Knee angle-specific EMG normalization: The use of polynomial based EMG-angle relationships

A Comparison of Bioelectric and Biomechanical EMG Normalization Techniques in Healthy Older and Young Adults during Walking Gait

This study compares biomechanical and bioelectric electromyography (EMG) normalization techniques across disparate age cohorts during walking to assess the impact of normalization methods on the functional interpretation of EMG data. The biomechanical method involved scaling EMG to a target absolute torque (EMGTS) from a joint-specific task and the chosen bioelectric methods were peak and mean normalization taken from the EMG signal during gait, referred to as dynamic mean and dynamic peak normalization (EMGMean and EMGPeak). The effects of normalization on EMG amplitude, activation pattern, and inter-subject variability were compared between disparate cohorts, including OLD (76.6 yrs N = 12) and YOUNG (26.6 yrs N = 12), in five lower-limb muscles. EMGPeak normalization resulted in differences between YOUNG and OLD cohorts in Biceps Femoris (BF) and Medial Gastrocnemius (MG) that were not observed with EMGMean or EMGTS normalization. EMGPeak and EMGMean normalization also demonstrated interactions between age and the phase of gait in BF that were not seen with EMGTS. Correlations showed that activation patterns across the gait cycle were similar between all methods for both age groups and the coefficient of variation comparisons found that EMGTS produced the greatest inter-subject variability. We have shown that the normalization technique can influence the interpretation of findings when comparing disparate populations, highlighting the need to carefully interpret functional differences in EMG between disparate cohorts.

Inter- and Intra-Individual Differences in EMG and MMG during Maximal, Bilateral, Dynamic Leg Extensions

The purpose of this study was to compare the composite, inter-individual, and intra-individual differences in the patterns of responses for electromyographic (EMG) and mechanomyographic (MMG) amplitude (AMP) and mean power frequency (MPF) during fatiguing, maximal, bilateral, and isokinetic leg extension muscle actions. Thirteen recreationally active men (age = 21.7 ± 2.6 years; body mass = 79.8 ± 11.5 kg; height = 174.2 ± 12.7 cm) performed maximal, bilateral leg extensions at 180°·s⁻¹ until the torque values dropped to 50% of peak torque for two consecutive repetitions. The EMG and MMG signals from the vastus lateralis (VL) muscles of both limbs were recorded. Four 2(Leg) × 19(time) repeated measures ANOVAs were conducted to examine mean differences for EMG AMP, EMG MPF, MMG AMP, and MMG MPF between limbs, and polynomial regression analyses were performed to identify the patterns of neuromuscular responses. The results indicated no significant differences between limbs for EMG AMP (p = 0.44), EMG MPF (p = 0.33), MMG AMP (p = 0.89), or MMG MPF (p = 0.52). Polynomial regression analyses demonstrated substantial inter-individual variability. Inferences made regarding the patterns of neuromuscular responses to fatiguing and bilateral muscle actions should be considered on a subject-by-subject basis.

Differences in Maximum Voluntary Excitation Between Isometric and Dynamic Contractions are Age-Dependent

Obtaining true maximum voluntary excitation appears to be more difficult in older populations than in young populations. The aims of this study were (1) to determine whether differences in maximum voluntary excitation obtained from maximum voluntary isometric contraction (MVIC) and (sub-)maximum voluntary dynamic contraction [(s-)MVDC] are age dependent, and (2) to determine how normalizing electromyographic signals to corresponding maximum voluntary excitations affects variance between participants and the likelihood of normalized signals exceeding 100%. MVIC, s-MVDC, and MVDC were recorded in 10 young women, and MVIC and s-MVDC were recorded in 19 older women. A significant age × contraction mode interaction effect was found for vastus lateralis (P = .04). In young women, MVDC elicited the highest maximum voluntary excitation for vastus lateralis and rectus femoris (P < .05). In older women, no differences in maximum voluntary excitation were found (P > .05). Normalization to dynamic contractions resulted in lower between-participant variance of electromyography amplitudes, though not for all muscles, and decreased the number of normalized signals exceeding 100% in young women. These findings indicate that differences in maximum voluntary excitation across contraction modes are age dependent. Therefore, one should be cautious when comparing normalized signals between age groups; however, overall dynamic contractions may be preferable over isometric contractions for normalization purposes.

Biomechanical Methods to Quantify Muscle Effort During Resistance Exercise

Chiu, LZF. Biomechanical methods to quantify muscle effort during resistance exercise. J Strength Cond Res 32(2): 502-513, 2018-Muscle hypertrophy and strength adaptations elicited by resistance training are dependent on the force exerted by active muscles. As an exercise may use many muscles, determining force for individual muscles or muscle groupings is important to understand the relation between an exercise and these adaptations. Muscle effort-the amount of force or a surrogate measure related to the amount of force exerted during a task-can be quantified using biomechanical methods. The purpose of this review was to summarize the biomechanical methods used to estimate muscle effort in movements, particularly resistance training exercises. These approaches include the following: (a) inverse dynamics with rigid body models, (b) forward dynamics and EMG-driven models, (c) normalized EMG, and (d) inverse dynamics with point-mass models. Rigid body models quantify muscle effort as net joint moments. Forward dynamics and EMG-driven models estimate muscle force as well as determine the effect of a muscle's action throughout the body. Nonlinear relations between EMG and muscle force and normalization reference action selection affect the usefulness of EMG as a measure of muscle effort. Point-mass models include kinetics calculated from barbell (or other implement) kinematics recorded using electromechanical transducers or measured using force platforms. Point-mass models only allow the net force exerted on the barbell or lifter-barbell system to be determined, so they cannot be used to estimate muscle effort. Data from studies using rigid body models, normalized EMG, and musculoskeletal modeling should be combined to develop hypotheses regarding muscle effort; these hypotheses should be verified by training interventions.

The Advantages of Normalizing Electromyography to Ballistic Rather than Isometric or Isokinetic Tasks

Isometric tasks have been a standard for electromyography (EMG) normalization stemming from anatomic and physiologic stability observed during contraction. Ballistic dynamic tasks have the benefit of eliciting maximum EMG signals for normalization, despite having the potential for greater signal variability. It is the purpose of this study to compare maximum voluntary isometric contraction (MVIC) to nonisometric tasks with increasing degrees of extrinsic variability, ie, joint range of motion, velocity, rate of contraction, etc., to determine if the ballistic tasks, which elicit larger peak EMG signals, are more reliable than the constrained MVIC. Fifteen subjects performed MVIC, isokinetic, maximum countermovement jump, and sprint tasks while EMG was collected from 9 muscles in the quadriceps, hamstrings, and lower leg. The results revealed the unconstrained ballistic tasks were more reliable compared to the constrained MVIC and isokinetic tasks for all triceps surae muscles. The EMG from sprinting was more reliable than the constrained cases for both the hamstrings and vasti. The most reliable EMG signals occurred when the body was permitted its natural, unconstrained motion. These results suggest that EMG is best normalized using ballistic tasks to provide the greatest within-subject reliability, which beneficially yield maximum EMG values.

The effect of swinging the arms on muscle activation and production of leg force during ski skating at different skiing speeds

The study investigated the effects of arm swing during leg push-off in V2-alternate/G4 skating on neuromuscular activation and force production by the leg muscles. Nine skilled cross-country skiers performed V2-alternate skating without poles at moderate, high, and maximal speeds, both with free (SWING) and restricted arm swing (NOSWING). Maximal speed was 5% greater in SWING (P<0.01), while neuromuscular activation and produced forces did not differ between techniques. At both moderate and high speed the maximal (2% and 5%, respectively) and average (both 5%) vertical force and associated impulse (10% and 14%) were greater with SWING (all P<0.05). At high speed range of motion and angular velocity of knee flexion were 24% greater with SWING (both P<0.05), while average EMG of m. biceps femoris was 31% lower (all P<0.05) in SWING. In a similar manner, the average EMG of m. vastus medialis and m. biceps femoris were lower (17% and 32%, P<0.05) during the following knee extension. Thus, swinging the arms while performing V2-alternate can enhance both maximal speed and skiing economy at moderate and, in particularly, high speeds.

Regional Surface Electromyography of the Vastus Lateralis During Strength and Power Exercises

Neuromuscular activation during and chronic adaptation from exercise are innately linked and both can vary along a muscle's length. During high-force and high-speed exercise, intramuscular hypertrophy follows set patterns that provide the greatest biomechanical advantages. However, it is unknown if muscle activity as recorded by surface electromyography (sEMG) will follow these patterns. The purpose of the present study was to compare vastus lateralis intramuscular sEMG during the heavy squat (HS) and unloaded jump squat (JS) exercises. Ten subjects performed HS with 80% of maximum load and unloaded JS to parallel-depth, while intramuscular peak sEMG and mean sEMG were measured at 33% (proximal), 50% (middle), and 67% (distal) thigh length. Muscle activity was compared between regions and exercises using a 3 × 2 repeated measures ANOVA with Bonferoni post hoc corrections. Peak sEMG was greater proximally in JS than HS (p = 0.033), but similar in the middle and distal regions (p = 0.521, 0.594, respectively), whereas mean sEMG was similar between all regions (p = 0.150-0.979). In addition, a main effect was found in which peak and mean sEMG were greater proximally than the middle and distal regions (p = 0.001, 0.006). Muscle activity measured using sEMG displayed dissimilar patterns to previously observed regional hypertrophy. Specifically, although previous research found greater proximal hypertrophy in JS than HS, in the present study peak sEMG was greater in HS than JS. Furthermore, distally where HS elicited greater hypertrophy than JS, no differences in sEMG were present. Thus, regional sEMG appears not to be a viable tool for predicting differences in regional hypertrophy, most likely due to technological constraints and intramuscular differences in muscle structure.

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

Electromyography-Based Quantitative Representation Method for Upper-Limb Elbow Joint Angle in Sagittal Plane

This paper presents a quantitative representation method for the upper-limb elbow joint angle using only electromyography (EMG) signals for continuous elbow joint voluntary flexion and extension in the sagittal plane. The dynamics relation between the musculotendon force exerted by the biceps brachii muscle and the elbow joint angle is developed for a modified musculoskeletal model. Based on the dynamics model, a quadratic-like quantitative relationship between EMG signals and the elbow joint angle is built using a Hill-type-based muscular model. Furthermore, a state switching model is designed to stabilize the transition of EMG signals between different muscle contraction motions during the whole movement. To evaluate the efficiency of the method, ten subjects performed continuous experiments during a 4-day period and five of them performed a subsequent consecutive stepping test. The results were calculated in real-time and used as control reference to drive an exoskeleton device bilaterally. The experimental results indicate that the proposed method can provide suitable prediction results with root-mean-square (RMS) errors of below 10° in continuous motion and RMS errors of below 10° in stepping motion with 20° and 30° increments. It is also easier to calibrate and implement.