EMG

KM Steele, MH Schwartz (2022) “Causal Effects of Motor Control on Gait Kinematics After Orthopedic Surgery in Cerebral Palsy: A Machine-Learning Approach”

Katie Landwehr JournalArticle, MotorControl, News, Publications , , , , , ,

Journal Article in Frontiers in Human Neuroscience

Altered motor control is common in cerebral palsy (CP). Understanding how altered motor control affects movement and treatment outcomes is important but challenging due to complex interactions with other neuromuscular impairments. While regression can be used to examine associations between impairments and movement, causal modeling provides a mathematical framework to specify assumed causal relationships, identify covariates that may introduce bias, and test model plausibility.

FIGURE 1 Directed Acyclic Graph (DAG) describing the assumed causal relationships between SEMLS (exposure) and 1GDI (outcome). The causal relationship between SEMLS and 1GDI is mediated by changes in impairments (1Imp). Baseline GDI (GDIpre) and 1GDI are related by measurement methods and other, unmeasured factors. Baseline impairment (Imppre), surgical history (Hx), and Age are also included as causal factors. The DAG also includes unmeasured factors related to general CP severity, which impact baseline impairment and surgical history. The step-by-step process and rationale for this DAG are available in the Supplementary Material and an interactive version is available on dagitty (http://dagitty.net/mUCSPWo).Aim: The goal of this research was to quantify the causal effects of altered motor control and other impairments on gait, before and after single-event multi-level orthopedic surgery (SEMLS).

Methods: We evaluated the impact of SEMLS on change in Gait Deviation Index (ΔGDI) between gait analyses. We constructed our causal model with a Directed Acyclic Graph that included the assumed causal relationships between SEMLS, ΔGDI, baseline GDI (GDIpre), baseline neurologic and orthopedic impairments (Imppre), age, and surgical history. We identified the adjustment set to evaluate the causal effect of SEMLS on ΔGDI and the impact of Imppre on ΔGDI and GDIpre. We used Bayesian Additive Regression Trees (BART) and accumulated local effects to assess relative effects.

Results: We prospectively recruited a cohort of children with bilateral CP undergoing SEMLS (N = 55, 35 males, age: 10.5 ± 3.1 years) and identified a control cohort with bilateral CP who did not undergo SEMLS (N = 55, 30 males, age: 10.0 ± 3.4 years). There was a small positive causal effect of SEMLS on ΔGDI (1.70 GDI points). Altered motor control (i.e., dynamic and static motor control) and strength had strong effects on GDIpre, but minimal effects on ΔGDI. Spasticity and orthopedic impairments had minimal effects on GDIpre or ΔGDI.

Interpretation: Altered motor control did have a strong effect on GDIpre, indicating that these impairments do have a causal effect on a child’s gait pattern, but minimal effect on expected changes in GDI after SEMLS. Heterogeneity in outcomes suggests there are other factors contributing to changes in gait. Identifying these factors and employing causal methods to examine the complex relationships between impairments and movement will be required to advance our understanding and care of children with CP.

Steele Lab members present their research to Seattle Young Adult Stroke Survivors (YASS)

Nicole News, UbiquitousRehabilitation ,

Steele Lab members – Kat, Christina, Nick, and Momona – were invited to present their research about wearable sensors for stroke recovery and device control to the Seattle Young Adult Stroke Survivors (YASS). YASS is a support group for individuals who have experienced a stroke and creates a community to learn, listen, share, and more. Steele lab was one of the first research groups to come and share our work with them. 

Young Adult Stroke Survivors logo. Light green writing on a dark green background with a silhouette of a person climbing up boulders.

Our presentation began with background information regarding neurophysiological changes after stroke to provide insight into upper extremity functional impairments – including weakness, loss of dexterity, and abnormal tone. Wearable sensors, such as electromyography (EMG), can provide information regarding muscle function. Many of the listeners were surprised to hear that their own smartphones or watches can act as wearable sensors!

A focus of our research is detecting muscle activity early after stroke using EMG. One member recalled thinking their muscle was firing during their acute recovery but could not see any physical movement.  EMG allows us to capture that type of activity and any functional changes throughout recovery, empowering patients and clinicians to track their recovery and adjust their therapy regimen. The crowd was interested in using EMG to evaluate their own muscles, identify which were firing, and guide their rehabilitation. 

EMG not only helps us track recovery, but can be paired with consumer technology. Nick demonstrated how using muscle activity from the affected limb can incorporate rehabilitation into daily computer use. EMG signals can simulate pressing keys on a keyboard or moving a mouse cursor, making it easier for people with limited mobility to use technology. YASS members expressed enthusiasm about the increasing commercial availability of such devices so they can buy them and give them a try.

It was a great opportunity to connect with stroke survivors and hear their thoughts on wearable sensors. Thank you to YASS for having us come in and share our research!

 

M Yamagami, KM Peters, I Milovanovic, I Kuang, Z Yang, N Lu, KM Steele (2018) “Assessment of Dry Epidermal Electrodes for Long-Term Electromyography Measurements.” Sensors

Keshia JournalArticle, Projects, Publications, UbiquitousRehabilitation
Sample sEMG signal from one subject’s FCU for (left) MVIC; (middle) dynamic and (right) functional tests indicate that there were no significant differences between the Delsys (lighter grey) and ESS electrodes (darker grey) based on raw sEMG amplitude, linear envelope amplitude, or power spectral density.

Journal article in Sensors:

In collaboration with University of Texas – Austin, we evaluated a new flexible, gold-based epidermal electrode for sensing muscle activity.

Sample sEMG signal from one subject’s FCU for (left) MVIC; (middle) dynamic and (right) functional tests indicate that there were no significant differences between the Delsys (lighter grey) and ESS electrodes (darker grey) based on raw sEMG amplitude, linear envelope amplitude, or power spectral density.Background: Commercially available electrodes can only provide quality surface electromyography (sEMG) measurements for a limited duration due to user discomfort and signal degradation, but in many applications, collecting sEMG data for a full day or longer is desirable to enhance clinical care. Few studies for long-term sEMG have assessed signal quality of electrodes using clinically relevant tests. The goal of this research was to evaluate flexible, gold-based epidermal sensor system (ESS) electrodes for long-term sEMG recordings.

Methods: We collected sEMG and impedance data from eight subjects from ESS and standard clinical electrodes on upper extremity muscles during maximum voluntary isometric contraction tests, dynamic range of motion tests, the Jebsen Taylor Hand Function Test, and the Box & Block Test. Four additional subjects were recruited to test the stability of ESS signals over four days.

Results: Signals from the ESS and traditional electrodes were strongly correlated across tasks. Measures of signal quality, such as signal-to-noise ratio and signal-to-motion ratio, were also similar for both electrodes.

Conclusions: Over the four-day trial, no significant decrease in signal quality was observed in the ESS electrodes, suggesting that thin, flexible electrodes may provide a robust tool that does not inhibit movement or irritate the skin for long-term measurements of muscle activity in rehabilitation and other applications.

BR Shuman, MH Schwartz, KM Steele (2017) “Electromyography Data Processing Impacts Muscle Synergies during Gait for Unimpaired Children and Children with Cerebral Palsy.” Frontiers in Computational Neuroscience

Dr. Steele JournalArticle, MotorControl, Projects, Publications , , , , ,
Example data from a representative TD participant. Left: EMG data processed with varying LP filter cutoffs. Center: Synergy weights and activations. Right: Total variance accounted for by n synergies. Total variance accounted for by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency.

Journal article in Frontiers in Computational Neuroscience:

Filtering parameters impact the results from muscle synergy analyses.

AExample data from a representative TD participant. Left: EMG data processed with varying LP filter cutoffs. Center: Synergy weights and activations. Right: Total variance accounted for by n synergies. Total variance accounted for by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency.bstract: Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpretation is important. The aim of this study was to evaluate how EMG signal processing impacts synergy outputs during gait. We evaluated the impacts of two common processing steps for synergy analyses: low pass (LP) filtering and unit variance scaling. We evaluated EMG data collected during barefoot walking from five muscles of 113 children with cerebral palsy (CP) and 73 typically-developing (TD) children. We applied LP filters to the EMG data with cutoff frequencies ranging from 4 to 40 Hz (reflecting the range reported in prior synergy research). We also evaluated the impact of normalizing EMG amplitude by unit variance. We found that the total variance accounted for (tVAF) by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency (e.g., 9.3 percentage points change for one synergy between 4 and 40 Hz). This change in tVAF can alter the number of synergies selected for further analyses. Normalizing tVAF to a z-score (e.g., dynamic motor control index during walking, walk-DMC) reduced sensitivity to LP cutoff. Unit variance scaling caused comparatively small changes in tVAF. Synergy weights and activations were impacted less than tVAF by LP filter choice and unit variance normalization. These results demonstrate that EMG signal processing methods impact outputs of synergy analysis and z-score based measures can assist in reporting and comparing results across studies and clinical centers.

Engineering Discovery Days

Keshia MotorControl, News, Orthoses, Outreach , ,

Our lab had a great time sharing our research at the College of Engineering Discovery Days. Our booth was entitled, “The Ultimate Machine” because we think of the human body as a complex system with our brain as a controller/computer and our muscles as our motors. Elementary and middle school students used their neural pathway, from brain to muscle, to control a robot gripper by either relaxing or activating their muscle.  A student activates his muscle to hold a golf ball with a robot gripper Our lab director, Kat Steele, explains why ankle foot orthoses are used and what we are doing to optimize the device. Another student tries her luck at holding a golf ball with a robot hand. The record hold time was 170 seconds. A group of students cheer on their peer as he activates his muscle to hold a golf ball with a robot gripper Elementary and middle school aged students try on 3D printed prosthetic devices