Biomedical subjects

Daniel W Stashuk

Publications and source records attributed to Daniel W Stashuk.

6 recordsLinked to original sources

PubMed2005

The effect of contraction intensity on motor unit number estimates of the tibialis anterior.

OBJECTIVE: To examine the effect of contractile level on motor unit number estimates (MUNEs) and establish the contraction intensity that will yield the most representative MUNE for the tibialis anterior (TA) muscle. METHODS: Surface and intramuscular electromyographic (EMG) signals were collected during a range of submaximal (threshold, 10, 20, 30 and 40% MVC) isometric dorsiflexion contractions using decomposition-enhanced spike-triggered averaging (DE-STA). Six MUNEs were calculated, one for each of the five intensities, and an ensemble sixth MUNE that had equal MU contributions from all intensities. RESULTS: Mean surface-motor unit potential sizes increased significantly (26-69 microV) and MUNEs decreased accordingly (226-91) as contraction intensity increased from threshold to 40% MVC, respectively (P<0.05). The ensemble MUNE was 153, and extrapolated to approximately 25% MVC. CONCLUSIONS: There was a significant and progressive decline in the MUNE as contraction intensity increased, confirming the importance of monitoring torque during data collection. The ensemble MUNE suggests that collecting EMG signals at a contraction intensity of approximately 25% MVC provides the most representative sample of the actual number and sizes of MUs in the TA. SIGNIFICANCE: Establishing appropriate contraction intensities improves the utility of DE-STA as a useful method for tracking changes to the MU pool in disease states and healthy aging.

Action Potentials↗

PubMed2005

Decomposition-based quantitative electromyography: effect of force on motor unit potentials and motor unit number estimates.

Decomposition-based quantitative electromyography (DQEMG) allows for the collection of motor unit potentials (MUPs) over a broad range of force levels. Given the size principle of motor unit recruitment, it may be necessary to control for force when using DQEMG for the purpose of deriving a motor unit number estimate (MUNE). Therefore, this study was performed to examine the effect of force on the physiological characteristics of concentric needle- and surface-detected MUPs and the subsequent impact on MUNEs obtained from the first dorsal interosseous (FDI) muscle sampled using DQEMG. Maximum M waves were elicited in 10 subjects with supramaximal stimulation of the ulnar nerve at the wrist. Intramuscular and surface-detected EMG signals were collected simultaneously during 30-s voluntary isometric contractions performed at specific percentages of maximal voluntary contraction (MVC). Decomposition algorithms were used to identify needle-detected MUPs and their individual MU firing times. These MU firing times were used as triggers to extract their corresponding surface-detected MUPs (S-MUPs) using spike-triggered averaging. A mean S-MUP was then calculated, the size of which was divided into the maximum M-wave size to derive a MUNE. Increased levels of contraction had a significant effect on needle- and surface-detected MUP size, firing rate, and MUNE. These results suggest that force level is an important factor to consider when performing quantitative EMG, including MUNEs with this method.

Adult↗

PubMed2005

Motor unit number estimates in the tibialis anterior muscle of young, old, and very old men.

The rate of motor unit (MU) loss and its influence on the progression of sarcopenia is not well understood. Therefore, the main purpose of this study was to estimate and compare numbers of MUs in the tibialis anterior (TA) of young men ( approximately 25 years) and two groups of older men ( approximately 65 years and >/=80 years). Decomposition-enhanced spike-triggered averaging was used to collect surface and intramuscular electromyographic signals during isometric dorsiflexions at 25% of maximum voluntary contraction. The mean surface-MU potential size was divided into the maximum M wave to calculate the motor unit number estimate (MUNE). The MUNE was significantly reduced in the old (91) compared to young (150) men, and further reduced in the very old men (59). Despite the smaller MUNE at age 65, strength was not reduced until beyond 80 years. This suggests that age-related MU loss in the TA does not limit function until a critical threshold is reached.

Adult↗

PubMed2005

Physiologically based simulation of clinical EMG signals.

An algorithm that generates electromyographic (EMG) signals consistent with those acquired in a clinical setting is described. Signals are generated using a model constructed to closely resemble the physiology and morphology of skeletal muscle, combined with line source models of commonly used needle electrodes positioned in a way consistent with clinical studies. The validity of the simulation routines is demonstrated by comparing values of statistics calculated from simulated signals with those from clinical EMG studies of normal subjects. The simulated EMG signals may be used to explore the relationships between muscle structure and activation and clinically acquired EMG signals. The effects of motor unit (MU) morphology, activation, and neuromuscular junction activity on acquired signals can be analyzed at the fiber, MU and muscle level. Relationships between quantitative features of EMG signals and muscle structure and activation are discussed.

Action Potentials↗

PubMed2004

Motor unit number estimation by decomposition-enhanced spike-triggered averaging: control data, test-retest reliability, and contractile level effects.

Decomposition-enhanced spike-triggered averaging (DE-STA) has been developed as a method for obtaining a motor unit number estimate (MUNE). We describe the method and report control data for the first dorsal interosseous/adductor pollicis and thenar muscles and reliability in the thenar muscles. Seventeen subjects (ages 20-50 years) took part in the study. The maximum M potential was elicited with supramaximal stimulation of the ulnar or median nerve at the wrist. Surface and intramuscularly detected electromyographic signals were then collected simultaneously during mild to moderate contractions. Decomposition algorithms were used to detect and sort the individual motor unit potential (MUP) occurrences of several concurrently active motor units in the needle-detected signals. The MUP occurrences were used as triggering sources to estimate their corresponding surface-detected MUPs (S-MUPs) using STA. The mean S-MUP size was calculated and divided into the maximum M-potential size to derive a MUNE. The MUNE values were consistent with those previously reported with other methods, and thenar MUNEs for the two trials were similar (249 +/- 78 and 246 +/- 90), with high test-retest reliability (r = 0.94, P < 0.05). DE-STA thus appears to be a valid and reliable method to obtain MUNEs.

Action Potentials↗

PubMed2003

Decomposition-based quantitative electromyography: methods and initial normative data in five muscles.

Quantitative electromyographic (EMG) techniques provide clinically useful information to aid in the diagnosis and follow the course or response to treatment of diseases affecting the motor system. The purpose of this study was to describe a decomposition-based quantitative electromyography method (DQEMG) designed to obtain clinically applicable information relating to motor unit potential (MUP) size and configuration, and motor unit (MU) firing characteristics. Additionally, preliminary normative data were obtained from the deltoid, biceps brachii, first dorsal interosseous, vastus medialis, and tibialis anterior muscles of 13 control subjects. DQEMG was capable of efficiently and accurately extracting MUP data from complex interference patterns during mild to moderate contractions. MUP amplitude, surface-detected MUP (S-MUP) amplitude, MUP duration, number of phases, and MU firing frequencies varied significantly across muscles. The mean parameter values for the individual muscles studied were similar to previous reports based on other quantitative methods. The main advantages of this method are the speed of data acquisition and processing, the ability to obtain MUPs from MUs with low and higher recruitment thresholds, and the ability to obtain both S-MUP or macro-MUP data as well as MU firing rate information.

Adult↗