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correlations (red) and the ratio correlation/NRMSE (black) between the original and fingerprint obtained by adjusting the displaced electrode grid (a) roughly identified angle of rotation (42.5 ) as a peak of the ratio correlation/NRMSE and (b) pinpointed precise value of 42 Angular precision could be tested on subject 2, where the same 2 fingerprints were found in two electrode displacement configurations. Searching for the joint peak of agreement revealed the angular ambiguity of 1.6 degrees.
Source publication
Introduction:
This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Ad-vanced Methods for Neural Signals and Images".
Objectives:
The study discusses a technique to automatically correct for effects of electrode grid displacement across serial surface EMG measurements with high-density electr...
Context in source publication
Context 1
... 25 reliable MU fingerprints were extracted with the decomposition method. Out of these, 3 units could be tracked across measurements: 1 unit appeared in 3 configurations (1, 2, 4), and the remaining two were matched across configurations 1 and 2. An example for the automatic correction of the specified 45 degrees displacement is portrayed in Fig. 3, showing the correlation and the ratio between correlation and NRMSE. The angle was estimated at 42 degrees, translation at -2 and 3 mm displacement in x and y directions respectively. Fig. 4. (a) and (b) indicate the originally recorded fingerprints from positions 2 and 1 respectively. Once the rotational and translational corrections ...
Citations
... Some studies at low muscle voluntary contraction concerning grid misalignment have been already introduced on MU fingerprints using HD-sEMG technique [6], [7]. This generates the study of isolated MUAP topographies. ...
... We also simulated 3 levels of muscle voluntary contractions (high and low) rather than one contraction levels and with different anatomies and MU recruitment patterns rather than just one anatomy as in [1]. Also, in this study we worked on the total sEMG signal by using an (8x8) electrode which seems to be more general and practical than working on single MU fingerprint recognition by using a (6x6) electrode on low contraction levels as in [7]. In future works, further improvements will be tested concerning nonlinear correlation analysis on segmented region of the matrices (64x64) of h 2 values to increase both sensitivity and robustness to clinical variability of the proposed approach. ...
... Some automatic realignment approaches have been already proposed on MU fingerprints using HD-sEMG techniques [7] [8]. This induces the study, at low muscle contraction levels, of isolated MUAP topographies. ...
In a recent past, several techniques have been developed to analyze the effect of electrode grid alignment with the muscle fibers. But, they focused on pattern matching of Motor Unit (MU) electrical signatures and not on the interference signal. In this study, we use a method which is widely applied in connectivity and directionality analysis of stochastic and complex signals, namely, the nonlinear correlation coefficient (h2) on HD-sEMG signal matrices. The approach is first applied on simulated data from recent generation model through an (8×8) simulated electrode matrix, then on real signals using the same grid specifications on the Biceps Brachii. Both simulated and real data were evaluated with three angles of grid alignment with respect to muscle fibers. For this purpose, five parameters were extracted from obtained h2 correlation matrices and tested. According to the obtained results, a relationship between h2 values and the electrode matrix alignment seems to exist. However, further efforts are needed to design parameters more sensitive to grid misalignment with respect to muscle fibers.
The chapter focuses on the basics of biomechanics and asserts that biomechanical principles align well with various areas of engineering. These fields are intertwined, making it challenging to isolate them, and have concurrently led to the advancement of each other. The chapter also defines the distinctions between biomechanics and biomechanical engineering. Additionally, it discusses how technological advancements, from the Renaissance to the modern age, have contributed to a better understanding of human motion. The chapter also delves into contemporary tools and methods extensively utilized in biomechanics.
Objective. To simulate progressive motor neuron loss and collateral reinnervation in motor neuron diseases (MNDs) by developing a dynamic muscle model based on human single motor unit (MU) surface-electromyography (EMG) recordings. Approach. Single MU potentials recorded with high-density surface-EMG from thenar muscles formed the basic building blocks of the model. From the baseline MU pool innervating a muscle, progressive MU loss was simulated by removal of MUs, one-by-one. These removed MUs underwent collateral reinnervation with scenarios varying from 0% to 100%. These scenarios were based on a geometric variable, reflecting the overlap in MU territories using the spatiotemporal profiles of single MUs and a variable reflecting the efficacy of the reinnervation process. For validation, we tailored the model to generate compound muscle action potential (CMAP) scans, which is a promising surface-EMG method for monitoring MND patients. Selected scenarios for reinnervation that matched observed MU enlargements were used to validate the model by comparing markers (including the maximum CMAP and a motor unit number estimate (MUNE)) derived from simulated and recorded CMAP scans in a cohort of 49 MND patients and 22 age-matched healthy controls. Main results. The maximum CMAP at baseline was 8.3 mV (5th–95th percentile: 4.6 mV–11.8 mV). Phase cancellation caused an amplitude drop of 38.9% (5th–95th percentile, 33.0%–45.7%). To match observations, the geometric variable had to be set at 40% and the efficacy variable at 60%–70%. The Δ maximum CMAP between recorded and simulated CMAP scans as a function of fitted MUNE was −0.4 mV (5th–95th percentile = −4.0 – +2.4 mV). Significance. The dynamic muscle model could be used as a platform to train personnel in applying surface-EMG methods prior to their use in clinical care and trials. Moreover, the model may pave the way to compare biomarkers more efficiently, without directly posing unnecessary burden on patients.
Key points summary:
The spinal alpha motoneuron is the only cell in the human CNS whose discharge can be routinely recorded in humans. We have reengineered motor unit collection and decomposition approaches, originally developed in humans, to measure the neural drive to muscle and estimate muscle force generation in the decerebrate cat model. Experimental, computational, and predictive approaches are used to demonstrate the validity of this approach across a wide range of modes to activate the motor pool. The utility of this approach is shown through the ability to track individual motor units across trials, allowing for better predictions of muscle force than the electromyography signal, and providing insights in to the stereotypical discharge characteristics in response to synaptic activation of the motor pool. This approach now allows for a direct link between the intracellular data of single motoneurons, the discharge properties of motoneuron populations, and muscle force generation in the same preparation.
Abstract:
The discharge of a spinal alpha motoneuron and the resulting contraction of its muscle fibers represents the functional quantum of the motor system. Recent advances in the recording and decomposition of the electromyographic signal allows for the identification of several tens of concurrently active motor units. These detailed population data provide the potential to achieve deep insights into the synaptic organization of motor commands. Yet most of our understanding of the synaptic input to motoneurons is derived from intracellular recordings in animal preparations. Thus, it is necessary to extend the new electrode and decomposition methods to recording of motor unit populations in these same preparations. To achieve this goal, we use high-density electrode arrays and decomposition techniques, analogous to those developed for humans, to record and decompose the activity of tens of concurrently active motor units in a hindlimb muscle in the decerebrate cat. Our results showed that the decomposition method in this animal preparation was highly accurate, with conventional two-source validation providing rates of agreement equal to or superior to those found in humans. Multidimensional reconstruction of the motor unit action potential provides the ability to accurately track the same motor unit across multiple contractions. Additionally, correlational analyses demonstrate that the composite spike train provides better estimates of whole muscle force than conventional estimates obtained from the electromyographic signal. Lastly, stark differences are observed between the modes of activation, in particular tendon vibration produced quantal interspike intervals at integer multiples of the vibration period. This article is protected by copyright. All rights reserved.
