difficulty achieving symmetrical walking using their prescribed prosthesis. To understand the impact of limb loss on gait measures, studies often compare individuals with lower limb amputation to healthy control participants or compare the amputated limb to the uninvolved limb while completing a specified task like steady state walking. Commonly implemented treatments for individuals with lower limb amputation are based upon the assumption that equal use of both legs (symmetry) while completing bipedal tasks (e.g., walking) would be beneficial, matching the behavior seen in healthy control individuals. Underlying kinematic or kinetic symmetry, as well as a potential relationship of the two biomechanical gait variables in individuals with below knee amputation have not been thoroughly evaluated during steady state treadmill walking. Methods: We explored potential underlying (a)symmetries in peak trailing limb angle (kinematic) and peak anterior ground reaction force (kinetic) in individuals with below knee amputation walking at self-selected walking speed on a treadmill without upper extremity support. We then implemented real-time visual feedback to alter symmetry and examine the potential relationship between peak trailing limb angle and peak anterior ground reaction force. Later, we recruited and tested healthy control individuals with and without a solid ankle foot orthosis (SAFO) walking at their self-selected walking speed on a treadmill and exposed them to a similar visual feedback program to alter their baseline (a)symmetry. Population: We enrolled eleven of the planned twenty-four individuals with unilateral below knee amputation and fourteen healthy control participants without any lower extremity pathology or gait abnormality. Results: We found that individuals with below knee amputation do have peak trailing limb and anterior ground reaction force asymmetries and unencumbered healthy control individuals demonstrate symmetry of the same outcome measures while walking on a treadmill at self-selected walking speed. The use of real time visual feedback yielded statistically significant differences in peak trailing limb angle in healthy control participants without a solid ankle foot orthosis (p=0.04), peak and impulse anterior ground reaction forces when wearing a solid ankle foot orthosis (p=0.04). Statistically significant correlation between peak trailing limb angle and peak anterior ground reaction force were found in individuals with below knee amputation at baseline (p=0.0004), with real time visual feedback for peak trailing limb angle (p\u3c0.0001), and peak anterior ground reaction force (p=0.0002). Conclusions: Real time visual feedback is one intervention used to alter walking symmetry. Our results do not demonstrate an overwhelming response to real time visual feedback by individuals with below knee amputation or their healthy control counterparts and should be interpreted with caution. This work does provide meaningful information for further studies and interventions to alter symmetry during steady state walking and begins to explore the potential relationship between peak trailing limb angel and peak anterior ground reaction force production during self-selected treadmill walking in individuals with below knee amputation as well as otherwise healthy control individuals

Technology for monitoring everyday prosthesis use: a systematic review

BACKGROUND Understanding how prostheses are used in everyday life is central to the design, provision and evaluation of prosthetic devices and associated services. This paper reviews the scientific literature on methodologies and technologies that have been used to assess the daily use of both upper- and lower-limb prostheses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long-term monitoring. METHODS A systematic literature search was conducted in PubMed, Web of Science, Scopus, CINAHL and EMBASE of studies that monitored the activity of prosthesis-users during daily-living. RESULTS 60 lower-limb studies and 9 upper-limb studies were identified for inclusion in the review. The first studies in the lower-limb field date from the 1990s and the number has increased steadily since the early 2000s. In contrast, the studies in the upper-limb field have only begun to emerge over the past few years. The early lower-limb studies focused on the development or validation of actimeters, algorithms and/or scores for activity classification. However, most of the recent lower-limb studies used activity monitoring to compare prosthetic components. The lower-limb studies mainly used step-counts as their only measure of activity, focusing on the amount of activity, not the type and quality of movements. In comparison, the small number of upper-limb studies were fairly evenly spread between development of algorithms, comparison of everyday activity to clinical scores, and comparison of different prosthesis user populations. Most upper-limb papers reported the degree of symmetry in activity levels between the arm with the prosthesis and the intact arm. CONCLUSIONS Activity monitoring technology used in conjunction with clinical scores and user feedback, offers significant insights into how prostheses are used and whether they meet the user’s requirements. However, the cost, limited battery-life and lack of availability in many countries mean that using sensors to understand the daily use of prostheses and the types of activity being performed has not yet become a feasible standard clinical practice. This review provides recommendations for the research and clinical communities to advance this area for the benefit of prosthesis users

A Lower Limb Prosthesis with Active Alignment for Reduced Limb Loading

Over the past decade, the growing field of robotics has created new possibilities in lower limb prostheses. The focus of these new prostheses has been replicating the dynamics of the lost limb in order to restore gait of individuals with lower limb amputations to healthy norms. This places demanding loads on the residual limb. Compensation by the rest of body is high, causes overloading of intact joints and can lead to deterioration of mobility and overall health. Abnormalities remain present in the person’s gait, stemming from the loading of soft tissue and the altered anatomy of the affected limb. In this dissertation, an experimental prosthesis is developed with systematic, simulation based techniques. Kinematics and kinetics of the prosthesis design are altered in order to actively realign the limb in relation to the center of pressure during stance, allowing positive power to be generated by the prosthesis while actively reducing the magnitude of the sagittal moment transferred to the residual limb. Initial findings show that during walking with the experimental device compared to a daily use prosthesis, peak pressures on the residual limb are lowered by over 10% while maintaining walking speed

Crowd-sourced amputee gait data : a feasibility study using YouTube videos of unilateral trans-femoral gait

Collecting large datasets of amputee gait data is notoriously difficult. Additionally, collecting data on less prevalent amputations or on gait activities other than level walking and running on hard surfaces is rarely attempted. However, with the wealth of user-generated content on the Internet, the scope for collecting amputee gait data from alternative sources other than traditional gait labs is intriguing. Here we investigate the potential of YouTube videos to provide gait data on amputee walking. We use an example dataset of trans-femoral amputees level walking at self-selected speeds to collect temporal gait parameters and calculate gait asymmetry. We compare our YouTube data with typical literature values, and show that our methodology produces results that are highly comparable to data collected in a traditional manner. The similarity between the results of our novel methodology and literature values lends confidence to our technique. Nevertheless, clear challenges with the collection and interpretation of crowd-sourced gait data remain, including long term access to datasets, and a lack of validity and reliability studies in this area