Atlas of Muscle Innervation Zones

Barbero, Marco; Merletti, Roberto; Rainoldi, Alberto

doi:10.1007/978-88-470-2463-2

Cited by 267 publications

(171 citation statements)

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“…rsfs.royalsocietypublishing.org Interface Focus 5: 20140076 towards each end of the muscle. Despite the simplified example set-up, the predicted EMG compares qualitatively well with the experimental sEMG data of Farina et al [1] and Barbero et al [39]. A quantitative comparison is difficult as experimental EMG signals depend heavily on properties that are difficult to control in experiments, for example the MU territories and the thickness of the subcutaneous tissue [40].…”

Section: Surface and Intramuscular Electromyography During Fixed-lengmentioning

confidence: 71%

Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

2015

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One contribution of 11 to a theme issue 'Multiscale modelling in biomechanics: theoretical, computational and translational challenges'. This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation-contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the a motor neurons.

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Section: Surface and Intramuscular Electromyography During Fixed-lengmentioning

confidence: 71%

Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

2015

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“…Lifting technique was based on the discretion of the individual and the subject's box weight was determined by their maximum psychophysically acceptable weight (Table 1). Electromyography (EMG) (Delsys Inc. 2000Hz) sensors were then placed on the right side internal oblique (IO), external oblique (EO), erector spinae (ES), and multifidus (Mf) at the fifth lumbar (L5) spinal level, as well as the rectus femoris(RF), vastus medialis (VM), semitendinosus (ST), gluteus maximus (GMx) and gluteus medius (GMd) all on the subjects right side (Barbero, Merletti, Rainoldi, 2012). Ground reaction forces (GRFs) were collected for each leg (AMTI 2000Hz).…”

Section: Methodsmentioning

confidence: 99%

Effects of Gender and Recurrent Low Back Pain on Lifting Style

Haddas

Yang

Sizer

2015

Central European Journal of Sport Sciences and Medicine

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Abstract. Objective: The purpose of this study was to examine the influence of gender and existing, recurrent low back pain (rLBP) on lower extremity and trunk mechanics, as well as neuromuscular control, during a lift task. Design: A multivariate design was used to examine the effects of gender and group on biomechanical and neuromuscular control variables in randomized symmetric and asymmetric lifting. Methods: 68 Males and females with rLBP and healthy performed symmetric and asymmetric weighted box lifting trials to a 1 meter height table. Results: Lifting style was different between gender and between the rLBP versus healthy groups during a 1m box lifting. A significant two-way interaction effect between gender and group was observed for multifidus muscle activity and knee rotation in asymmetric lifting. Several gender and group main effects were observed in pelvis obliquity, trunk flexion and side flexion, knee abduction angles in symmetric lifting; and in pelvis obliquity and rotation, trunk flexion and side flexion, hip abduction, knee abduction angles, external oblique and internal oblique muscles activity in asymmetric lifting. Conclusions: Females and individuals with rLBP appear to use different lifting styles that emphasize movement at the pelvis accompanied by poor kinematic control features at the hip, trunk and knee. Clinicians should be mindful of these changes when developing prevention and rehabilitation programs aimed at improving trunk control in preparation for lifting tasks during domestic and occupational activities.

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“…The likely location of the IZ for the TA was estimated to be 34% between the tibila tuberosity and intermalleolar line from the tibila tuberosity [41]. The skin was cleaned and exfoliated before placing the electrode array over the TA and the reference electrodes were placed on the ankle.…”

Section: Electrode Placementmentioning

confidence: 99%

Normalised Mutual Information of High-Density Surface Electromyography during Muscle Fatigue

Bingham

Arjunan

Jelfs

et al. 2017

Entropy

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Abstract:This study has developed a technique for identifying the presence of muscle fatigue based on the spatial changes of the normalised mutual information (NMI) between multiple high density surface electromyography (HD-sEMG) channels. Muscle fatigue in the tibialis anterior (TA) during isometric contractions at 40% and 80% maximum voluntary contraction levels was investigated in ten healthy participants (Age range: 21 to 35 years; Mean age = 26 years; Male = 4, Female = 6). HD-sEMG was used to record 64 channels of sEMG using a 16 by 4 electrode array placed over the TA. The NMI of each electrode with every other electrode was calculated to form an NMI distribution for each electrode. The total NMI for each electrode (the summation of the electrode's NMI distribution) highlighted regions of high dependence in the electrode array and was observed to increase as the muscle fatigued. To summarise this increase, a function, M(k), was defined and was found to be significantly affected by fatigue and not by contraction force. The technique discussed in this study has overcome issues regarding electrode placement and was used to investigate how the dependences between sEMG signals within the same muscle change spatially during fatigue.

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Atlas of Muscle Innervation Zones

Cited by 267 publications

References 0 publications

Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

Effects of Gender and Recurrent Low Back Pain on Lifting Style

Normalised Mutual Information of High-Density Surface Electromyography during Muscle Fatigue

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