BR Shuman, M Goudriaan, K Desloovere, MH Schwartz, KM Steele (2019) “Muscle Synergy Constraints Do Not Improve Estimates of Muscle Activity From Static Optimization During Gait for Unimpaired Children or Children With Cerebral Palsy” Frontiers in Neurorobotics

Journal Article in Frontiers of Neurorobotics:

This study demonstrated that muscle activations estimated from static optimization using generic musculoskeletal modeling does not accurately predict EMG profiles for children with CP or TD peers. Constraining activation patterns to experimentally measured synergies increased estimated muscle stresses, but did not improve the estimation of muscle activations for either group.

figure depicting flow chart with modeling optimization and muscle activity
Constraining simulated activations in inverse dynamic simulations to subject-specific synergies alone does not improve estimation of muscle activations during gait for generic musculoskeletal models.


Neuromusculoskeletal simulation provides a promising platform to inform the design of assistive devices or inform rehabilitation. For these applications, a simulation must be able to accurately represent the person of interest, such as an individual with a neurologic injury. If a simulation fails to predict how an individual recruits and coordinates their muscles during movement, it will have limited utility for informing design or rehabilitation. While inverse dynamic simulations have previously been used to evaluate anticipated responses from interventions, like orthopaedic surgery or orthoses, they frequently struggle to accurately estimate muscle activations, even for tasks like walking. The simulated muscle activity often fails to represent experimentally measured muscle activity from electromyographic (EMG) recordings. Research has theorized that the nervous system may simplify the range of possible activations used during dynamic tasks, by constraining activations to weighted groups of muscles, referred to as muscle synergies. Synergies are altered after neurological injury, such as stroke or cerebral palsy (CP), and may provide a method for improving subject-specific models of neuromuscular control.


The aim of this study was to test whether constraining simulation to synergies could improve estimated muscle activations compared to EMG data.


We evaluated modeled muscle activations during gait for six typically developing children (TD) and six children with CP. Muscle activations were estimated with: 1) static optimization (SO), minimizing muscle activations squared, and 2) synergy static optimization (SynSO), minimizing synergy activations squared using the weights identified from EMG data for 2-5 synergies.


While SynSO caused changes in estimated activations compared to SO, the correlation to EMG data was not higher in SynSO than SO for either TD or CP groups . The correlations to EMG were higher in CP than TD for both SO (CP: 0.48, TD: 0.36) and SynSO (CP: 0.46, TD: 0.26 for 5 synergies). Constraining activations to SynSO caused the simulated muscle stress to increase compared to SO for all individuals, causing a 157% increase with two synergies.


These results suggest that constraining simulated activations in inverse dynamic simulations to subject-specific synergies alone does not improve estimation of muscle activations during gait for generic musculoskeletal models.

Congratulations – Damon Ding is awarded UWIN’s Innovation Undergraduate Fellowship in Neuroengineering.

Portrait photo of young man wearing black glasses, navy sweater and white button-up undershirt in front of a tan wallOur undergraduate student, Damon Qilang Ding, has been awarded the Innovation Undergraduate Fellowship  the UW’s Institute for Neuroengineering. The UWIN Fellowship provides funding for Damon to conduct research in his upcoming quarters and is a highly prestigious and selective competition. Congratulations, Damon!

Damon’s research is to lead a fabrication, assembly, and tuning of a dynamic walking bipedal robot, which will serve as a testbed for validating the Ability & Innovation lab’s simulation framework evaluating whether discrepancy modeling with data-driven approaches enables more accurate dynamic solutions of bipedal movement with both unaltered and altered control.

Makoto Eyre receives internship from Blue Origin

We are proud to announce that Makoto Eyre has been offered an an internship at Blue Origin! He will be working at Blue Origin  as a space architecture intern during the Winter 2020 academic quarter. See the link below for a spotlight on Makoto from earlier this year.

Makoto the Space Architect

Please join us in congratulating Makoto and wishing him good luck!

Nicole Zaino wins the ESMAC Best Paper award

Congratulations to Nicole Zaino for being awarded the ESMAC (European Society of Movement Analysis for Adults and Children) Best Paper Award. Nicole received this award at the 2019 ESMAC conference in Amsterdam, September 23-28, 2019 where she gave her talk: “Spasticity reduction in children with cerebral palsy is not associated with reduced energy during walking.” For more information, visit ESMAC.

Woman in formal attire standing behind a black and purple podium in front of a large presentation screen