JournalArticle

YC Pan, B Goodwin, E Sabelhaus, KM Peters, KF Bjornson, KLD Pham, WO Walker, KM Steele (2020) “Feasibility of using acceleration-derived jerk to quantify bimanual arm use” Journal of NeuroEngineering and Rehabilitation

Dr. Steele JournalArticle, UbiquitousRehabilitation , , , , ,

Journal Article in Journal of NeuroEngineering & Rehabilitation

Two plots illustrating jerk ratio results. The plot on the left shows the probability distribution from one child with cerebral palsy before, during, and after constraint induced movement therapy. Before therapy, the probability distribution is shifted to the left of the center line, indicating that the individual relies much more on their non-paretic hand during daily life. During therapy, when their non-paretic hand is in a cast, the curve shifts to the right of the center line. This indicates they are using their paretic hand much more - which makes sense, since the other hand is in a cast. Unfortunately, after the cast is removed at the end of therapy, the curve is nearly identical to the curve before treatment, suggesting that after this intensive therapy the child did not use their paretic hand more during daily life. The figure on the right shows the summary metric from this plot, called jerk ratio 50 - which is just the 50% value of the probability density function - for all 5 children with cerebral palsy before, during, and after therapy. All the children have JR50 greater than 0.5 before therapy, which means they use their non-paretic hand more during daily life. During therapy, these values drop to 0.2 - 0.5, indicating that they use their paretic hand much more during CIMT. However, after therapy the JR50 values for all five participants return to close to their baseline value before therapy.
(Left) Example of jerk ratio distribution for one child with cerebral palsy before, during, and after constraint induced movement therapy. (Right) Summary metric of jerk ratio (jerk ratio-50) for all five children with cerebral palsy.

Background

Accelerometers have become common for evaluating the efficacy of rehabilitation for patients with neurologic disorders. For example, metrics like use ratio (UR) and magnitude ratio (MR) have been shown to differentiate movement patterns of children with cerebral palsy (CP) compared to typically-developing (TD) peers. However, these metrics are calculated from “activity counts” – a measure based on proprietary algorithms that approximate movement duration and intensity from raw accelerometer data. Algorithms used to calculate activity counts vary between devices, limiting comparisons of clinical and research results. The goal of this research was to develop complementary metrics based on raw accelerometer data to analyze arm movement after neurologic injury.

Method

We calculated jerk, the derivative of acceleration, to evaluate arm movement from accelerometer data. To complement current measures, we calculated jerk ratio (JR) as the relative jerk magnitude of the dominant (non-paretic) and non-dominant (paretic) arms.  We evaluated the JR distribution between arms and calculated the 50th percentile of the JR distribution (JR50). To evaluate these metrics, we analyzed bimanual accelerometry data for five children with hemiplegic CP who underwent Constraint-Induced Movement Therapy (CIMT) and five typically developing (TD) children. We compared JR between the CP and TD cohorts, and to activity count metrics.

Results

The JR50 differentiated between the CP and TD cohorts (CP = 0.578±0.041 before CIMT, TD = 0.506±0.026), demonstrating increased reliance on the non-dominant arm for the CP cohort. Jerk metrics also quantified changes in arm use during and after therapy (e.g., JR50 = 0.378±0.125 during CIMT, 0.591 ± 0.057 after CIMT). The JR was strongly correlated with UR and MR (r = -0.92, 0.89) for the CP cohort. For the TD cohort, JR50 was repeatable across three data collection periods with an average similarity of 0.945±0.015.

Conclusions

Acceleration-derived jerk captured differences in motion between TD and CP cohorts and correlated with activity count metrics. The code for calculating and plotting JR is open-source and available for others to use and build upon. By identifying device-independent metrics that can quantify arm movement in daily life, we hope to facilitate collaboration for rehabilitation research using wearable technologies.

Code

The algorithm for calculating jerk ratio, as well as user-friendly code to produce plots similar to the figure above are provided open-source as Python 3.6 code as a Python Jupyter Notebook within Google Colab. With this resource, research groups can use existing or newly created data from accelerometers to analyze jerk ratio as a complementary metric to existing measures, enabling comparison between research studies or centers that may rely on different sensors and activity count algorithms.

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

Elijah JournalArticle, News, Publications, UbiquitousRehabilitation , , ,

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.

Background

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.

Purpose

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

Method

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.

Results

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.

Conclusions

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.

N Mehrabi, MH Schwartz, KM Steele (2019) “Can altered muscle synergies control unimpaired gait?” Journal of Biomechanics

Nicole JournalArticle, MotorControl, Publications , , , , ,

Journal Article in Journal of Biomechanics:

Musculoskeletal models of gait with lower dimensional control spaces showed that an individual with reduced number of synergies could not produce an unimpaired gait

Background: Recent studies have postulated that the human motor control system recruits groups of muscles through low-dimensional motor commands, or muscle synergies. This scheme simplifies the neural control problem associated with the high-dimensional structure of the neuromuscular system. Several lines of evidence have suggested that neurological injuries, such as stroke or cerebral palsy, may reduce the dimensions that are available to the motor control system, and these altered dimensions or synergies are thought to contribute to impaired walking patterns. However, no study has investigated whether impaired low-dimensional control spaces necessarily lead to impaired walking patterns.

Methods: In this study, using a two-dimensional model of walking, we developed a synergy-based control framework that can simulate the dynamics of walking.

Results: The simulation analysis showed that a synergy-based control scheme can produce well-coordinated movements of walking matching unimpaired gait. However, when the dimensions available to the controller were reduced, the simplified emergent pattern deviated from unimpaired gait. A system with two synergies, similar to those seen after neurological injury, could not produce an unimpaired walking pattern.

Conclusions: These findings provide further evidence that altered muscle synergies can contribute to impaired gait patterns and may need to be directly addressed to improve gait after neurological injury.

HA Feldner, D Howell, VE Kelly, S Westcott McCoy, KM Steele (2019) “‘Look, Your Muscles Are Firing!’: A Qualitative Study of Clinician Perspectives on the Use of Surface Electromyography in Neurorehabilitation.” Archives of Physical Medicine and Rehabilitation

Nicole JournalArticle, Projects, Publications, UbiquitousRehabilitation

Journal Article in Archives of Physical Medicine and Rehabilitation:

We collaborated with rehabilitation clinicians across the Seattle region to understand the barriers and facilitators of using wireless electromyography sensors to track motor recovery in the clinic and community

Objective: To examine the perceived value, benefits, drawbacks, and ideas for technology development and implementation of surface electromyography recordings in neurologic rehabilitation practice from clinical stakeholder perspectives.

Design: A qualitative, phenomenological study was conducted. In-depth, semistructured interviews and focus groups were completed. Sessions included questions about clinician perspectives and demonstrations of surface electromyography systems to garner perceptions of specific system features.

Setting: The study was conducted at hospital systems in a large metropolitan area.

Participants: Adult and pediatric physical therapists, occupational therapists, and physiatrists from inpatient, outpatient, and research settings (N=22) took part in the study.

Interventions: Not applicable.

Main Outcome Measures: Interviews and focus groups were audio-recorded, transcribed verbatim, then coded for analysis into themes.

Results: Four major themes emerged: (1) low-tech clinical practice and future directions for rehabilitation; (2) barriers to surface electromyography uptake and potential solutions; (3) benefits of surface electromyography for targeted populations; and (4) essential features of surface electromyography systems.

Conclusions: Surface electromyography systems were not routinely utilized for assessment or intervention following neurologic injury. Despite recognition of potential clinical benefits of surface electromyography use, clinicians identified limited time and resources as key barriers to implementation. Perspectives on design and surface electromyography system features indicated the need for streamlined, intuitive, and clinically effective applications. Further research is needed to determine feasibility and clinical relevance of surface electromyography in rehabilitation intervention.

BR Shuman, M Goudriaan, K Desloovere, MH Schwartz, KM Steele (2019) “Muscle synergies demonstrate only minimal changes after treatment in cerebral palsy.” Journal of NeuroEngineering and Rehabilitation

Nicole JournalArticle, MotorControl, Projects, Publications , , , , , , ,

Journal Article in Journal of NeuroEngineering and Rehabilitation:

In collaboration with University Hospital Pellenberg we examined whether muscle synergies change following common treatments in CP.

Background: Children with cerebral palsy (CP) have altered synergies compared to typically-developing peers, reflecting different neuromuscular control strategies used to move. While these children receive a variety of treatments to improve gait, whether synergies change after treatment, or are associated with treatment outcomes, remains unknown.

Methods: We evaluated synergies for 147 children with CP before and after three common treatments: botulinum toxin type-A injection (n = 52), selective dorsal rhizotomy (n = 38), and multi-level orthopaedic surgery (n = 57). Changes in synergy complexity were measured by the number of synergies required to explain > 90% of the total variance in electromyography data and total variance accounted for by one synergy. Synergy weights and activations before and after treatment were compared using the cosine similarity relative to average synergies of 31 typically-developing (TD) peers.

Results: There were minimal changes in synergies after treatment despite changes in walking patterns. Number of synergies did not change significantly for any treatment group. Total variance accounted for by one synergy increased (i.e., moved further from TD peers) after botulinum toxin type-A injection (1.3%) and selective dorsal rhizotomy (1.9%), but the change was small. Synergy weights did not change for any treatment group (average 0.001 ± 0.10), but synergy activations after selective dorsal rhizotomy did change and were less similar to TD peers (− 0.03 ± 0.07). Only changes in synergy activations were associated with changes in gait kinematics or walking speed after treatment. Children with synergy activations more similar to TD peers after treatment had greater improvements in gait.

Conclusions: While many of these children received significant surgical procedures and prolonged rehabilitation, the minimal changes in synergies after treatment highlight the challenges in altering neuromuscular control in CP. Development of treatment strategies that directly target impaired control or are optimized to an individual’s unique control may be required to improve walking function.