EMG Archives - Page 2 of 3 - Neuromechanics & Mobility Lab

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 April 20, 2018October 12, 2021EMG

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.

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 May 19, 2017October 12, 2021Cerebral Palsy, EMG, Gillette, Synergy, UWIN, Walk-DMC

Journal article in Frontiers in Computational Neuroscience:

Filtering parameters impact the results from muscle synergy analyses.

Abstract: 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 April 22, 2016October 12, 2021Discovery Days, EMG, Orthoses

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

Seattle’s MESA Day (Mathematics Engineering Science Achievement)

Keshia News, Outreach March 29, 2016October 12, 2021EMG, MESA, STEM

MESA Day brought high school and middle school students from the Seattle area to North Seattle College for a morning of competitions and STEM activities, put on by volunteers in the community. Gaurav and Michael developed an activity using electromyography (EMG) sensors to teach students about neural control of muscles, how we quantify muscle activity, and how we can use that knowledge to improve quality of life. Small groups selected a “test subject” and hooked up an EMG sensor to a muscle of their choice. They then picked tasks to perform, generated corresponding hypothetical muscle activation curves, and experimentally tested their hypotheses. The attendees were impressive. Students, ages 13-18, surprised our PhD students with their curiosity, knowledge, and ability to generate hypotheses and explain their results. Overall, the students seemed to enjoy the event and we hope that we helped them think about how understanding the mechanisms of the human body can be used to improve lives.

BR Shuman, M Goudriaan, L Bar-On, MH Schwartz, K Desloovere, KM Steele (2016) “Repeatability of muscle synergies within and between days for typically developing children and children with cerebral palsy.” Gait & Posture.

Dr. Steele JournalArticle, MotorControl, Projects, Publications January 28, 2016October 12, 2021Cerebral Palsy, EMG, Gillette, Leuven, Synergy

Journal article in Gait and Posture:

Filtering parameters impact the results from muscle synergy analyses.

Abstract: Muscle synergies are typically calculated from electromyographic (EMG) signals using nonnegative matrix factorization. Synergies identify weighted groups of muscles that are commonly activated together during a task, such as walking. Synergy analysis has become an emerging tool to evaluate neuromuscular control; however, the repeatability of synergies between trials and days has not been evaluated. The goal of this study was to evaluate the repeatability of synergy complexity and structure in unimpaired individuals and individuals with cerebral palsy (CP). EMG data were collected from eight lower-limb muscles during gait for six typically developing (TD) children and five children with CP on two separate days, over three walking speeds. To evaluate synergy complexity, we calculated the total variance accounted for by one synergy (tVAF1). On a given day, the average range in tVAF1 between gait cycles was 18.2% for TD and 19.1% for CP. The average standard deviation in tVAF1 between gait cycles was 4.9% for TD and 5.0% for CP. Average tVAF1 calculated across gait cycles was not significantly different between days for TD or CP participants. Comparing synergy structure, the average (standard deviation) within day correlation coefficients of synergy weights for two or more synergies were 0.89 (0.15) for TD and 0.88 (0.15) for CP. Between days, the average correlation coefficient of synergy weights for two or more synergies was greater than 0.89 for TD and 0.74 for CP. These results demonstrate that synergy complexity and structure averaged over multiple gait cycles are repeatable between days in both TD and CP groups.