Differences in muscle contraction onset as determined by ultrasound and electromyography

Distributed Wearable Ultrasound Sensors Predict Isometric Ground Reaction Force

Rehabilitation from musculoskeletal injuries focuses on reestablishing and monitoring muscle activation patterns to accurately produce force. The aim of this study is to explore the use of a novel low-powered wearable distributed Simultaneous Musculoskeletal Assessment with Real-Time Ultrasound (SMART-US) device to predict force during an isometric squat task. Participants (N = 5) performed maximum isometric squats under two medical imaging techniques; clinical musculoskeletal motion mode (m-mode) ultrasound on the dominant vastus lateralis and SMART-US sensors placed on the rectus femoris, vastus lateralis, medial hamstring, and vastus medialis. Ultrasound features were extracted, and a linear ridge regression model was used to predict ground reaction force. The performance of ultrasound features to predict measured force was tested using either the Clinical M-mode, SMART-US sensors on the vastus lateralis (SMART-US: VL), rectus femoris (SMART-US: RF), medial hamstring (SMART-US: MH), and vastus medialis (SMART-US: VMO) or utilized all four SMART-US sensors (Distributed SMART-US). Model training showed that the Clinical M-mode and the Distributed SMART-US model were both significantly different from the SMART-US: VL, SMART-US: MH, SMART-US: RF, and SMART-US: VMO models (p < 0.05). Model validation showed that the Distributed SMART-US model had an R2 of 0.80 ± 0.04 and was significantly different from SMART-US: VL but not from the Clinical M-mode model. In conclusion, a novel wearable distributed SMART-US system can predict ground reaction force using machine learning, demonstrating the feasibility of wearable ultrasound imaging for ground reaction force estimation.

Rectus abdominis muscle thickness change and activation increase during planks performed on different surfaces

AIMS

The plank is a common exercise used to evaluate core function. Surface electromyography (sEMG) and ultrasound can be used simultaneously to measure muscle activity. We aimed to compare the %-thickness and %-activation during the plank performed on three surfaces and to determine agreement and relationship between rectus abdominis (RA) %-thickness of a rested tabletop position and %-activation normalized to quiet tabletop position during the plank on three surfaces.

METHODS

In this cross-sectional study, ultrasound and sEMG measured RA muscle function during the first 5-s and last 5-s of a plank performed on a table, yoga mat, and fitness ball. A repeated measures ANOVA compared differences in %-thickness change and Friedman's tests compared differences in %-activation, alpha set a priori p ≤ 0.05. Bland-Altman plots measured agreement between instruments. Spearman's rho determined relationships between instruments.

RESULTS

There was no difference between %-thickness change across surfaces during the first 5-s or last 5-s, or between %-activation during the last 5-s. The %-activation of the RA during the first 5-s performed on the fitness ball was higher than the table and yoga mat (p < 0.001). Ultrasound and sEMG had weak relationships across all surfaces (ρ = - 0.078 to 0.116).

CONCLUSION

The first 5-s of the plank performed on the fitness ball requires a greater RA activation. Ultrasound could not detect changes in %-thickness of the RA during the plank which may be influenced by the type of contraction. Comparison between these measurement tools during isometric exercise should be used with caution.

A Comparison of Approaches for Segmenting the Reaching and Targeting Motion Primitives in Functional Upper Extremity Reaching Tasks

There is growing interest in the kinematic analysis of human functional upper extremity movement (FUEM) for applications such as health monitoring and rehabilitation. Deconstructing functional movements into activities, actions, and primitives is a necessary procedure for many of these kinematic analyses. Advances in machine learning have led to progress in human activity and action recognition. However, their utility for analyzing the FUEM primitives of reaching and targeting during reach-to-grasp and reach-to-point tasks remains limited. Domain experts use a variety of methods for segmenting the reaching and targeting motion primitives, such as kinematic thresholds, with no consensus on what methods are best to use. Additionally, current studies are small enough that segmentation results can be manually inspected for correctness. As interest in FUEM kinematic analysis expands, such as in the clinic, the amount of data needing segmentation will likely exceed the capacity of existing segmentation workflows used in research laboratories, requiring new methods and workflows for making segmentation less cumbersome. This paper investigates five reaching and targeting motion primitive segmentation methods in two different domains (haptics simulation and real world) and how to evaluate these methods. This work finds that most of the segmentation methods evaluated perform reasonably well given current limitations in our ability to evaluate segmentation results. Furthermore, we propose a method to automatically identify potentially incorrect segmentation results for further review by the human evaluator. Clinical impact: This work supports efforts to automate aspects of processing upper extremity kinematic data used to evaluate reaching and grasping, which will be necessary for more widespread usage in clinical settings.

Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound

OBJECTIVE

The study of human neuromechanical control at the motor unit (MU) level has predominantly focussed on electrical activity and force generation, whilst the link between these, i.e., the muscle deformation, has not been widely studied. To address this gap, we analysed the kinematics of muscle units in natural contractions.

APPROACH

We combined high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) recordings, at 1000 frames per second, from the tibialis anterior muscle to measure the motion of the muscular tissue caused by individual MU contractions. The MU discharge times were identified online by decomposition of the HDsEMG and provided as biofeedback to 12 subjects who were instructed to keep the MU active at the minimum discharge rate (9.8 ± 4.7 pulses per second; force less than 10% of the maximum). The series of discharge times were used to identify the velocity maps associated with 51 single muscle unit movements with high spatio-temporal precision, by a novel processing method on the concurrently recorded US images. From the individual MU velocity maps, we estimated the region of movement, the duration of the motion, the contraction time, and the excitation-contraction (E-C) coupling delay.

MAIN RESULTS

Individual muscle unit motions could be reliably identified from the velocity maps in 10 out of 12 subjects. The duration of the motion, total contraction time, and E-C coupling were 17.9 ± 5.3 ms, 56.6 ± 8.4 ms, and 3.8 ± 3.0 ms (n = 390 across 10 participants). The experimental measures also provided the first evidence of muscle unit twisting during voluntary contractions and MU territories with distinct split regions.

SIGNIFICANCE

The proposed method allows for the study of kinematics of individual MU twitches during natural contractions. The described measurements and characterisations open new avenues for the study of neuromechanics in healthy and pathological conditions.

Identification of single motor units in skeletal muscle under low force isometric voluntary contractions using ultrafast ultrasound

The central nervous system (CNS) controls skeletal muscles by the recruitment of motor units (MUs). Understanding MU function is critical in the diagnosis of neuromuscular diseases, exercise physiology and sports, and rehabilitation medicine. Recording and analyzing the MUs’ electrical depolarization is the basis for state-of-the-art methods. Ultrafast ultrasound is a method that has the potential to study MUs because of the electrical depolarizations and consequent mechanical twitches. In this study, we evaluate if single MUs and their mechanical twitches can be identified using ultrafast ultrasound imaging of voluntary contractions. We compared decomposed spatio-temporal components of ultrasound image sequences against the gold standard needle electromyography. We found that 31% of the MUs could be successfully located and their firing pattern extracted. This method allows new non-invasive opportunities to study mechanical properties of MUs and the CNS control in neuromuscular physiology.

M-Mode Ultrasound Examination of Soleus Muscle in Healthy Subjects: Intra- and Inter-Rater Reliability Study

Objective: M-mode ultrasound imaging (US) reflects the motion of connective tissue within muscles. The objectives of this study were to evaluate inter-rater and intra-rater reliability of soleus muscle measurements between examiners with different levels of US experience in asymptomatic subjects and to investigate the level of soleus muscle isometric activity in two positions (knee extended and knee flexed at 30°). Methods: Thirty volunteers without a history of ankle pain were evaluated with US examinations of the soleus muscle. Each muscle was scanned independently by two evaluators. Muscle at rest thickness, maximal isometric contraction thickness, time and velocity measures were detailed and blinded to the other examiner. Results: Intra- and inter-rater reliability at rest, in maximal isometric contraction thickness, contraction time and contraction velocity measures for both positions (extended and flexed knee) were reported from good to excellent for all outcome measurements. The position with the knee extended reported a statistically significant increase in thickness after motion showing 1.33 ± 0.27 mm for measurements at rest thickness with knee extended versus 1.50 ± 0.29 mm for measurements at end thickness with the knee in flexed position (p = 0.001), as well as 1.31 ± 0.23 mm for rest thickness with the knee in flexed position measurements with respect to 1.34 ± 0.24 mm for maximal isometric contraction thickness with extended knee measurements (p = 0.058). Conclusions: This study found that intra- and inter-examiner reliability of M-mode ultrasound imaging of the soleus muscle was excellent in asymptomatic subjects and the soleus muscle activity was different between the position with the knee extended and the position with the knee flexed.