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Introduction: It has been shown that, for male subjects, the sEMG activity at low contraction forces is normally "pulsatile", i.e., formed by a few large-amplitude MUPs, coming from the most superficial motor units. The subcutaneous layer thickness, known to be greater in females than males, influences the electrode detection volume. Here, we investigated the influence of the subcutaneous layer thickness on the type of sEMG activity (pulsatile vs. continuous) at low contraction forces. Methods: Voluntary surface EMG signals were recorded from the quadriceps muscles of healthy males and females as force was gradually increased from 0% to 40% MVC. The sEMG filling process was examined by measuring the EMG filling factor, computed from the non-central moments of the rectified sEMG signal. Results: 1) The sEMG activity at low contraction forces was "continuous" in the VL, VM and RF of females, whereas this sEMG activity was "pulsatile" in the VL and VM of males. 2) The filling factor at low contraction forces was lower in males than females for the VL (p = 0.003) and VM (p = 0.002), but not for the RF (p = 0.54). 3) The subcutaneous layer was significantly thicker in females than males for the VL (p = 0.001), VM (p = 0.001), and RF (p = 0.003). 4) A significant correlation was found in the vastus muscles between the subcutaneous layer thickness and the filling factor (p < 0.05). Discussion: The present results indicate that the sEMG activity at low contraction forces in the female quadriceps muscles is "continuous" due to the thick subcutaneous layer of these muscles, which impedes an accurate assessment of the sEMG filling process. [ABSTRACT FROM AUTHOR]

We introduce a novel long-range traffic monitoring system for vehicle detection, tracking, and classification based on fiber-optic distributed acoustic sensing (DAS). High resolution and long range are provided by the use of an optimized setup incorporating pulse compression, which, to our knowledge, is the first time that is applied to a traffic-monitoring DAS system. The raw data acquired with this sensor feeds an automatic vehicle detection and tracking algorithm based on a novel transformed domain that can be regarded as an evolution of the Hough Transform operating with non-binary valued signals. The detection of vehicles is performed by calculating the local maxima in the transformed domain for a given time-distance processing block of the detected signal. Then, an automatic tracking algorithm, which relies on a moving window paradigm, identifies the trajectory of the vehicle. Hence, the output of the tracking stage is a set of trajectories, each of which can be regarded as a vehicle passing event from which a vehicle signature can be extracted. This signature is unique for each vehicle, allowing us to implement a machine-learning algorithm for vehicle classification purposes. The system has been experimentally tested by performing measurements using dark fiber in a telecommunication fiber cable running in a buried conduit along 40 km of a road open to traffic. Excellent results were obtained, with a general classification rate of 97.7% for detecting vehicle passing events and 99.6% and 85.7% for specific car and truck passing events, respectively. [ABSTRACT FROM AUTHOR]

Featured Application: Determination of neuromuscular fatigue threshold in elite cyclists during an incremental test. (1) Background: The aim of this study was to investigate the validity and reliability of surface electromyography (EMG) for automatic detection of the aerobic and anaerobic thresholds during an incremental continuous cycling test using 1 min exercise periods in elite cyclists. (2) Methods: Sixteen well-trained cyclists completed an incremental exercise test (25 W/1 min) to exhaustion. Surface bipolar EMG signals were recorded from the vastus lateralis, vastus medialis, biceps femoris, and gluteus maximus, and the root mean square (RMS) were assessed. The multi-segment linear regression method was used to calculate the first and second EMG thresholds (EMGT1 and EMGT2). During the test, gas exchange data were collected to determine the first and second ventilatory thresholds (VT1 and VT2). (3) Results: Two breakpoints (thresholds) were identified in the RMS EMG vs. time curve for all muscles in 75% of participants. The two breakpoints, EMGT1 and EMGT2, were detected at around 70%–80% and 90%–95% of VO2MAX, respectively. No significant differences were found between the means of VT1 and EMGT1 for the vastii and biceps femoris muscles (p > 0.05). There were no significant differences between means of EMGT2 and VT2 (p > 0.05). (4) Conclusions: It is concluded that the multi-segment linear regression algorithm is a valid non-invasive method for analyzing the aerobic-anaerobic transition during incremental tests with 1 min stage durations. [ABSTRACT FROM AUTHOR]

Inter-discharge interval (IDI) distribution analysis of motor unit firing patterns is a valuable tool in EMG decomposition and analysis. However, the firing pattern obtained by EMG decomposition may have detection errors: false positives (incorrectly classified firings) and false negatives (missed firings). In this paper, the mathematical derivation of an IDI distribution model that accommodates false positives and false negatives of the detection process is presented. An approximation of the general model to adapt to specific EMG decomposition conditions is also presented. To illustrate the usefulness of the model, the obtained distribution is used to derive the maximum likelihood estimates of the statistics of motor unit firing patterns, the IDI mean and standard deviation, and estimates of the false negative and false positive ratios. Results obtained from simulation experiments and tests with real motor unit firing patterns show an enhanced estimation performance when compared to previously available algorithms. Goodness- of-fit tests applied to estimations for real data corrupted with false positives showed that the model-driven estimations fitted the uncorrupted data better than EFE estimations: 82% versus 52% not rejectable, respectively, when false positives were about 10% of IDIs. With about 5% false positives, the not rejectable estimations were 85% versus 70%. [ABSTRACT FROM AUTHOR]

Estimation of motor unit firing pattern statistics is a valuable method in physiological studies and a key procedure in electromyographic (EMG) decomposition algorithms. However, if any firings within the pattern are undetected or missed during the decomposition process, the estimation procedure can be disrupted. In order to provide an optimal solution, we present a maximum likelihood estimator of EMG firing pattern statistics, taking into account that some firings may be undetected. A model of the inter-discharge interval (IDI) probability density function with missing firings has been employed to derive the maximum likelihood estimator of the mean and standard deviation of the IDIs. Actual calculation of the maximum likelihood solution has been obtained by means of numerical optimization. The proposed estimator has been evaluated and compared to other previously developed algorithms by means of simulation experiments and has been tested on real signals. The new estimator was found to be robust and reliable in diverse conditions: IDI distributions with a high coefficient of variance or considerable skewness. Moreover, the proposed estimator outperforms previous algorithms both in simulated and real conditions. [ABSTRACT FROM AUTHOR]

A fundamental aspect of bioelectricity studies is the process by which activation of an excitable cell results in the generation of a transmembrane voltage (the intracellular action potential) and an extracellular electrical potential in the surrounding medium. Traditional methods for teaching how to calculate the potentials do to provide biomedical engineering students with a means to appreciate the progressive nature of the generation of the extracellular potential as the intracellular potential propagates along the fiber. The objective of this paper is to propose a new approach, based on electrostatic theory, to teach students the basics of the formation of the intra- and extra-cellular potential around a fiber. The paper reports on the application and testing of this approach, which is demonstrated to enhance the ability of students to predict the shape (waveform) of the extracellular potential at different electrode positions relative to the fiber. In addition, the new approach helps students to create a mental picture of bioelectrical potentials in the context of the biological structures in which they occur and interact. The paper also emphasizes the necessity of considering the spatial profile of the intracellular potential, in conjunction with its temporal profile, for a correct interpretation of the amplitude and temporal characteristics of extracellular potentials. [ABSTRACT FROM AUTHOR]

Abstract: In situ recording of the intracellular action potential (IAP) of human muscle fibres is not yet feasible, and consequently, knowledge about certain IAP characteristics of these IAPs is still limited. The ratio between the amplitudes of the second and first phases (the so-called peak-to-peak ratio, PPR) of a single fibre action potential (SFAP) is known to be closely related to the IAP profile. The PPR of experimentally recorded SFAPs has been found to be largely independent of changes in the fibre-to-electrode (radial) distance. The main goal of this paper is to analyze the effect of changes in different aspects of the IAP spike on the relationship between PPR and radial distance. Based on this analysis, we hypothesize about the characteristics of IAPs obtained experimentally. It was found that the sensitivity of the SFAP PPR to changes in radial distance is essentially governed by the duration of the IAP spike. Assuming that, for mammals, the duration of the IAP rising phase lies within the range 0.2–0.4ms, we tentatively suggest that the duration of the IAP spike should be over approximately 0.75ms, with the shape of the spike strongly asymmetric. These IAP characteristics broadly coincide with those observed in mammal IAPs. [Copyright &y& Elsevier]

Abstract: In a series of previous works we studied the ratio between the amplitudes of the second and first phases (the peak-to-peak ratio) of single fibre action potential (SFAPs) using the Dimitrov–Dimitrova SFAP convolutional model as a reference. From experimental potentials extracted from both healthy and diseased muscles, we determined typical peak-to-peak ratio (PPR) values and ranges for both normal and pathological conditions. In addition, we investigated the changes observed in the PPR of consecutive potentials recorded at different fibre-to-electrode distances. However, our results were not conclusive due to insufficient data. The objective of the present work was to obtain a more concrete description of the relation between PPR and radial distance. To this end, we recorded 135 sets of consecutive SFAPs from the m. tibialis anterior of four normal subjects. The needle was intentionally moved whilst recording each SFAP set. We found that PPR was largely independent of small changes in electrode position when the electrode was close to the fibre and sufficiently far from the neuromuscular and/or fibre–tendon junctions. In the discussion, we provide evidence that this result is in agreement with the generation of extracellular potentials considering the spatial extension of the intracellular action potential (IAP) along the fibre. [Copyright &y& Elsevier]

A new system is presented that enhances the interoperability between a video-oculographic (VOG) system for mouse movement control and an electromyographic (EMG) system for mouse click detection. The proposed VOG-EMG system combines gaze and muscle information to minimize the number of undesired clicks due to involuntary activations and environmental noise. We tested the system with 24 subjects, comparing three different configurations: one in which the VOG and EMG systems worked independently and two in which we used VOG gaze information to improve the EMG click detection. Results show that the number of false-positive click detections can be reduced when VOG and EMG information is combined. In addition, the third configuration, including extra processing, can reduce the activation delay produced because of the combined use of the VOG and EMG systems. The new VOG-EMG system is meant to be used in noisy environments in which the number of false clicks may impeach a reliable human-computer interaction. [ABSTRACT FROM AUTHOR]

Abstract: In situ recording of the intracellular action potential (IAP) of human muscle fibres is not yet possible, and consequently, knowledge concerning certain IAP characteristics is still limited. According to the core-conductor theory, close to a fibre, a single fibre action potential (SFAP) can be assumed to be proportional to the IAP second derivative. Thus, we might expect to be able to derive some characteristics of the IAP, such as the duration of its spike, from the SFAP waveform. However, SFAP properties not only depend on the IAP shape but also on the fibre-to-electrode (radial) distance and other physiological properties of the fibre. In this paper we, first, propose an SFAP parameter (the negative phase duration, NPD) appropriate for estimating the IAP spike duration and, second, show that this parameter is largely independent of changes in radial distance and muscle fibre propagation velocity. Estimation of the IAP spike duration from a direct measurement taken from the SFAP waveform provides a possible way to enhance the accuracy of SFAP models. Because IAP spike duration is known to be sensitive to the effects of fatigue and calcium accumulation, the proposed SFAP parameter, the NPD, has potential value in electrodiagnosis and as an indicator of IAP profile changes due to peripheral fatigue. [Copyright &y& Elsevier]

Abstract: Using the core-conductor theory, a single fibre action potential (SFAP) can be expressed as the convolution of a biolectrical source and a weight function. In the Dimitrov–Dimitrova (D–D) SFAP convolutional model, the first temporal derivative of the intracellular action potential (IAP) is used as the source. The present work evaluates the relationship between the SFAP peak-to-peak amplitude (V pp) and peak-to-peak interval (rise-time, RT) at different fibre-to-electrode distances using simulated signals obtained by the D–D model as well as real recordings. With a single fibre electrode, we recorded 63 sets of consecutive SFAPs from the m. tibialis anterior of four normal subjects. The needle was intentionally moved whilst recording each SFAP set. We used the observed changes in RT and V pp within each SFAP set as a point of reference with which to evaluate how closely the relationship between RT and V pp provided by the D–D model reflects real data. We found that half of the recorded SFAP sets had rise-times higher than those generated by the D–D model. We also showed the influence of the IAP spatial length on the sensitivity of RT and V pp with radial distance. The study reveals some inaccuracies in simulated SFAPs whose origin might be related to the assumptions made in the core-conductor theory. [ABSTRACT FROM AUTHOR]

In Electromyography studies, the motor unit is considered as the anatomical und functional unit responsible of the electrical activity related to the contraction of the skeletal muscle. This paper is aimed at showing biomedical engineering master students how to model and study the electrical potentials produced by the activation of the motor unit. The proposed model is based on a mathematical concept familiar to engineers, the convolution. By using computer simulations based on this model, the effects of changes in the motor unit parameters on the characteristics of generated electrical signal are illustrated. The paper is useful in showing the students how to identify the different aspects involved in the analysis of biological phenomena. [ABSTRACT FROM AUTHOR]

An innovative way of teaching introductory circuit theory to higher education first courses of nonelectrical engineering students arises from our own teaching experience. In these students' learning programme, circuit theory is located at the very early stages (first or second semester, when the student is still not too skilled on maths). Fewer credits are being devoted to it, since it is viewed as an introductory subject, a precursor to subsequent systems theory and electronics. In this paper we wish to encourage teachers to give up the classical approach to circuits and replace it with the proposed Laplace transform approach which, remembering A. Einstein's sentence,' Everything should be made as simple as possible' allows circuit theory to be made much simpler. Perhaps, this attitude could grow into a text book, definitively new and different, intended for teaching the basics of circuits to first courses of non-electrical engineering students. [ABSTRACT FROM AUTHOR]

Recently, a new method has been proposed to detect the onset of neuromuscular fatigue during an incremental cycling test by assessing the changes in spectral electromyographic (sEMG) frequencies within individual exercise periods of the test. The method consists on determining the highest power output that can be sustained without a significant decrease in spectral frequencies. This study evaluated the validity of the new approach by assessing the changes in spectral indicators both throughout the whole test and within individual exercise periods of the test. Fourteen cyclists performed incremental cycle ergometer rides to exhaustion with bipolar surface EMG signals recorded from the vastus lateralis. The mean and median frequencies (Fmean and Fmedian, respectively) of the sEMG power spectrum were calculated. The main findings were: (1) Examination of spectral indicators within individual exercise periods of the test showed that neither Fmean nor Fmedian decreased significantly during the last (most fatiguing) exercise periods. (2) Examination of the whole incremental test showed that the behaviour of Fmean and Fmedian with increasing power output was highly inconsistent and varied greatly among subjects. (3) Over the whole incremental test, half of the participants exhibited a positive relation between spectral indicators and workload, whereas the other half demonstrated the opposite behavior. Collectively, these findings indicate that spectral sEMG indexes do not provide a reliable measure of the fatigue state of the muscle during an incremental cycling test. Moreover, it is concluded that it is not possible to determine the onset of neuromuscular fatigue during an incremental cycling test by examining spectral indicators within individual exercise periods of the test. [ABSTRACT FROM AUTHOR]

Abstract: In a previous work we studied the ratio between the amplitudes of the second and first phases (which we call PPR, after peak-to-peak ratio) of the single fibre action potential (SFAP) for a collection of fibrillation potentials (FPs) extracted from two pathological muscles. These FPs showed a wider PPR range than the Dimitrov–Dimitrova (D–D) convolutional model could provide. We proposed a modification of the D–D intracellular action potential (IAP) in order to obtain a range of PPRs comparable to that observed in our FPs. This paper extends that study to a large number of SFAPs extracted from the tibialis anterior muscle of normal subjects. The estimation of the average PPR range of non-diseased muscles in non-fatigued conditions is important since it can be used as a reference to establish a comparison with PPR ranges from muscles suffering some disorder or from fibres that are fatigued. Other aspects of the PPR, as its sensitivity with volume conductor parameters or to what extent changes in the SFAP PPR reflects changes in IAP spatial profile are also examined. We found that the PPR of experimental SFAPs ranges from 0.3 to 2.5 in all subjects and that all PPR histograms contain a well-defined single peak around the PPR value 1.0. [ABSTRACT FROM AUTHOR]

The Dimitrov-Dimitrova (D-D) model generates a single fibre action potential (SFAP) as the convolution of an excitation function and a filter impulse function. We propose a method to estimate the parameters involved in these functions from a SFAP waveform (inverse problem) and call it Identification Procedure. The Identification Procedure comprises two parts. The present paper, Part I, is centred on the estimation of the radial distance, r, and the fibre diameter, d, of a given SFAP. To this end we develop a technique which we call the candidate pair method (CP-method), and we test it on fibrillation potentials (FPs) as experimental data. We found that the D-D model cannot synthesize all the SFAP waveforms observed in the experimental recordings, but in the cases where it can, the CP-method then provides the values of r and d that are more likely to have synthesized the SFAP. Having a method that provides information about the fibre diameter straight from a SFAP waveform is very desirable as this parameter has clinical and physiological relevance. Moreover, the CP-method plays a major role in the Identification Procedure that is carried out in Part II. [ABSTRACT FROM AUTHOR]

The present paper describes a global procedure for estimating all the synthesis parameters that generate a single fibre action potential (SFAP) in the Dimitrov-Dimitrova (D-D) convolutional model. We call this inverse problem Identification Procedure, and it is presented in two parts, this paper being the second. The procedure incorporates the candidate pair (CP) method developed in Part I, which provides the values of radial distance r and fibre diameter d of the simulated SFAP that best matches a potential under study. The CP-method required prior knowledge of all the excitation parameters. However, since the Identification Procedure makes no assumption about the excitation, multiple combinations of the synthesis parameters result in very similar SFAPs whose shape is close the signal under study. Analysis of the possible combinations reveals that r and d can be modelled as two jointly Gaussian random variables. The interest of the Identification Procedure is that, for a certain SFAP, it provides estimates of r and d, along with estimates of different parameters that determine the IAP waveform. Moreover, the procedure is able to determine the degree of error that accompanies the estimation of r and d. [ABSTRACT FROM AUTHOR]

EMG filling curve characterizes the EMG filling process and EMG probability density function (PDF) shape change for the entire force range of a muscle.We aim to understand the relation between the physiological and recording variables, and the resulting EMG filling curves. We thereby present an analytical and simulation study to explain how the filling curve patterns relate to specific changes in the motor unit potential (MUP) waveforms and motor unit (MU) firing rates, the two main factors affecting the EMG PDF, but also to recording conditions in terms of noise level. We compare the analytical results with simulated cases verifying a perfect agreement with the analytical model. Finally, we present a set of real EMG filling curves with distinct patterns to explain the information about MUP amplitudes, MU firing rates, and noise level that these patterns provide in the light of the analytical study. Our findings reflect that the filling factor increases when firing rate increases or when newly recruited motor unit have potentials of smaller or equal amplitude than the former ones. On the other hand, the filling factor decreases when newly recruited potentials are larger in amplitude than the previous potentials. Filling curves are shown to be consistent under changes of the MUP waveform, and stretched under MUP amplitude scaling. Our findings also show how additive noise affects the filling curve and can even impede to obtain reliable information from the EMG PDF statistics.

An analytical derivation of the EMG signal's amplitude probability density function (EMG PDF) is presented and used to study how an EMG signal builds-up, or fills, as the degree of muscle contraction increases. The EMG PDF is found to change from a semi-degenerate distribution to a Laplacian-like distribution and finally to a Gaussian-like distribution.We present a measure, the EMG filling factor, to quantify the degree to which an EMG signal has been built-up. This factor is calculated from the ratio of two non-central moments of the rectified EMG signal. The curve of the EMG filling factor as a function of the mean rectified amplitude shows a progressive and mostly linear increase during early recruitment, and saturation is observed when the EMG signal distribution becomes approximately Gaussian. Having presented the analytical tools used to derive the EMG PDF, we demonstrate the usefulness of the EMG filling factor and curve in studies with both simulated signals and real signals obtained from the tibialis anterior muscle of 10 subjects. Both simulated and real EMG filling curves start within the 0.2 to 0.35 range and rapidly rise towards 0.5 (Laplacian) before stabilizing at around 0.637 (Gaussian). Filling curves for the real signals consistently followed this pattern (100% repeatability within trials in 100% of the subjects). The theory of EMG signal filling derived in this work provides (a) an analytically consistent derivation of the EMG PDF as a function of motor unit potentials and motor unit firing patterns; (b) an explanation of the change in the EMG PDF according to degree of muscle contraction; and (c) a way (the EMG filling factor) to quantify the degree to which an EMG signal has been built-up.

Motor unit layout algorithms have a significant effect on motor unit fibre densities recorded. Motor unit fibre densities are affected by both the method used to place the motor unit territories, and the mechanism by which muscle fibres are assigned to motor units. The first of these should emulate the process by which separate motor neurons create overlapping territories that cover the muscle cross section, while the second should have some relation to the processes involved with axonal arborization and development of the spatial dispersion of the neuro-muscular junctions. The success of an algorithm in creating physiologically realistic motor unit layouts may be evaluated, in part, by examining the distribution of the muscle fibres assigned to the motor units. This paper examines the motor unit fibre densities found in muscles created by two recent algorithms, and explores the degree to which the concepts used by these algorithms may be shared.

Modeling of muscle architecture, which aims to recreate mathematically the physiological structure of the muscle fibers and motor units, is a powerful tool for understanding and modeling the mechanical and electrical behavior of the muscle. Most of the published models are presented in the form of algorithms, without mathematical analysis of mechanisms or outcomes of the model. Through the study of the muscle architecture model proposed by Stashuk, we present the analytical tools needed to better understand these models. We provide a statistical description for the spatial relations between motor units and muscle fibers. We are particularly concerned with two physiological quantities: the motor unit fiber number, which we expect to be proportional to the motor unit territory area; and the motor unit fiber density, which we expect to be constant for all motor units. Our results indicate that the Stashuk model is in good agreement with the physiological evidence in terms of the expectations outlined above. However, the resulting variance is very high. In addition, a considerable 'edge effect' is present in the outer zone of the muscle cross-section, making the properties of the motor units dependent on their location. This effect is relevant when motor unit territories and muscle cross-section are of similar size.

The aim of this work is to present and evaluate a new algorithm, based on the wavelet transform, for the automatic measurement of motor unit action potential (MUAP) duration. A total of 240 MUAPs were studied. The waveform of each MUAP was wavelet-transformed, and the start and end points were estimated by regarding the maxima and minima points in a particular scale of the wavelet transform. The results of the new method were compared to the gold standard of duration marker positions obtained by manual measurement. The new method was also compared to a conventional algorithm, which we had found to be best in a previous comparative study. To evaluate the new method against manual measurements, the dispersion of automatic and manual duration markers were analyzed in a set of 19 repeatedly recorded MUAPs. The differences between the new algorithm's marker positions and the gold standard of duration marker positions were smaller than those observed with the conventional method. The dispersion of the new algorithm's marker positions was slightly less than that of the manual one. Our new method for automatic measurement of MUAP duration is more accurate than other available algorithms and more consistent than manual measurements.

The aim of this work is to analyze the variability in manual measurements of motor unit action potential (MUAP) duration and to evaluate the effectiveness of well-known algorithms for automatic measurement. Two electromyographists carried out three independent duration measurements of a set of 240 MUAPs. The intraexaminer and interexaminer variabilities were analyzed by means of the Gage Reproducibility and Repeatability method. The mean of the three closest manually marked positions was considered the gold standard of the duration markers positions (GSP). The results of four well-known automatic methods for estimating MUAP duration were compared to the GSP. Manual measurements of duration showed a lot of variability, with the combined intraoperator and interoperator variability greater than 30%. The greatest difference between manual positions was 11.2 ms. The mean differences between the GSP and those obtained with the four automatic methods ranged between 0.6 and 8.5 ms. Both manual and automatic measurements of MUAP duration show a high degree of variability. More precise methods are needed to improve the accuracy and reliability of the estimates of this parameter.