Estimation of muscle activation during different walking speeds with two mathematical approaches compared to surface EMG

Abstract

Modelling approaches do not yet show sufficient consistency of agreement between estimated and recorded muscle activation to support recommending immediate clinical adoption of muscle force modelling. This may be because assumptions underlying muscle activation estimations (e.g. muscles' anatomy and maximum voluntary contraction) are not yet sufficiently individualizable. Future research needs to find timely and cost efficient ways to scale musculoskeletal models for better individualisation to facilitate future clinical implementation.

The effects of electromyography-assisted modelling in estimating musculotendon forces during gait in children with cerebral palsy

“…Another strategy often used to obtain muscle activations is computed muscle control (e.g. Hamner, Seth, & Delp, 2010;Liu, Anderson, Schwartz, & Delp, 2008;Steele, Seth, Hicks, Schwartz, & Delp, 2010;Trinler et al, 2018;Van der Krogt, Delp, & Schwartz, 2012), which is also a tool in OpenSim (Thelen et al, 2003;Thelen and Anderson, 2006). This procedure might improve model performance compared to static optimization, since it adds feedback and feedforward control, implementing time-dependency of the solution.…”

“…This procedure might improve model performance compared to static optimization, since it adds feedback and feedforward control, implementing time-dependency of the solution. However, studies using computed muscle control also showed clear discrepancies between computed activations and EMG solutions in healthy individuals (Hamner et al, 2010;Liu et al, 2008;Steele et al, 2010;Trinler et al, 2018;Van der Krogt et al, 2012). Hence, the weight of available evidence suggests that the commonly used optimization approaches which do not implement recorded excitations might not be appropriate in estimating musculotendon forces in healthy individuals, let alone individuals with neuromuscular impairments.…”

“…The assumption that all individuals employ similar neuromuscular strategies to perform a movement is in disagreement with experimental findings that show that for the same joint angles and joint moments EMG patterns vary between individuals (Lloyd and Buchanan, 2001), and in the same people EMG patterns (Buchanan and Lloyd, 1995;Milner and Cloutier, 1998) and motor unit recruitment (Tax et al, 1990) vary when the same movement is involved in a different task. A recent study by Trinler et al, (2018) indicated that activations estimated by static optimization did not agree well with measured EMG at different walking speeds in healthy individuals. Moreover, due to the aberrant motor control in children with CP, the use of a static optimization approach solely minimizing activation squared to solve the redundancy problem is likely to be even more problematic in this clinical population.…”

Musculoskeletal modelling and simulation of oil palm fresh fruit bunch harvesting

“…The biceps demonstrated a high correlation in R MA and a poor correlation in MAE MA when F RA was 30 N. Three possible reasons may explain the poor correlation of biceps. Firstly, higher speed can result in higher deviations than lower speed 47 . The harvesters must exert alarge force at a very high speed to harvest the fruit 48 .…”

Healthy Lifestyle, Autonomic Nervous System Activity, and Sleep Status for Healthy Aging

“…The higher activation for the tibialis anterior, while walking slower might be caused by a deviation from the natural walking pattern of the participant [28]. On the contrary, it has been suggested that walking with a four-wheeled walker (rollator) consistently reduced EMG muscle activity in all lower extremity muscle groups and that increased weight-bearing lead to an increased reduction in muscle activity.…”