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Objective. The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in clinical practice. To overcome this limitation, this study aims at presenting a toolbox to help scientists easily characterize and assess muscle activation patterns during cyclical movements. Approach. CIMAP(Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. Main results. From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment of muscle activation patterns. The toolbox can be flexibly modified to comply with the necessities of the scientist.CIMAPis addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub (https://github.com/Biolab-PoliTO/CIMAP). Significance. CIMAPtoolbox offers scientists a standardized method for analyzing muscle activation patterns during cyclical movements., (Creative Commons Attribution license.)

The muscle synergy theory was widely used in literature to assess the modular organization of the central nervous system (CNS) during human locomotion. The extraction of muscle synergies may be strongly influenced by the preprocessing techniques applied to surface electromyographic (sEMG) signals. The aim of this contribution is to assess the robustness improvement in muscle synergy extraction obtained using an innovative pre-processing technique with respect to the standard procedure. The new pre-processing technique that we propose is based on the extraction of principal muscle activation intervals (necessary to accomplish a specific biomechanical task during gait) from the original sEMG signals, discarding the secondary muscle activation intervals (activations that occur only in some strides with auxiliary functions). Results suggest that the extraction of the principal activation intervals from sEMG provide a more consistent and stable description of the modular organization of the CNS with respect to the standard pre-processing procedure.

Hemiplegia is a neurological disorder that is often detected in children with cerebral palsy. Although many studies have investigated muscular activity in hemiplegic legs, few EMG-based findings focused on unaffected limb. This study aimed to quantify the asymmetric behavior of lower-limb-muscle recruitment during walking in mild-hemiplegic children from surface-EMG and foot-floor contact features. sEMG signals from tibialis anterior (TA) and gastrocnemius lateralis and foot-floor contact data during walking were analyzed in 16 hemiplegic children classified as W1 according to Winter' scale, and in 100 control children. Statistical gait analysis, a methodology achieving a statistical characterization of gait by averaging surface-EMG-based features, was performed. Results, achieved in hundreds of strides for each child, indicated that in the hemiplegic side with respect to the non-hemiplegic side, W1 children showed a statistically significant: decreased number of strides with normal foot-floor contact; decreased stance-phase length and initial-contact sub-phase; curtailed, less frequent TA activity in terminal swing and a lack of TA activity at heel-strike. The acknowledged impairment of anti-phase eccentric control of dorsiflexors was confirmed in the hemiplegic side, but not in the contralateral side. However, a modified foot-floor contact pattern is evinced also in the contralateral side, probably to make up for balance requirements.

Muscle co-contractions are particularly relevant in analyzing children pathologies. To interpret surface electromyography (sEMG) in pathological conditions, reliable normative data in non-pathological children are required for direct comparison. Aim of the study was the quantification of co-contraction activity between quadriceps femoris (QF) and hamstring muscles during walking in healthy children. To this aim, Statistical gait analysis was performed on sEMG signals from rectus femoris (RF), vastus medialis (VM), and lateral hamstrings (LH), in 16401 strides walked by 100 healthy school-age children. Co-contractions were assessed as overlapping period between activation intervals of considered muscles. Results showed full superimpositions of LH with both RF and VL activity from terminal swing, 80-100% of gait cycle, to successive loading response (0-15% of gait cycle), in around 90% of strides, as reported in adults. This indicates that children regularly use a cocontraction activity between QF and hamstring muscles in weight acceptance during walking, supporting the hypothesis of a regulatory role of co-contraction in providing knee joint stability. Concomitant activity of QF and hamstring muscles was detected also during push-off phase (30-50% of gait cycle), showing a large variability intra and inter subjects and a lower occurrence frequency (around 25% of strides). This could be intended for controlling rapid knee flexion and/or stabilizing pelvis during body progression. Present findings represent the first attempt to provide normative sEMG dataset on variability of QF and hamstring muscles co-contractions during child walking, useful for discriminating physiological and pathological behavior and for designing future studies on maturation of gait., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Natural variability of myoelectric activity during walking was recently analyzed considering hundreds of strides. This allowed assessing a parameter seldom considered in classic surface EMG (sEMG) studies: the occurrence frequency, defined as the frequency each muscle activation occurs with, quantified by the number of strides when a muscle is recruited with that specific activation modality. Aim of present study was to propose the occurrence frequency as a new parameter for assessing sEMG-signal variability during walking. Aim was addressed by processing sEMG signals acquired from Gastrocnemius Lateralis, Tibialis Anterior, Rectus Femoris and Biceps femoris in 40 healthy subjects in order to: (1) show that occurrence frequency is not correlated with ON/OFF instants (R mean =0.11±0.07; P>0.05) and total time of activation (R mean =0.15±0.08; P>0.05); (2) confirm the above results by two handy examples of application (analysis of gender and age) which highlighted that significant (P<0.05) gender-related and age-related differences within population were detected in occurrence frequency, but not in temporal sEMG parameters. In conclusion, present study demonstrated that occurrence frequency is able to provide further information, besides those supplied by classical temporal sEMG parameters and thus it is suitable to complement them in the evaluation of variability of myoelectric activity during walking., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The research purpose was to quantify the co-contraction patterns of quadriceps femoris (QF) vs. hamstring muscles during free walking, in terms of onset-offset muscular activation, excitation intensity, and occurrence frequency. Statistical gait analysis was performed on surface-EMG signals from vastus lateralis (VL), rectus femoris (RF), and medial hamstrings (MH), in 16315 strides walked by 30 healthy young adults. Results showed full superimpositions of MH with both VL and RF activity from terminal swing, 80 to 100% of gait cycle (GC), to the successive loading response (≈0-15% of GC), in around 90% of the considered strides. A further superimposition was detected during the push-off phase both between VL and MH activation intervals (38.6±12.8% to 44.1±9.6% of GC) in 21.9±13.6% of strides, and between RF and MH activation intervals (45.9±5.3% to 50.7±9.7 of GC) in 32.7±15.1% of strides. These findings led to identify three different co-contractions among QF and hamstring muscles during able-bodied walking: in early stance (in ≈90% of strides), in push-off (in 25-30% of strides) and in terminal swing (in ≈90% of strides). The co-contraction in terminal swing is the one with the highest levels of muscle excitation intensity. To our knowledge, this analysis represents the first attempt for quantification of QF/hamstring muscles co-contraction in young healthy subjects during normal gait, able to include the physiological variability of the phenomenon., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Gait alterations are observed even years after hip replacement surgery. Such long-lasting alterations may arise from a global change of the motor control strategies. The aim of this work is to investigate the changes in gait motor control strategies of patients after hip replacement surgery by analyzing the frequency of occurrence (OF) of myoelectric activation patterns. We studied five lower limb muscles during gait, in hip prosthesis patients and controls. We found that patients adopt a motor control strategy that tends to prefer "simplified" myoelectric patterns, showing a smaller number of activations within the gait cycle. This altered motor control was present both on the prosthesis and the sound side, and did not improve during the 12-month follow-up. The reduced number of activations is even more evident in lateral hamstrings and gluteus medius, which are the muscles more affected by hip replacement surgery. Furthermore, this study demonstrated that the OF is a sensitive parameter able to discover subtle changes in motor control strategies. Its use can be extended to other studies involving motor coordination, motor learning and motor control adaptations.

Purpose: The study was designed to assess the co-contractions of tibialis anterior (TA) and gastrocnemius lateralis (GL) in healthy school-age children during gait at self-selected speed and cadence, in terms of variability of onset-offset muscular activation and occurrence frequency., Methods: Statistical gait analysis, a recent methodology performing a statistical characterization of gait by averaging spatio-temporal and sEMG-based parameters over numerous strides, was performed in 100 healthy children, aged 6-11 years. Co-contractions were assessed as the period of overlap between activation intervals of TA and GL., Results: On average, 165±27 strides were analyzed for each child, resulting in approximately 16,500 strides. Results showed that GL and TA act as pure agonist/antagonists for ankle plantar/dorsiflexion (no co-contractions) in only 19.2±10.4% of strides. In the remaining strides, statistically significant (p<0.05) co-contractions appear in early stance (46.5±23.0% of the strides), mid-stance (28.8±15.9%), pre-swing (15.2±9.2%), and swing (73.2±22.6%). This significantly increased complexity in muscle recruitment strategy beyond the activation as pure ankle plantar/dorsiflexors, suggests that in healthy children co-contractions are likely functional to further physiological tasks as balance improvement and control of joint stability., Conclusions: This study represents the first attempt for the development in healthy children of a normative dataset for GL/TA co-contractions during gait, achieved on an exceptionally large number of strides in every child and in total. The present reference frame could be useful for discriminating physiological and pathological behavior in children and for designing more focused studies on the maturation of gait., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In many applications requiring the study of the surface myoelectric signal (SMES) acquired in dynamic conditions, it is essential to have a quantitative evaluation of the quality of the collected signals. When the activation pattern of a muscle has to be obtained by means of single- or double-threshold statistical detectors, the background noise level e (noise) of the signal is a necessary input parameter. Moreover, the detection strategy of double-threshold detectors may be properly tuned when the SNR and the duty cycle (DC) of the signal are known. The aim of this paper is to present an algorithm for the estimation of e (noise), SNR, and DC of an SMES collected during cyclic movements. The algorithm is validated on synthetic signals with statistical properties similar to those of SMES, as well as on more than 100 real signals., (© 2011 IEEE)

Gait analysis is widely used in clinics to study walking abnormalities for surgery planning, definition of rehabilitation protocols, and objective evaluation of clinical outcomes. Surface electromyography allows the study of muscle activity non-invasively and the evaluation of the timing of muscle activation during movement. The aim of this study was to present a normative dataset of muscle activation patterns obtained from a large number of strides in a population of 100 healthy children aged 6-11 years. The activity of Tibialis Anterior, Lateral head of Gastrocnemius, Vastus Medialis, Rectus Femoris and Lateral Hamstrings on both lower limbs was analyzed during a 2.5-min walk at free speed. More than 120 consecutive strides were analyzed for each child, resulting in approximately 28,000 strides. Onset and offset instants were reported for each observed muscle. The analysis of a high number of strides for each participant allowed us to obtain the most recurrent patterns of activation during gait, demonstrating that a subject uses a specific muscle with different activation modalities even in the same walk. The knowledge of the various activation patterns and of their statistics will be of help in clinical gait analysis and will serve as reference in the design of future gait studies., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Gait asymmetry is typically evaluated using spatio-temporal or joint kinematics parameters. Only a few studies addressed the problem of defining an asymmetry index directly based on muscle activity, extracting parameters from surface electromyography (sEMG) signals. Moreover, no studies used the extraction of the muscle principal activations (activations that are necessary for accomplishing a specific motor task) as the base to construct an asymmetry index, less affected by the variability of sEMG patterns. The aim of this paper is to define a robust index to quantitatively assess the asymmetry of muscle activations during locomotion, based on the extraction of the principal activations. SEMG signals were analyzed combining statistical gait analysis (SGA) and a clustering algorithm that allows for obtaining the muscle principal activations. We evaluated the asymmetry levels of four lower limb muscles in: (1) healthy subjects of different ages (children, adults, and elderly); (2) different populations of orthopedic patients (adults with megaprosthesis of the knee after bone tumor resection, elderly subjects after total knee arthroplasty, and elderly subjects after total hip arthroplasty); and (3) neurological patients (children with hemiplegic cerebral palsy and elderly subjects affected by idiopathic normal pressure hydrocephalus). The asymmetry index obtained for each pathological population was then compared to that of age-matched controls. We found asymmetry levels consistent with the expected impact of the different pathologies on muscle activation during gait. This suggests that the proposed index can be successfully used in clinics for an objective assessment of the muscle activation asymmetry during locomotion. [ABSTRACT FROM AUTHOR]