Increasing level of neuromusculoskeletal model personalisation to investigate joint contact forces in cerebral palsy: A twin case study

Davico, Giorgio; Pizzolato, Claudio; Lloyd, David G.; Obst, Steven; Walsh, Henry P.J.; Carty, Christopher P.

doi:10.1016/j.clinbiomech.2019.12.011

Cited by 37 publications

(27 citation statements)

References 51 publications

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“…EMG signals were band-pass filtered at 30–400 Hz (zero lag 4th order Butterworth), full wave rectified, and low-pass filtered at 6 Hz (zero lag 4th order Butterworth). The muscle-specific EMG linear envelopes were normalised to the maximum values identified across the processed trials to ensure that they remained within a range of 0–1 28 , 30 . Next, each of the linear envelopes was interpolated via cubic splines, and reduced to 100 data points 28 , 30 , which represented a muscle activation pattern.…”

Section: Methodsmentioning

confidence: 99%

A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children

Rabbi

Diamond

Carty

et al. 2022

Sci Rep

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Preparing children with cerebral palsy prior to gait analysis may be a challenging and time-intensive task, especially when large number of sensors are involved. Collecting minimum number of electromyograms (EMG) and yet providing adequate information for clinical assessment might improve clinical workflow. The main goal of this study was to develop a method to estimate activation patterns of lower limb muscles from EMG measured from a small set of muscles in children with cerebral palsy. We developed and implemented a muscle synergy extrapolation method able to estimate the full set of lower limbs muscle activation patterns from only three experimentally measured EMG. Specifically, we extracted a set of hybrid muscle synergies from muscle activation patterns of children with cerebral palsy and their healthy counterparts. Next, those muscle synergies were used to estimate activation patterns of muscles, which were not initially measured in children with cerebral palsy. Two best combinations with three (medial gastrocnemius, semi membranous, and vastus lateralis) and four (lateral gastrocnemius, semi membranous, sartorius, and vastus medialis) experimental EMG were able to estimate the full set of 10 muscle activation patterns with mean (± standard deviation) variance accounted for of 79.93 (± 9.64)% and 79.15 (± 6.40)%, respectively, using only three muscle synergies. In conclusion, muscle activation patterns of unmeasured muscles in children with cerebral palsy can be estimated from EMG measured from three to four muscles using our muscle synergy extrapolation method. In the future, the proposed muscle synergy-based method could be employed in gait clinics to minimise the required preparation time.

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Section: Methodsmentioning

confidence: 99%

A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children

Rabbi

Diamond

Carty

et al. 2022

Sci Rep

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“…(Figure 3), as in Davico et al (2020). In Figure 3 were also reported the joint kinematics of the sagittal plane obtained in OpenSim through the solution of an IK problem.…”

Section: Wtnr Model Reliability In Pdmentioning

confidence: 99%

Electromyography-informed modeling for estimating muscle activation and force alterations in Parkinson’s disease

Romanato

Volpe²,

Guiotto

et al. 2021

Computer Methods in Biomechanics and Biomedical Engineering

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Electromyography (EMG)-driven neuromusculoskeletal modeling (NMSM) enables simulating the mechanical function of multiple muscle-tendon units as controlled by nervous system in the generation of complex movements. In the context of clinical assessment this may enable understanding biomechanical factor contributing to gait disorders such as one induced by Parkinson's disease (PD). In spite of the challenges in the development of patient-specific models, this preliminary study aimed at establishing a feasible and noninvasive experimental and modeling pipeline to be adopted in clinics to detect PD-induced gait alterations. Four different NMSM have been implemented for three healthy controls using CEINMS, an OpenSim-compatible toolbox. Models differed in the EMG-normalization methods used for calibration purposes (i.e. walking trial normalization and maximum voluntary contraction normalization) and in the set of experimental EMGs used for the musculotendon-unit mapping (i.e. 4 channels vs. 15 channels). Model accuracy assessment showed no statistically significant differences between the more complete model (non-clinically viable) and the proposed reduced one (clinically viable). The clinically viable reduced model was systematically applied on a dataset including ten PD's and thirteen healthy controls. Results showed significant differences in the neuromuscular control strategy of the PD group in term of muscle forces and joint torques. Indeed, PD patients displayed a significantly lower magnitude on force production and revealed a higher amount of force variability with the respect of the healthy controls. The estimated variables could become a measurable biomechanical outcome to assess and track both disease progression and its impact on gait in PD subjects.

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“…Motion capture (e.g., stereophotogrammetry marker-based systems or inertial measurement units) and external force data (e.g., ground reaction forces) are used to determine joint angles and moments using inverse kinematics and inverse dynamics approaches, respectively. Mechanical methods based on metabolic expenditure optimization criterion, such as static or dynamic optimization, can be used to solve the muscle redundancy problem; however, these approaches do not account for the individual’s motor control and have repeatedly shown to be unable to appropriately predict muscle co-contractions that are evident in measured EMG data ( Hoang et al, 2018 ; Davico et al, 2019b ; Veerkamp et al, 2019 ). Alternatively, EMG data can be directly used to inform forward dynamic simulations of muscles contraction and calculate muscle forces ( Lloyd and Besier, 2003 ; Pizzolato et al, 2015 , 2017c ).…”

Section: Framework For Real-time Estimation Of Localized Achilles Tenmentioning

confidence: 99%

“…Alternatively, EMG data can be directly used to inform forward dynamic simulations of muscles contraction and calculate muscle forces ( Lloyd and Besier, 2003 ; Pizzolato et al, 2015 , 2017c ). When personalized to the individual (e.g., via system identification methods or direct measurement) EMG-informed NMS models can predict physiologically plausible muscle forces across different motor tasks and different populations varying by age and pathology ( Gerus et al, 2013 ; Hoang et al, 2018 ; Davico et al, 2019b ; Veerkamp et al, 2019 ).…”

Section: Framework For Real-time Estimation Of Localized Achilles Tenmentioning

confidence: 99%

Targeted Achilles Tendon Training and Rehabilitation Using Personalized and Real-Time Multiscale Models of the Neuromusculoskeletal System

Pizzolato

Shim

Lloyd

et al. 2020

Front. Bioeng. Biotechnol.

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Increasing level of neuromusculoskeletal model personalisation to investigate joint contact forces in cerebral palsy: A twin case study

Cited by 37 publications

References 51 publications

A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children

A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children

Electromyography-informed modeling for estimating muscle activation and force alterations in Parkinson’s disease

Targeted Achilles Tendon Training and Rehabilitation Using Personalized and Real-Time Multiscale Models of the Neuromusculoskeletal System

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