Local Dynamic Stability of Trunk During Gait is Responsive to Rehabilitation in Subjects with Primary Degenerative Cerebellar Ataxia.

This study aimed to assess the responsiveness to the rehabilitation of three trunk acceleration-derived gait indexes, namely the harmonic ratio (HR), the short-term longest Lyapunov's exponent (sLLE), and the step-to-step coefficient of variation (CV), in a sample of subjects with primary degenerative cerebellar ataxia (swCA), and investigate the correlations between their improvements (∆), clinical characteristics, and spatio-temporal and kinematic gait features. The trunk acceleration patterns in the antero-posterior (AP), medio-lateral (ML), and vertical (V) directions during gait of 21 swCA were recorded using a magneto-inertial measurement unit placed at the lower back before (T0) and after (T1) a period of inpatient rehabilitation. For comparison, a sample of 21 age- and gait speed-matched healthy subjects (HSmatched) was also included. At T1, sLLE in the AP (sLLEAP) and ML (sLLEML) directions significantly improved with moderate to large effect sizes, as well as SARA scores, stride length, and pelvic rotation. sLLEML and pelvic rotation also approached the HSmatched values at T1, suggesting a normalization of the parameter. HRs and CV did not significantly modify after rehabilitation. ∆sLLEML correlated with ∆ of the gait subscore of the SARA scale (SARAGAIT) and ∆stride length and ∆sLLEAP correlated with ∆pelvic rotation and ∆SARAGAIT. The minimal clinically important differences for sLLEML and sLLEAP were ≥ 36.16% and ≥ 28.19%, respectively, as the minimal score reflects a clinical improvement in SARA scores. When using inertial measurement units, sLLEAP and sLLEML can be considered responsive outcome measures for assessing the effectiveness of rehabilitation on trunk stability during walking in swCA.

Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results.

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment.

Instrumental Evaluation of the Effects of Vertebral Consolidation Surgery on Trunk Muscle Activations and Co-Activations in Patients with Multiple Myeloma: Preliminary Results.

Multiple myeloma (MM) patients complain of pain and stiffness limiting motility. To determine if patients can benefit from vertebroplasty, we assessed muscle activation and co-activation before and after surgery. Five patients with MM and five healthy controls performed sitting-to-standing and lifting tasks. Patients performed the task before and one month after surgery. Surface electromyography (sEMG) was recorded bilaterally over the erector spinae longissimus and rectus abdominis superior muscles to evaluate the trunk muscle activation and co-activation and their mean, maximum, and full width at half maximum were evaluated. Statistical analyses were performed to compare MM patients before and after the surgery, MM and healthy controls and to investigate any correlations between the muscle's parameters and the severity of pain in patients. The results reveal increased activations and co-activations after vertebroplasty as well as in comparison with healthy controls suggesting how MM patients try to control the trunk before and after vertebroplasty surgery. The findings confirm the beneficial effects of vertebral consolidation on the pain experienced by the patient, despite an overall increase in trunk muscle activation and co-activation. Therefore, it is important to provide patients with rehabilitation treatment early after surgery to facilitate the CNS to correctly stabilize the spine without overloading it with excessive co-activations.

Optimizing Rare Disease Gait Classification through Data Balancing and Generative AI: Insights from Hereditary Cerebellar Ataxia.

The interpretability of gait analysis studies in people with rare diseases, such as those with primary hereditary cerebellar ataxia (pwCA), is frequently limited by the small sample sizes and unbalanced datasets. The purpose of this study was to assess the effectiveness of data balancing and generative artificial intelligence (AI) algorithms in generating synthetic data reflecting the actual gait abnormalities of pwCA. Gait data of 30 pwCA (age: 51.6 ± 12.2 years; 13 females, 17 males) and 100 healthy subjects (age: 57.1 ± 10.4; 60 females, 40 males) were collected at the lumbar level with an inertial measurement unit. Subsampling, oversampling, synthetic minority oversampling, generative adversarial networks, and conditional tabular generative adversarial networks (ctGAN) were applied to generate datasets to be input to a random forest classifier. Consistency and explainability metrics were also calculated to assess the coherence of the generated dataset with known gait abnormalities of pwCA. ctGAN significantly improved the classification performance compared with the original dataset and traditional data augmentation methods. ctGAN are effective methods for balancing tabular datasets from populations with rare diseases, owing to their ability to improve diagnostic models with consistent explainability.

Identification of Gait Unbalance and Fallers Among Subjects with Cerebellar Ataxia by a Set of Trunk Acceleration-Derived Indices of Gait.

This study aimed to assess the ability of 25 gait indices to characterize gait instability and recurrent fallers among persons with primary degenerative cerebellar ataxia (pwCA), regardless of gait speed, and investigate their correlation with clinical and kinematic variables. Trunk acceleration patterns were acquired during the gait of 34 pwCA, and 34 age- and speed-matched healthy subjects (HSmatched) using an inertial measurement unit. We calculated harmonic ratios (HR), percent recurrence, percent determinism, step length coefficient of variation, short-time largest Lyapunov exponent (sLLE), normalized jerk score, log-dimensionless jerk (LDLJ-A), root mean square (RMS), and root mean square ratio of accelerations (RMSR) in each spatial direction for each participant. Unpaired t-tests or Mann-Whitney tests were performed to identify significant differences between the pwCA and HSmatched groups. Receiver operating characteristics were plotted to assess the ability to characterize gait alterations in pwCA and fallers. Optimal cutoff points were identified, and post-test probabilities were calculated. The HRs showed to characterize gait instability and pwCA fallers with high probabilities. They were correlated with disease severity and stance, swing, and double support duration, regardless of gait speed. sLLEs, RMSs, RMSRs, and LDLJ-A were slightly able to characterize the gait of pwCA but failed to characterize fallers.

Consensus Paper: Ataxic Gait.

The aim of this consensus paper is to discuss the roles of the cerebellum in human gait, as well as its assessment and therapy. Cerebellar vermis is critical for postural control. The cerebellum ensures the mapping of sensory information into temporally relevant motor commands. Mental imagery of gait involves intrinsically connected fronto-parietal networks comprising the cerebellum. Muscular activities in cerebellar patients show impaired timing of discharges, affecting the patterning of the synergies subserving locomotion. Ataxia of stance/gait is amongst the first cerebellar deficits in cerebellar disorders such as degenerative ataxias and is a disabling symptom with a high risk of falls. Prolonged discharges and increased muscle coactivation may be related to compensatory mechanisms and enhanced body sway, respectively. Essential tremor is frequently associated with mild gait ataxia. There is growing evidence for an important role of the cerebellar cortex in the pathogenesis of essential tremor. In multiple sclerosis, balance and gait are affected due to cerebellar and spinal cord involvement, as a result of disseminated demyelination and neurodegeneration impairing proprioception. In orthostatic tremor, patients often show mild-to-moderate limb and gait ataxia. The tremor generator is likely located in the posterior fossa. Tandem gait is impaired in the early stages of cerebellar disorders and may be particularly useful in the evaluation of pre-ataxic stages of progressive ataxias. Impaired inter-joint coordination and enhanced variability of gait temporal and kinetic parameters can be grasped by wearable devices such as accelerometers. Kinect is a promising low cost technology to obtain reliable measurements and remote assessments of gait. Deep learning methods are being developed in order to help clinicians in the diagnosis and decision-making process. Locomotor adaptation is impaired in cerebellar patients. Coordinative training aims to improve the coordinative strategy and foot placements across strides, cerebellar patients benefiting from intense rehabilitation therapies. Robotic training is a promising approach to complement conventional rehabilitation and neuromodulation of the cerebellum. Wearable dynamic orthoses represent a potential aid to assist gait. The panel of experts agree that the understanding of the cerebellar contribution to gait control will lead to a better management of cerebellar ataxias in general and will likely contribute to use gait parameters as robust biomarkers of future clinical trials.

Characterization of prosthetic knees through a low-dimensional description of gait kinematics.

The characterization of both limbs' behaviour in prosthetic gait is of key importance for improving the prosthetic components and increasing the biomechanical capability of trans-femoral amputees. When characterizing human gait, modular motor control theories have been proven to be powerful in providing a compact description of the gait patterns. In this paper, the planar covariation law of lower limb elevation angles is proposed as a compact, modular description of prosthetic gait; this model is exploited for a comparison between trans-femoral amputees walking with different prosthetic knees and control subjects walking at different speeds. Results show how the planar covariation law is maintained in prostheses users, with a similar spatial organization and few temporal differences. Most of the differences among the different prosthetic knees are found in the kinematic coordination patterns of the sound side. Moreover, different geometrical parameters have been calculated over the common projected plane, and their correlation with classical gait spatiotemporal and stability parameters has been investigated. The results from this latter analysis have highlighted a correlation with several parameters of gait, suggesting that this compact description of kinematics unravels a significant biomechanical meaning. These results can be exploited to guide the control mechanisms of prosthetic devices based purely on the measurement of relevant kinematic quantities.

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease.

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

The assistance of BAZAR robot promotes improved upper limb motor coordination in workers performing an actual use-case manual material handling.

This study aims at evaluating upper limb muscle coordination and activation in workers performing an actual use-case manual material handling (MMH). The study relies on the comparison of the workers' muscular activity while they perform the task, with and without the help of a dual-arm cobot (BAZAR). Eleven participants performed the task and the flexors and extensors muscles of the shoulder, elbow, wrist, and trunk joints were recorded using bipolar electromyography. The results showed that, when the particular MMH was carried out with BAZAR, both upper limb and trunk muscular co-activation and activation were decreased. Therefore, technologies that enable human-robot collaboration (HRC), which share a workspace with employees, relieve employees of external loads and enhance the effectiveness and calibre of task completion. Additionally, these technologies improve the worker's coordination, lessen the physical effort required to interact with the robot, and have a favourable impact on his or her physiological motor strategy. Practitioner summary: Upper limb and trunk muscle co-activation and activation is reduced when a specific manual material handling was performed with a cobot than without it. By improving coordination, reducing physical effort, and changing motor strategy, cobots could be proposed as an ergonomic intervention to lower workers' biomechanical risk in industry.

Trunk Muscle Coactivation in People with and without Low Back Pain during Fatiguing Frequency-Dependent Lifting Activities.

Lifting tasks are manual material-handling activities and are commonly associated with work-related low back disorders. Instrument-based assessment tools are used to quantitatively assess the biomechanical risk associated with lifting activities. This study aims at highlighting different motor strategies in people with and without low back pain (LBP) during fatiguing frequency-dependent lifting tasks by using parameters of muscle coactivation. A total of 15 healthy controls (HC) and eight people with LBP performed three lifting tasks with a progressively increasing lifting index (LI), each lasting 15 min. Bilaterally erector spinae longissimus (ESL) activity and rectus abdominis superior (RAS) were recorded using bipolar surface electromyography systems (sEMG), and the time-varying multi-muscle coactivation function (TMCf) was computed. The TMCf can significantly discriminate each pair of LI and it is higher in LBP than HC. Collectively, our findings suggest that it is possible to identify different motor strategies between people with and without LBP. The main finding shows that LBP, to counteract pain, coactivates the trunk muscles more than HC, thereby adopting a strategy that is stiffer and more fatiguing.

Machine Learning Approach to Support the Detection of Parkinson's Disease in IMU-Based Gait Analysis.

The aim of this study was to determine which supervised machine learning (ML) algorithm can most accurately classify people with Parkinson's disease (pwPD) from speed-matched healthy subjects (HS) based on a selected minimum set of IMU-derived gait features. Twenty-two gait features were extrapolated from the trunk acceleration patterns of 81 pwPD and 80 HS, including spatiotemporal, pelvic kinematics, and acceleration-derived gait stability indexes. After a three-level feature selection procedure, seven gait features were considered for implementing five ML algorithms: support vector machine (SVM), artificial neural network, decision trees (DT), random forest (RF), and K-nearest neighbors. Accuracy, precision, recall, and F1 score were calculated. SVM, DT, and RF showed the best classification performances, with prediction accuracy higher than 80% on the test set. The conceptual model of approaching ML that we proposed could reduce the risk of overrepresenting multicollinear gait features in the model, reducing the risk of overfitting in the test performances while fostering the explainability of the results.

Ability of a Set of Trunk Inertial Indexes of Gait to Identify Gait Instability and Recurrent Fallers in Parkinson's Disease.

The aims of this study were to assess the ability of 16 gait indices to identify gait instability and recurrent fallers in persons with Parkinson's disease (pwPD), regardless of age and gait speed, and to investigate their correlation with clinical and kinematic variables. The trunk acceleration patterns were acquired during the gait of 55 pwPD and 55 age-and-speed matched healthy subjects using an inertial measurement unit. We calculated the harmonic ratios (HR), percent recurrence, and percent determinism (RQAdet), coefficient of variation, normalized jerk score, and the largest Lyapunov exponent for each participant. A value of ≤1.50 for the HR in the antero-posterior direction discriminated between pwPD at Hoehn and Yahr (HY) stage 3 and healthy subjects with a 67% probability, between pwPD at HY 3 and pwPD at lower HY stages with a 73% probability, and it characterized recurrent fallers with a 77% probability. Additionally, HR in the antero-posterior direction was correlated with pelvic obliquity and rotation. RQAdet in the antero-posterior direction discriminated between pwPD and healthy subjects with 67% probability, regardless of the HY stage, and was correlated with stride duration and cadence. Therefore, HR and RQAdet in the antero-posterior direction can both be used as age- and-speed-independent markers of gait instability.

Impairment of Global Lower Limb Muscle Coactivation During Walking in Cerebellar Ataxias.

The aim of this study was to investigate the time-varying multi-muscle coactivation function (TMCf) in the lower limbs during gait and its relationship with the biomechanical and clinical features of patients with cerebellar ataxia. A total of 23 patients with degenerative cerebellar ataxia (16 with spinocerebellar ataxia, 7 with adult-onset ataxia of unknown etiology) and 23 age-, sex-, and speed-matched controls were investigated. The disease severity was assessed using the Scale for the Assessment and Rating of Ataxia (SARA) in all patients. During walking, simultaneous acquisition of kinematic, kinetic, and electromyography data was performed using a motion analysis system. The coactivation was processed throughout the gait cycle using the TMCf, and the following parameters were measured: synthetic coactivation index, full width at half maximum, and center of activity. Spatiotemporal (walking speed, stance duration, swing duration, first and second double-support durations, step length, step width, stride length, Center of Mass displacement), kinetic (vertical component of GRFs), and energy consumption (total energy consumption and mechanical energy recovered) parameters were also measured. The coactivation variables were compared between patients and controls and were correlated with both clinical and gait variables. A significantly increased global TMCf was found in patients compared with controls. In addition, the patients showed a significant shift of the center of activity toward the initial contact and a significant reduction in energy recovery. All coactivation parameters were negatively correlated with gait speed, whereas the coactivation index and center of activity were positively correlated with both center-of-mass mediolateral displacement values and SARA scores. Our findings suggest that patients use global coactivation as a compensatory mechanism during the earliest and most challenging subphase (loading response) of the gait cycle to reduce the lateral body sway, thus improving gait stability at the expense of effective energy recovery. This information could be helpful in optimizing rehabilitative treatment aimed at improving lower limb muscle control during gait in patients with cerebella ataxia.

Global Muscle Coactivation of the Sound Limb in Gait of People with Transfemoral and Transtibial Amputation.

The aim of this study was to analyze the effect of the level of amputation and various prosthetic devices on the muscle activation of the sound limb in people with unilateral transfemoral and transtibial amputation. We calculated the global coactivation of 12 muscles using the time-varying multimuscle coactivation function method in 37 subjects with unilateral transfemoral amputation (10, 16, and 11 with mechanical, electronic, and bionic prostheses, respectively), 11 subjects with transtibial amputation, and 22 healthy subjects representing the control group. The results highlighted that people with amputation had a global coactivation temporal profile similar to that of healthy subjects. However, amputation increased the level of the simultaneous activation of many muscles during the loading response and push-off phases of the gait cycle and decreased it in the midstance and swing subphases. This increased coactivation probably plays a role in prosthetic gait asymmetry and energy consumption. Furthermore, people with amputation and wearing electronic prosthesis showed lower global coactivation when compared with people wearing mechanical and bionic prostheses. These findings suggest that the global lower limb coactivation behavior can be a useful tool to analyze the motor control strategies adopted and the ability to adapt to the prosthetic device.

The Sensor-Based Biomechanical Risk Assessment at the Base of the Need for Revising of Standards for Human Ergonomics.

Due to the epochal changes introduced by "Industry 4.0", it is getting harder to apply the varying approaches for biomechanical risk assessment of manual handling tasks used to prevent work-related musculoskeletal disorders (WMDs) considered within the International Standards for ergonomics. In fact, the innovative human-robot collaboration (HRC) systems are widening the number of work motor tasks that cannot be assessed. On the other hand, new sensor-based tools for biomechanical risk assessment could be used for both quantitative "direct instrumental evaluations" and "rating of standard methods", allowing certain improvements over traditional methods. In this light, this Letter aims at detecting the need for revising the standards for human ergonomics and biomechanical risk assessment by analyzing the WMDs prevalence and incidence; additionally, the strengths and weaknesses of traditional methods listed within the International Standards for manual handling activities and the next challenges needed for their revision are considered. As a representative example, the discussion is referred to the lifting of heavy loads where the revision should include the use of sensor-based tools for biomechanical risk assessment during lifting performed with the use of exoskeletons, by more than one person (team lifting) and when the traditional methods cannot be applied. The wearability of sensing and feedback sensors in addition to human augmentation technologies allows for increasing workers' awareness about possible risks and enhance the effectiveness and safety during the execution of in many manual handling activities.

Modular motor control of the sound limb in gait of people with trans-femoral amputation.

BACKGROUND: The above-knee amputation of a lower limb is a severe impairment that affects significantly the ability to walk; considering this, a complex adaptation strategy at the neuromuscular level is needed in order to be able to move safely with a prosthetic knee. In literature, it has been demonstrated that muscle activity during walking can be described via the activation of a small set of muscle synergies. The analysis of the composition and the time activation profiles of such synergies have been found to be a valid tool for the description of the motor control schemes in pathological subjects. METHODS: In this study, we used muscle synergy analysis techniques to characterize the differences in the modular motor control schemes between a population of 14 people with trans-femoral amputation and 12 healthy subjects walking at two different (slow and normal self-selected) speeds. Muscle synergies were extracted from a 12 lower-limb muscles sEMG recording via non-negative matrix factorization. Equivalence of the synergy vectors was quantified by a cross-validation procedure, while differences in terms of time activation coefficients were evaluated through the analysis of the activity in the different gait sub-phases. RESULTS: Four synergies were able to reconstruct the muscle activity in all subjects. The spatial component of the synergy vectors did not change in all the analysed populations, while differences were present in the activity during the sound limb's stance phase. Main features of people with trans-femoral amputation's muscle synergy recruitment are a prolonged activation of the module composed of calf muscles and an additional activity of the hamstrings' module before and after the prosthetic heel strike. CONCLUSIONS: Synergy-based results highlight how, although the complexity and the spatial organization of motor control schemes are the same found in healthy subjects, substantial differences are present in the synergies' recruitment of people with trans femoral amputation. In particular, the most critical task during the gait cycle is the weight transfer from the sound limb to the prosthetic one. Future studies will integrate these results with the dynamics of movement, aiming to a complete neuro-mechanical characterization of people with trans-femoral amputation's walking strategies that can be used to improve the rehabilitation therapies.

Local Stability of the Trunk in Patients with Degenerative Cerebellar Ataxia During Walking.

This study aims to evaluate trunk local stability in a group of patients with degenerative primary cerebellar ataxia and to correlate it with spatio-temporal parameters, clinical variables, and history of falls. Sixteen patients affected by degenerative cerebellar ataxia and 16 gender- and age-matched healthy adults were studied by means of an inertial sensor to measure trunk kinematics and spatio-temporal parameters during over-ground walking. Trunk local dynamic stability was quantified by the maximum Lyapunov exponent with short data series of the acceleration data. According to this index, low values indicate more stable trunk dynamics, while high values denote less stable trunk dynamics. Disease severity was assessed by means of International Cooperative Ataxia Rating Scale (ICARS) according to which higher values correspond to more severe disease, while lower values correspond to less severe disease.Patients displayed a higher short-term maximum Lyapunov exponent than controls in all three spatial planes, which was correlated with the age, onset of the disease, and history of falls. Furthermore, the maximum Lyapunov exponent was negatively correlated with ICARS balance, ICARS posture, and ICARS total scores.These findings indicate that trunk local stability during gait is lower in patients with cerebellar degenerative ataxia than that in healthy controls and that this may increase the risk of falls. Local dynamic stability of the trunk seems to be an important aspect in patients with ataxia and could be a useful tool in the evaluation of rehabilitative and pharmacological treatment outcomes.

Progression of Gait Ataxia in Patients with Degenerative Cerebellar Disorders: a 4-Year Follow-Up Study.

In the present study, the progression of gait impairment in a group of patients with primary degenerative cerebellar ataxias was observed over a period of 4 years. A total of 30 patients underwent an initial gait analysis study, and thereafter only 12 were evaluated because they completed the 2- and 4-year follow-up evaluations. Time-distance parameters, trunk and joint range of motion (RoM), and variability parameters (e.g., coefficients of variation) were measured at the baseline and at each follow-up evaluation. The scale for the assessment and rating of ataxia (SARA) was used to evaluate disease severity. We found a significant increase in the SARA score at both the 2- and 4-year follow-up evaluations. Almost all the gait variables changed significantly only at the 4-year follow-up. Particularly, we found a significant decrease in the step length and in the hip, knee, and ankle joint RoM values and noted a significant increase in the trunk rotation RoM and stride-to-stride and step length variability. Furthermore, a significant difference in ankle joint RoM was found between spinocerebellar ataxia and sporadic adult-onset ataxia patients, with the value being lower in the former group of patients. Our findings suggest that patients with degenerative cerebellar ataxias exhibit gait decline after 4 years from the baseline. Moreover, patients try to maintain an effective gait by adopting different compensatory mechanisms during the course of the disease in spite of disease progression.

A new muscle co-activation index for biomechanical load evaluation in work activities.

Low-back disorders (LBDs) are the most common and costly musculoskeletal problem. Muscle co-activation, a mechanism that stabilises the spine, is adopted by the central nervous system to provide added protection and avoid LBDs. However, during high-risk lifting tasks, the compressive load on the spine grows owing to increased co-activation. The aim of this study was to develop a method for the sample-by-sample monitoring of the co-activation of more than two muscles, and to compare this method with agonist-antagonist methods. We propose a time-varying multi-muscle co-activation function that considers electromyographic (EMG) signals as input. EMG data of 10 healthy subjects were recorded while they manually lifted loads at three progressively heavier conditions. The repeated measures ANOVA revealed a significant effect of lifting condition on our co-activation index. Heavier conditions resulted in higher muscle co-activation values. Significant correlations were found between the time-varying multi-muscle co-activation index and other agonist-antagonist methods. Practitioner Summary: We have developed a method to quantify muscle co-activation during the execution of a lifting task. To do this we used surface electromyography. Our algorithm provides a measure of time-varying co-activation between more than two muscles.