Identification and classification of involuntary leg muscle contractions in electromyographic records from individuals with spinal cord injury

Thomas, Christine K.; Dididze, Marine; Martínez, A.; Morris, Richard

doi:10.1016/j.jelekin.2014.05.013

Cited by 19 publications

(10 citation statements)

References 25 publications

(37 reference statements)

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“…Electromyographic activity (EMG) has been used to document the various types of involuntary muscle contractions that occur during daily tasks (Tepavac et al, 1992 ; Winslow et al, 2009 ; Thomas et al, 2014 ), or imposed movements (Benz et al, 2005 ), when tone is assessed using the Ashworth scale (Sköld et al, 1998 ; Sherwood et al, 2000 ; McKay et al, 2004 ), as muscles are stretched passively (Burke et al, 1971 ), or when people with SCI walk (e.g., Yang et al, 1991 ; Harkema, 2001 ; Kressler et al, 2014 ). If injured individuals are using these contractions to judge spasticity, quantification of this muscle activity may provide a novel and important approach to improve the poor correlations often found between physiological, clinical and self-reported measures of spasticity.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Involuntary Contractions after Spinal Cord Injury Reveals Associations between Physiological and Self-Reported Measures of Spasticity

Mayo

DeForest

Castellanos

et al. 2017

Front. Integr. Neurosci.

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Correlations between physiological, clinical and self-reported assessments of spasticity are often weak. Our aims were to quantify functional, self-reported and physiological indices of spasticity in individuals with thoracic spinal cord injury (SCI; 3 women, 9 men; 19–52 years), and to compare the strength and direction of associations between these measures. The functional measure we introduced involved recording involuntary electromyographic activity during a transfer from wheelchair to bed which is a daily task necessary for function. High soleus (SL) and tibialis anterior (TA) F-wave/M-wave area ratios were the only physiological measures that distinguished injured participants from the uninjured (6 women, 13 men, 19–67 years). Hyporeflexia (decreased SL H/M ratio) was unexpectedly present in older participants after injury. During transfers, the duration and intensity of involuntary electromyographic activity varied across muscles and participants, but coactivity was common. Wide inter-participant variability was seen for self-reported spasm frequency, severity, pain and interference with function, as well as tone (resistance to imposed joint movement). Our recordings of involuntary electromyographic activity during transfers provided evidence of significant associations between physiological and self-reported measures of spasticity. Reduced low frequency H-reflex depression in SL and high F-wave/M-wave area ratios in TA, physiological indicators of reduced inhibition and greater motoneuron excitability, respectively, were associated with long duration SL and biceps femoris (BF) electromyographic activity during transfers. In turn, participants reported high spasm frequency when transfers involved short duration TA EMG, decreased co-activation between SL and TA, as well as between rectus femoris (RF) vs. BF. Thus, the duration of muscle activity and/or the time of agonist-antagonist muscle coactivity may be used by injured individuals to count spasms. Intense electromyographic activity and high tone related closely (possibly from joint stabilization), while intense electromyographic activity in one muscle of an agonist-antagonist pair (especially in TA vs. SL, and RF vs. BF) likely induced joint movement and was associated with severe spasms. These data support the idea that individuals with SCI describe their spasticity by both the duration and intensity of involuntary agonist-antagonist muscle coactivity during everyday tasks.

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Section: Introductionmentioning

confidence: 99%

Characterization of Involuntary Contractions after Spinal Cord Injury Reveals Associations between Physiological and Self-Reported Measures of Spasticity

Mayo

DeForest

Castellanos

et al. 2017

Front. Integr. Neurosci.

View full text Add to dashboard Cite

show abstract

“…We quantified the duration of the muscles spasms based on the EMG record, using the approach described by Thomas et al and our previous work . Briefly, filtered and rectified EMG was integrated over 10 ms. To separate EMG from baseline noise, a threshold was calculated based on the 30 seconds rest period prior to transfer.…”

Section: Methodsmentioning

confidence: 99%

Spasticity and Pain after Spinal Cord Injury: Impact on Daily Life and the Influence of Psychological Factors

Tibbett

Field-Fote

Thomas

et al. 2019

PM&R

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Background Spasticity and pain frequently co‐occur in persons with spinal cord injury (SCI), yet, how these sequelae interact in daily life is unclear. Additionally, little is known about how psychological factors relate to the perception of spasticity and its impacts on daily life. Objectives (1) Characterize relationships between spasticity and chronic pain with regard to perceived severity, difficulty dealing, and life interference. (2) Determine the extent to which perceived spasticity severity and physiological, psychological, and pain‐related factors contribute to impacts of spasticity on daily life (difficulty in dealing, life interference). (3) Determine the effects of painful spasticity on aspects of chronic pain and spasticity (severity, life interference, interference with sleep, and spasm duration). Design Observational study. Setting University laboratory. Participants Twenty participants with SCI and lower extremity spasticity. Methods Measures included International SCI Pain Basic Data Set, Pain and Spasticity Inventories, Difficulty Dealing with Pain/Spasticity, SCI‐Spasticity Evaluation Tool, Connor‐Davidson Resilience and Moorong Self‐Efficacy Scales, Spinal Cord Assessment Tool for Spastic Reflexes, spasm duration, and injury‐related and demographic factors. Bivariate correlations, multiple regression analyses, and pairwise comparisons were performed. Results Spasticity and chronic pain were directly related, with respect to perceived severity, difficulty dealing, and life interference (rho = 0.514‐0.673, P < .05). Shorter injury duration, greater perceived spasticity severity, and greater difficulty dealing with pain explained 61% of variance in difficulty dealing with spasticity. Greater perceived spasticity severity and lower resilience explained 72% of variance in life interference of spasticity. Spasm duration was not significantly associated with perceived spasticity severity. Participants with painful spasticity had significantly greater chronic pain severity (P = .02) and sleep‐related impact of spasticity (P = .03) than participants without painful spasticity. Conclusions Perceived severity of spasticity, injury duration, ability to deal with chronic pain, resilience, and painful spasms appear to play important roles in the negative impacts of spasticity on life after SCI. Level of Evidence III.

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“…Clonus involves periodic bursts of EMG between 4 and 12 Hz, the frequency of which largely depend on the length of the reflex arc [13], [14]. Clonus is documented clinically when there are four bursts of EMG [15].…”

Section: Clonus Classificationmentioning

confidence: 99%

Automatic Identification and Classification of Muscle Spasms in Long-Term EMG Recordings

Winslow

Martínez

Thomas

2015

IEEE J. Biomed. Health Inform.

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Spinal cord injured (SCI) individuals may be afflicted by spasticity, a condition in which involuntary muscle spasms are common. EMG recordings can be analyzed to quantify this symptom of spasticity but manual identification and classification of spasms are time consuming. Here, an algorithm was created to find and classify spasm events automatically within 24-h recordings of EMG. The algorithm used expert rules and time-frequency techniques to classify spasm events as tonic, unit, or clonus spasms. A companion graphical user interface (GUI) program was also built to verify and correct the results of the automatic algorithm or manually defined events. Eight channel EMG recordings were made from seven different SCI subjects. The algorithm was able to correctly identify an average (±SD) of 94.5 ± 3.6% spasm events and correctly classify 91.6 ± 1.9% of spasm events, with an accuracy of 61.7 ± 16.2%. The accuracy improved to 85.5 ± 5.9% and the false positive rate decreased to 7.1 ± 7.3%, respectively, if noise events between spasms were removed. On average, the algorithm was more than 11 times faster than manual analysis. Use of both the algorithm and the GUI program provide a powerful tool for characterizing muscle spasms in 24-h EMG recordings, information which is important for clinical management of spasticity.

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Identification and classification of involuntary leg muscle contractions in electromyographic records from individuals with spinal cord injury

Cited by 19 publications

References 25 publications

Characterization of Involuntary Contractions after Spinal Cord Injury Reveals Associations between Physiological and Self-Reported Measures of Spasticity

Characterization of Involuntary Contractions after Spinal Cord Injury Reveals Associations between Physiological and Self-Reported Measures of Spasticity

Spasticity and Pain after Spinal Cord Injury: Impact on Daily Life and the Influence of Psychological Factors

Automatic Identification and Classification of Muscle Spasms in Long-Term EMG Recordings

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