Determination of ankle muscle power in normal gait using an EMG-to-force processing approach

The ankle dorsiflexion kinetics demand to increase swing phase foot-ground clearance: implications for assistive device design and energy demands

BACKGROUND

The ankle is usually highly effective in modulating the swing foot's trajectory to ensure safe ground clearance but there are few reports of ankle kinetics and mechanical energy exchange during the gait cycle swing phase. Previous work has investigated ankle swing mechanics during normal walking but with developments in devices providing dorsiflexion assistance, it is now essential to understand the minimal kinetic requirements for increasing ankle dorsiflexion, particularly for devices employing energy harvesting or utilizing lighter and lower power energy sources or actuators.

METHODS

Using a real-time treadmill-walking biofeedback technique, swing phase ankle dorsiflexion was experimentally controlled to increase foot-ground clearance by 4 cm achieved via increased ankle dorsiflexion. Swing phase ankle moments and dorsiflexor muscle forces were estimated using AnyBody modeling system. It was hypothesized that increasing foot-ground clearance by 4 cm, employing only the ankle joint, would require significantly higher dorsiflexion moments and muscle forces than a normal walking control condition.

RESULTS

Results did not confirm significantly increased ankle moments with augmented dorsiflexion, with 0.02 N.m/kg at toe-off reducing to zero by the end of swing. Tibialis Anterior muscle force incremented significantly from 2 to 4 N/kg after toe-off, due to coactivation with the Soleus. To ensure an additional 4 cm mid swing foot-ground clearance, an estimated additional 0.003 Joules/kg is required to be released immediately after toe-off.

CONCLUSION

This study highlights the interplay between ankle moments, muscle forces, and energy demands during swing phase ankle dorsiflexion, offering insights for the design of ankle assistive technologies. External devices do not need to deliver significantly greater ankle moments to increase ankle dorsiflexion but, they should offer higher mechanical power to provide rapid bursts of energy to facilitate quick dorsiflexion transitions before reaching Minimum Foot Clearance event. Additionally, for ankle-related bio-inspired devices incorporating artificial muscles or humanoid robots that aim to replicate natural ankle biomechanics, the inclusion of supplementary Tibialis Anterior forces is crucial due to Tibialis Anterior and Soleus co-activation. These design strategies ensures that ankle assistive technologies are both effective and aligned with the biomechanical realities of human movement.

An EMG-to-Force Processing Approach to Estimating Knee Muscle Forces during Adult, Self-Selected Speed Gait

BACKGROUND

The purpose of this study was to determine the force production during self-selected speed normal gait by muscle-tendon units that cross the knee. The force of a single knee muscle is not directly measurable without invasive methods, yet invasive techniques are not appropriate for clinical use. Thus, an EMG-to-force processing (EFP) model was developed which scaled muscle-tendon unit (MTU) force output to gait EMG.

METHODS

An EMG-to-force processing (EFP) model was developed which scaled muscle-tendon unit (MTU) force output to gait EMG. Active muscle force power was defined as the product of MTU forces (derived from EFP) and that muscle's contraction velocity. Net knee EFP moment was determined by summing individual active knee muscle moments. Net knee moments were also calculated for these study participants via inverse dynamics (kinetics plus kinematics, KIN). The inverse dynamics technique used are well accepted and the KIN net moment was used to validate or reject this model. Closeness of fit of the moment power curves for the two methods (during active muscle forces) was used to validate the model.

RESULTS

The correlation between the EFP and KIN methods was sufficiently close, suggesting validation of the model's ability to provide reasonable estimates of knee muscle forces.

CONCLUSIONS

The EMG-to-force processing approach provides reasonable estimates of active individual knee muscle forces in self-selected speed walking in neurologically intact adults.

Assessment methodology for human-exoskeleton interactions: Kinetic analysis based on muscle activation

During the development and assessment of an exoskeleton, many different analyzes need to be performed. The most frequently used evaluate the changes in muscle activations, metabolic consumption, kinematics, and kinetics. Since human-exoskeleton interactions are based on the exchange of forces and torques, the latter of these, kinetic analyzes, are essential and provide indispensable evaluation indices. Kinetic analyzes, however, require access to, and use of, complex experimental apparatus, involving many instruments and implicating lengthy data analysis processes. The proposed methodology in this paper, which is based on data collected via EMG and motion capture systems, considerably reduces this burden by calculating kinetic parameters, such as torque and power, without needing ground reaction force measurements. This considerably reduces the number of instruments used, allows the calculation of kinetic parameters even when the use of force sensors is problematic, does not need any dedicated software, and will be shown to have high statistical validity. The method, in fact, combines data found in the literature with those collected in the laboratory, allowing the analysis to be carried out over a much greater number of cycles than would normally be collected with force plates, thus enabling easy access to statistical analysis. This new approach evaluates the kinetic effects of the exoskeleton with respect to changes induced in the user's kinematics and muscular activation patterns and provides indices that quantify the assistance in terms of torque (AMI) and power (API). Following the User-Center Design approach, which requires driving the development process as feedback from the assessment process, this aspect is critical. Therefore, by enabling easy access to the assessment process, the development of exoskeletons could be positively affected.

Building Effective Machine Learning Models for Ankle Joint Power Estimation During Walking Using FMG Sensors

Ankle joint power is usually determined by a complex process that involves heavy equipment and complex biomechanical models. Instead of using heavy equipment, we proposed effective machine learning (ML) and deep learning (DL) models to estimate the ankle joint power using force myography (FMG) sensors. In this study, FMG signals were collected from nine young, healthy participants. The task was to walk on a special treadmill for five different velocities with a respective duration of 1 min. FMG signals were collected from an FMG strap that consists of 8 force resisting sensor (FSR) sensors. The strap was positioned around the lower leg. The ground truth value for ankle joint power was determined with the help of a complex biomechanical model. At first, the predictors' value was preprocessed using a rolling mean filter. Following, three sets of features were formed where the first set includes raw FMG signals, and the other two sets contained time-domain and frequency-domain features extracted using the first set. Cat Boost Regressor (CBR), Long-Short Term Memory (LSTM), and Convolutional Neural Network (CNN) were trained and tested using these three features sets. The results presented in this study showed a correlation coefficient of R = 0.91 ± 0.07 for intrasubject testing and were found acceptable when compared to other similar studies. The CNN on raw features and the LSTM on time-domain features outperformed the other variations. Aside from that, a performance gap between the slowest and fastest walking distance was observed. The results from this study showed that it was possible to achieve an acceptable correlation coefficient in the prediction of ankle joint power using FMG sensors with an appropriate combination of feature set and ML model.

Contraction fatigability during interleaved neuromuscular electrical stimulation of the ankle dorsiflexors does not depend on contraction amplitude

Interleaved neuromuscular electrical stimulation (iNMES) involves alternating stimulus pulses between the tibialis anterior muscle and common peroneal nerve. The current investigation aimed to characterize the relationship between contraction amplitude, motor unit (MU) “overlap”, and contraction fatigability during iNMES. It was hypothesized that as iNMES generates progressively larger contractions, more MUs would be recruited from both sites (i.e., more MU overlap), resulting in more fatigability for larger than smaller contractions. Fourteen participants completed 3 sessions. Fatigability was assessed as the decline in torque over 180 contractions (0.3 s “on”, 0.7 s “off”) when iNMES was delivered to produce initial contractions of ∼5%, 15%, or 30% of a maximal voluntary contraction. Although MU overlap increased significantly with contraction amplitude, the relative (percent) decline in torque was not different between the contraction amplitudes and torque declined on average by 23%. Contraction fatigability was not significantly correlated with either MU overlap or initial contraction amplitude. In conclusion, iNMES can produce fatigue-resistant contractions across a functionally-meaningful range of contraction amplitudes for rehabilitation.

Novelty Interleaved neuromuscular electrical stimulation progressively recruits MUs as contraction amplitude increases. However, the relative amount of fatigability of recruited MUs was not different as contraction amplitude increased. This suggests iNMES can be used effectively to produce fatigue-resistant and functionally meaningful contractions.

Fatigue and Discomfort During Spatially Distributed Sequential Stimulation of Tibialis Anterior

Neuromuscular electrical stimulation is conventionally applied through a single pair of electrodes over the muscle belly, denominated single electrode stimulation (SES). SES is limited by discomfort and incomplete motor-unit recruitment, restricting electrically-evoked torque and promoting premature fatigue-induced torque-decline. Sequential stimulation involving rotation of pulses between multiple pairs of electrodes has been proposed as an alternative, denominated spatially distributed sequential stimulation (SDSS). The present aim was to compare discomfort, maximal-tolerated torque, and fatigue-related outcomes between SES and SDSS of tibialis anterior. Ten healthy participants completed two experimental sessions. The self-reported discomfort at sub-maximal torque, the maximal-tolerated torque, fatigue-induced torque-decline during, and doublet-twitch torque at 10- and 100-Hz before and after, 300 intermittent (0.6-s-ON-0.6-s-OFF) isokinetic contractions were compared between SES and SDSS. SDSS stimulation improved fatigue-related outcomes, whereas increased discomfort and reduced maximal-tolerated torque. SDSS holds promise for reducing fatigue. However, limited torque production and associated discomfort may limit its utility for rehabilitation/training.

Estimation of Ankle Joint Power during Walking Using Two Inertial Sensors

(1) Background: Ankle joint power, as an indicator of the ability to control lower limbs, is of great relevance for clinical diagnosis of gait impairment and control of lower limb prosthesis. However, the majority of available techniques for estimating joint power are based on inverse dynamics methods, which require performing a biomechanical analysis of the foot and using a highly instrumented environment to tune the parameters of the resulting biomechanical model. Such techniques are not generally applicable to real-world scenarios in which gait monitoring outside of the clinical setting is desired. This paper proposes a viable alternative to such techniques by using machine learning algorithms to estimate ankle joint power from data collected by two miniature inertial measurement units (IMUs) on the foot and shank, (2) Methods: Nine participants walked on a force-plate-instrumented treadmill wearing two IMUs. The data from the IMUs were processed to train and test a random forest model to estimate ankle joint power. The performance of the model was then evaluated by comparing the estimated power values to the reference values provided by the motion tracking system and the force-plate-instrumented treadmill. (3) Results: The proposed method achieved a high accuracy with the correlation coefficient, root mean square error, and normalized root mean square error of 0.98, 0.06 w/kg, and 1.05% in the intra-subject test, and 0.92, 0.13 w/kg, and 2.37% in inter-subject test, respectively. The difference between the predicted and true peak power values was 0.01 w/kg and 0.14 w/kg with a delay of 0.4% and 0.4% of gait cycle duration for the intra- and inter-subject testing, respectively. (4) Conclusions: The results of this study demonstrate the feasibility of using only two IMUs to estimate ankle joint power. The proposed technique provides a basis for developing a portable and compact gait monitoring system that can potentially offer monitoring and reporting on ankle joint power in real-time during activities of daily living.

Functional Task Training Combined With Electrical Stimulation Improves Motor Capacity in Children With Unilateral Cerebral Palsy: A Single-Subject Design

PURPOSE

Reduced propulsive capability can impact negatively on mobility activities of many children with spastic unilateral cerebral palsy (SUCP). This study investigated the effect of a task-oriented training program combined with functional electrical stimulation (FES) on the motor capacity of children with SUCP.

METHODS

Single-case A-B design with follow-up. Gross motor function and biomechanical walking data of 4 children with SUCP were measured repeatedly across the baseline, intervention, and follow-up phases. Intervention was a task-oriented training program combined with FES applied on the gastrocnemius. Outcome variables included gait speed, impulsive torque, and ankle/hip power generation ratio. The 2-SD band and celeration line methods compared outcomes among the baseline, intervention, and follow-up periods.

RESULTS

One child improved walking speed. All children improved impulsive torque and ankle/hip power ratio of the affected leg. All children improved gross motor function.

CONCLUSION

The intervention improved children's propulsive capability and positively influenced their mobility.

A systematic review of approaches to modelling lower limb muscle forces during gait: Applicability to clinical gait analyses

Computational methods to estimate muscle forces during walking are becoming more common in biomechanical research but not yet in clinical gait analysis. This systematic review aims to identify the current state-of-the-art, examine the differences between approaches, and consider applicability of the current approaches in clinical gait analysis. A systematic database search identified studies including estimated muscle force profiles of the lower limb during healthy walking. These were rated for quality and the muscle force profiles digitised for comparison. From 13.449 identified studies, 22 were finally included which used four modelling approaches: static optimisation, enhanced static optimisation, forward dynamics and EMG-driven. These used a range of different musculoskeletal models, muscle-tendon characteristics and cost functions. There is visually broad agreement between and within approaches about when muscles are active throughout the gait cycle. There remain, considerable differences (CV 7%-151%, range of timing of peak forces in gait cycle 1%-31%) in patterns and magnitudes of force between and within modelling approaches. The main source of this variability is not clear. Different musculoskeletal models, experimental protocols, and modelling approaches will clearly have an effect as will the variability of joint kinetics between healthy individuals. Limited validation of modelling approaches, particularly at the level of individual participants, makes it difficult to conclude if any of the approaches give consistently better estimates than others. While muscle force modelling has clear potential to enhance clinical gait analyses future research is needed to improve validation, accuracy and feasibility of implementation in clinical practice.

Inter-individual similarities and variations in muscle forces acting on the ankle joint during gait

Muscle forces acting over the ankle joint play an important role in the forward progression of the body during gait. Yet despite the importance of ankle muscle forces, direct in-vivo measurements are neither possible nor practical. This makes musculoskeletal simulation useful as an indirect technique to quantify the muscle forces at work during locomotion. The purpose of this study was to: 1) identify the maximum peaks of individual ankle muscle forces during gait; 2) investigate the order over which the muscles are sorted based on their maximum peak force. Three-dimensional kinematics and ground reaction forces were measured during the gait of 10 healthy subjects, and the data so obtained were input into the musculoskeletal model distributed with the OpenSim software. In all 10 individuals we observed that the soleus muscle generated the greatest strength both in dynamic (1856.1N) and isometric (3549N) conditions, followed by the gastrocnemius in dynamic conditions (1232.5N). For all other muscles, however, the sequence looks different across subjects, so the k-means clustering method was used to obtain one main order over which the muscles' peak-forces are sorted. The results indicate a common theme, with some variations in the maximum peaks of ankle muscle force across subjects.

Estimates of individual muscle power production in normal adult walking

Background

The purpose of this study was to determine the contribution of individual hip muscles to the net hip power in normal adult self-selected speed walking. A further goal was to examine each muscle’s role in propulsion or support of the body during that task.

Methods

An EMG-to-force processing (EFP) model was developed which scaled muscle-tendon unit (MTU) force output to gait EMG. Active muscle power was defined as the product of MTU forces (derived from EFP) and that muscle’s contraction velocity. Passive hip power was estimated from passive moments associates with hip position (angle of flexion (extension)) and the hip’s angular velocity. Net hip EFP power was determined by summing individual active hip muscle power plus the net passive hip power at each percent gait cycle interval. Net hip power was also calculated for these study participants via inverse dynamics (kinetics plus kinematics, KIN). The inverse dynamics technique – well accepted in the biomechanics literature – was used as a “gold standard” for validation of this EFP model. Closeness of fit of the power curves of the two methods was used to validate the model.

Results

The correlation between the EFP and KIN methods was sufficiently close, suggesting validation of the model’s ability to provide reasonable estimates of power produced by individual hip muscles. Key findings were that (1) most muscles undergo a stretch-shorten cycle of muscle contraction, (2) greatest power was produced by the hip abductors, and (3) the hip adductors contribute to either hip adduction or hip extension (but not both).

Conclusions

The EMG-to-force processing approach provides reasonable estimates of individual hip muscle forces in self-selected speed walking in neurologically-intact adults.

Torque, Current, and Discomfort During 3 Types of Neuromuscular Electrical Stimulation of Tibialis Anterior

BACKGROUND

The benefits of neuromuscular electrical stimulation (NMES) for rehabilitation depend on the capacity to generate functionally relevant torque with minimal fatigability and discomfort. Traditionally, NMES is delivered either over a muscle belly (mNMES) or a nerve trunk (nNMES). Recently, a technique that minimizes contraction fatigability by alternating pulses between the mNMES and nNMES sites, termed "interleaved" NMES (iNMES), was developed. However, discomfort and the ability to generate large torque during iNMES have not been explored adequately.

OBJECTIVE

The study objective was to compare discomfort and maximal torque between mNMES, nNMES, and iNMES.

METHODS

Stimulation trains (12 pulses at 40 Hz) were delivered to produce dorsiflexion torque using mNMES, nNMES, and iNMES. Discomfort was assessed using a visual analogue scale for contractions that generated 5-30% of a maximal voluntary isometric contraction (MVIC), and for the maximal tolerable torque.

RESULTS

Discomfort scores were not different between NMES types when torque was ≤20% MVIC. At 30% MVIC, mNMES produced more discomfort than nNMES and iNMES. nNMES produced the most torque (65% MVIC), followed by iNMES (49% MVIC) and mNMES (33% MVIC); in these trials, mNMES produced more discomfort than nNMES, but not iNMES.

LIMITATIONS

The present results may be limited to individuals with no history of neuromusculoskeletal impairment.

CONCLUSIONS

In terms of discomfort, there were no differences between mNMES, nNMES, or iNMES for contractions between 5-20% MVIC. However, mNMES produced more discomfort than nNMES and iNMES for contractions of 30% MVIC, while for larger contractions, mNMES only produced more discomfort than nNMES. The advantages and disadvantages of each NMES type should be considered prior to implementation in rehabilitation programs.

Interleaved neuromuscular electrical stimulation: Motor unit recruitment overlap

INTRODUCTION

In this study, we quantified the "overlap" between motor units recruited by single pulses of neuromuscular electrical stimulation (NMES) delivered over the tibialis anterior muscle (mNMES) and the common peroneal nerve (nNMES). We then quantified the torque produced when pulses were alternated between the mNMES and nNMES sites at 40 Hz ("interleaved" NMES; iNMES).

METHODS

Overlap was assessed by comparing torque produced by twitches evoked by mNMES, nNMES, and both delivered together, over a range of stimulus intensities. Trains of iNMES were delivered at the intensity that produced the lowest overlap.

RESULTS

Overlap was lowest (5%) when twitches evoked by both mNMES and nNMES produced 10% peak twitch torque. iNMES delivered at this intensity generated 25% of maximal voluntary dorsiflexion torque (11 Nm).

DISCUSSION

Low intensity iNMES leads to low overlap and produces torque that is functionally relevant to evoke dorsiflexion during walking. Muscle Nerve 55: 490-499, 2017.

Quantitative sensory and motor measures detect change overtime and correlate with walking speed in individuals with multiple sclerosis

BACKGROUND

Impairments of sensation, strength, and walking are common in multiple sclerosis (MS). The relationship among these abnormalities and how they change over time remains unclear.

OBJECTIVE

To determine the extent that quantitative lower extremity sensory and motor measures detect abnormalities over time, relate to global disability, and to walking speed in individuals with MS.

METHODS

This prospective, longitudinal analysis evaluated 136 MS subjects. Measures included measures of leg strength, sensation, the Expanded Disability Status Scale(EDSS) and timed 25-foot walk test (T25FW). Mixed effects regression models were used.

RESULTS

Our cohort׳s mean age is 44.3±10.8 years (mean±SD), EDSS score range 0–7.5, 66% were females, and follow-up time was 2.1±1.2 years. Strength significantly changed over time; the RRMS group demonstrated the greatest changes in ADF (3.3 lbs/yr) while the PPMS group showed significant HF changes (−2.1 lbs/yr). Walking speed was affected most by HF, especially in the weakest individuals (HF<20 lbs); T25FW increased by 0.20 s for each 1 lb loss (p=0.001). Likewise T25FW changed by 0.19 s for each 1 lb change in ADF (p<0.01).

CONCLUSION

Quantitative measures detected changes in sensation and strength over time, despite a stable respective functional systems scores of the EDSS. Quantitative measurement tools may improve the sensitivity of disability measures in MS and further investigation of these tools as outcomes in future clinical trials of rehabilitative and neuroreparative interventions is warranted.

The impact of dynamic balance measures on walking performance in multiple sclerosis

BACKGROUND

Static posture imbalance and gait dysfunction are common in individuals with multiple sclerosis (MS). Although the impact of strength and static balance on walking has been examined, the impact of dynamic standing balance on walking in MS remains unclear.

OBJECTIVE

To determine the impact of dynamic balance, static balance, sensation, and strength measures on walking in individuals with MS.

METHODS

Fifty-two individuals with MS (27 women; 26 relapsing-remitting; mean age = 45.6 ± 10.3 years; median Expanded Disability Status Scale score = 3.5) participated in posturography testing (Kistler-9281 force plate), hip flexion, hip extension, ankle dorsiflexion strength (Microfet2 hand-held dynamometer), sensation (Vibratron II), and walk velocity (Optotrak Motion Analysis System). Analyses included, Mann-Whitney, Spearman correlation coefficients, and multiple regression.

RESULTS

All measures were abnormal in individuals with MS when compared with norms (P < .05). Static balance (eyes open, feet together [EOFT]), anterior-posterior (AP) dynamic sway, and hip extension strength were strongly correlated with walking velocity (AP sway r = 0.68; hip extension strength r = 0.73; EOFT r = -0.40). Together, AP dynamic sway (ρr = 0.71; P < .001), hip extension strength (ρr = 0.54; P < .001), and EOFT static balance (ρr = -0.41; P = .01) explained more than 70% of the variance in walking velocity (P < .001).

CONCLUSIONS

AP dynamic sway affects walking performance in MS. A combined evaluation of dynamic balance, static balance, and strength may lead to a better understanding of walking mechanisms and the development of strategies to improve walking.

The functional role of the triceps surae muscle during human locomotion

Aim

Despite numerous studies addressing the issue, it remains unclear whether the triceps surae muscle group generates forward propulsive force during gait, commonly identified as ‘push-off’. In order to challenge the push-off postulate, one must probe the effect of varying the propulsive force while annulling the effect of the progression velocity. This can be obtained by adding a load to the subject while maintaining the same progression velocity.

Methods

Ten healthy subjects initiated gait in both unloaded and loaded conditions (about 30% of body weight attached at abdominal level), for two walking velocities, spontaneous and fast. Ground reaction force and EMG activity of soleus and gastrocnemius medialis and lateralis muscles of the stance leg were recorded. Centre of mass velocity and position, centre of pressure position, and disequilibrium torque were calculated.

Results

At spontaneous velocity, adding the load increased disequilibrium torque and propulsive force. However, load had no effect on the vertical braking force or amplitude of triceps activity. At fast progression velocity, disequilibrium torque, vertical braking force and triceps EMG increased with respect to spontaneous velocity. Still, adding the load did not further increase braking force or EMG.

Conclusions

Triceps surae is not responsible for the generation of propulsive force but is merely supporting the body during walking and restraining it from falling. By controlling the disequilibrium torque, however, triceps can affect the propulsive force through the exchange of potential into kinetic energy.

Influence of joint models on lower-limb musculo-tendon forces and three-dimensional joint reaction forces during gait

Several three-dimensional (3D) lower-limb musculo-skeletal models have been developed for gait analysis and different hip, knee and ankle joint models have been considered in the literature. Conversely to the influence of the musculo-tendon geometry, the influence of the joint models - i.e. number of degrees of freedom and passive joint moments - on the estimated musculo-tendon forces and 3D joint reaction forces has not been extensively examined.

In this paper musculo-tendon forces and 3D joint reaction forces have been estimated for one subject and one gait cycle with nine variations of a musculoskeletal model and outputs have been compared to measured electromyographic signals and knee joint contact forces. The model outputs are generally in line with the measured signals. However, the 3D joint reaction forces were higher than published values and the contact forces measured for the subject. The results of this study show that, with more degrees of freedom in the model, the musculo-tendon forces and the 3D joint reaction forces tend to increase but with some redistribution between the muscles. In addition, when taking into account passive joint moments, the 3D joint reaction forces tend to decrease during the stance phase and increase during the swing phase.

Although further investigations are needed, a five-degree-of-freedom lower-limb musculo-skeletal model with some angle-dependent joint coupling and stiffness seems to provide satisfactory musculo-tendon forces and 3D joint reaction forces.