Search

Dataverse de l'Université du Québec à Trois-Rivières Logo
The Effect of Trunk Position and Pain Location on Lumbar Extensor Muscle Recruitment Strategies
Borealis
Ducas, Julien — 2024-06-12 Healthy participants performed isometric contractions in three positions: neutral, 45° trunk flexion, and 90° trunk flexion; under three conditions: no pain (NP), caudal pain (CrP), and cranial pain (CaP). During each contraction, myoelectric activity of the right and left lumbar extensor muscle was recorded with two HDsEMG of 64 electrodes arranged in 8 columns and 8 rows spaced by 10 mm (semidisposable adhesive matrix; model ELSCH064, OTBioelettronica, Torino, Italy). Furthermore, the force signal generated during the isometric contractions was recorded using the load cell. Dependent variables were calculated for each pain condition (No pain, CrP, CaP) and for each position (neutral, 45° trunk flexion, 90° trunk flexion). Specifically, pain intensity, HDsEMG variables and force were analyzed. With regards to the HDsEMG dependent variable, the ‘Muscle activity amplitude’ corresponded to the mean of the root mean square (RMS) across all filtered channels. This amplitude was subsequently normalized using the mean MVIC amplitude calculated over a 1-second epoch in the corresponding position for each task. In addition, as a complementary analysis to further investigate the effect of trunk position on LEM activation strategies, the muscle activity amplitude normalized to the force produced was computed. To determine the spatial distribution of muscle activity of LEM, the medio-lateral (x) and cranio-caudal (y) coordinates of the centroid were calculated. To facilitate in the interpretation of the spatial coordinates, the right array was flipped along the x-axis, so higher x coordinates indicate a more medial location of the centroid on both sides. The centroid represents the average position of the channels that had absolute RMS values greater than 70% of the maximum absolute RMS value across all channels during the contractions. Specifically, channels with values exceeding 70% of the maximum RMS value were selected, and their estimates were averaged to generate a single estimate for each side, encompassing both x- and y-axis coordinates. For the force generation variables, ‘Force production' corresponds to the mean force exerted in Newton while ‘Force steadiness’ is determined by the CoV of force. As a complementary analysis, the variability in individual pain responses under both CrP and CaP conditions was illustrated by comparing them to the baseline score (no pain condition) for metrics such as muscle activity amplitude, centroid coordinates, and CoV, for each participant. Variability in muscle activity amplitude was determined by calculating the difference between each pain condition and the baseline, and then multiplying it by 100 to represent a percentage of change. For the centroid coordinates and force steadiness, only the differences between each pain conditions and baseline are presented.
Dataverse de l'Université du Québec à Trois-Rivières Logo
Task-dependent neuromuscular adaptation in low back pain
Borealis
Ducas, Julien — 2024-09-10 24 healthy participants performed isometric back extension contractions in two positions (45° and 90° trunk flexion) under two conditions (no pain and experimental low back pain using electrical stimulation). Lumbar muscle activation strategies were recorded using high-density surface electromyography on both sides and force steadiness (standard deviation of force production) was recoded using a load cell. The signals were imported and analyzed using Matlab (v.2023b; TheMathWorks, Natick, MA). Throughout all isometric trunk extension contractions, HDsEMG data were gathered and analyzed independently for both the left and right sides. Then, the HDsEMG signals were filtered using an 8th-order Butterworth filter with a frequency range of 30–400 Hz. In addition, a 2nd-order Butterworth notch filter was used to eliminate interference from the 60 Hz power lines and its harmonics. For the recording during all isometric trunk extension contractions, a comprehensive visual examination of the raw HDsEMG signals was conducted, which led to the identification of electrodes exhibiting contact issues or artifacts induced by stimulation. To further evaluate the presence of stimulation-related artifacts, amplitude spectra were computed for all electrodes and for each condition using a Fast Fourier transform and visually screened. For electrodes that had such problems, a reconstruction technique was applied by interpolating data from neighboring electrodes. If these electrode artifacts were observed on more than 10% of all electrodes, the recording was excluded from the analysis. The ten middle seconds of each signal recording were analyzed and segmented into consecutive windows of 0.5s. Force signals underwent a low-pass filtering at 10 Hz using a 2nd-order Butterworth filter. The force steadiness was examined for each position and painful condition. To evaluate the force steadiness, the standard deviation (SD) was computed. Dependent variables were calculated for each pain condition (baseline and lumbar pain) and for each position (45° trunk flexion and 90° trunk flexion). Specifically, pain intensity, HDsEMG variables, and force steadiness were computed. Regarding the dependent variable of HDsEMG, ‘Muscle activity amplitude’ corresponded to the mean of the root mean square (RMS) in all filtered channels, which is then normalized using the mean RMS of the MVC in its corresponding position. To determine the spatial distribution of lumbar extensor muscle activity, the means of the mediolateral and craniocaudal coordinates of the centroid were calculated. To evaluate the magnitude of neuromuscular adaptation to pain, the centroid coordinates collected during the pain condition were subjected to a subtraction process from the one collected during the baseline condition. The resulting differences were transformed into absolute values to assess the magnitude rather than the direction of redistribution. For muscle activity amplitude, the percentage of change from the baseline condition was assessed and transformed into absolute values to assess the magnitude of muscle amplitude adaptation to pain. Regarding the force variable used as an assessment metric to maintain the task goal of 20% of the MVIC, 'Force steadiness’ was used and represented the standard deviation (SD) of force during the isometric back extension contraction. To evaluate how the magnitude of neuromuscular adaptation to pain influences the capability to generate force, the force steadiness during the lumbar pain condition was subtracted from the baseline condition. However, unlike the HDsEMG data, these differences were not transformed into absolute values. This approach was designed to discern whether there was an increase or decrease in the ability to produce force, emphasizing the impact of the magnitude of pain adaptation on the capability to maintain the goal of the task.

Map search instructions

1.Turn on the map filter by clicking the “Limit by map area” toggle.
2.Move the map to display your area of interest. Holding the shift key and clicking to draw a box allows for zooming in on a specific area. Search results change as the map moves.
3.Access a record by clicking on an item in the search results or by clicking on a location pin and the linked record title.
Note: Clusters are intended to provide a visual preview of data location. Because there is a maximum of 50 records displayed on the map, they may not be a completely accurate reflection of the total number of search results.

(Source Repository: Dataverse de l'Université du Québec à Trois-Rivières) AND (Author: Ducas, Julien)

Limit by:

Clear all

to