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The influence of large vessels on near infrared spectroscopy (NIRS) measurement is generally considered negligible. Aim of this study is to test the hypothesis that changes in the vessel size, by varying the amount of absorbed NIR light, could profoundly affect NIRS blood volume indexes. Changes in haemoglobin concentration (tHb) and in tissue haemoglobin index (THI) were monitored over the basilic vein (BV) and over the biceps muscle belly, in 11 subjects (7 M – 4 F; age 31 ± 8 year) with simultaneous ultrasound monitoring of BV size. The arm was subjected to venous occlusion, according to two pressure profiles: slow (from 0 to 60 mmHg in 135 s) and rapid (0 to 40 mmHg maintained for 30 s). Both tHb and THI detected a larger blood volume increase (1.7 to 4 fold; p

Objectives Changes in pupil size are governed by the autonomic nervous system but may be systematically driven by voluntary shifting the gaze in depth. Thus, the pupil accommodative response (PAR) that accompanies voluntary gaze shifts from a far to a near target might be exploited as a simple human-computer interface (HCI), bypassing the somato-motor system. Here we aim to characterize PAR in quasi-natural conditions with low-cost equipment and test the possibility to use PAR as a binary communication tool. Methods Nineteen healthy subjects were instructed to voluntary switch the focus from a far to a near target upon presentation of an auditory cue. Three protocols addressed the effects of monocular/binocular vision, eye illuminance, duration of near vision, target texture and target brightness on PAR features. In a fourth protocol PAR was used to establish binary communication at different bit rates. Results PAR amplitude decreased with increasing eye illuminance and was modulated by monocular/binocular vision, duration of near vision or target texture. PAR amplitude was larger with a bright near target and a dark far target than vice-versa. However, PAR was always clearly present, regardless of the experimental manipulations. PAR-based communication performance achieved an accuracy of 100% at 10 bits/min and 96% at 15 bits/min. Significance Voluntary PAR is a robust signal, and can achieve a high communication speed when used as an HCI. This study provides a proof of concept for a PAR-based HCI, potentially useful to communicate with locked-in patients with preserved visual and autonomic functions.

The herniation of cerebellum through the foramen magnum may block the normal flow of cerebrospinal fluid determining a severe disorder called Chiari I Malformation (CM-I). Different surgical options are available to help patients, but there is no standard to select the optimal treatment. This paper proposes a fully automated method to select the optimal intervention. It is based on morphological parameters of the brain, posterior fossa and cerebellum, estimated by processing sagittal magnetic resonance images (MRI). The processing algorithm is based on a non-rigid registration by a balanced multi-image generalization of demons method. Moreover, a post-processing based on active contour was used to improve the estimation of cerebellar hernia. This method allowed to delineate the boundaries of the regions of interest with a percentage of agreement with the delineation of an expert of about 85%. Different features characterizing the estimated regions were then extracted and used to develop a classifier to identify the optimal surgical treatment. Classification accuracy on a database of 50 patients was about 92%, with a predictive value of 88% (tested with a leave-one-out approach).

A new approach is introduced for non-rigid registration of a pair of magnetic resonance images (MRI). It is a generalization of the demons algorithm with low computational cost, based on local information augmentation (by integrating multiple images) and balanced implementation. Specifically, a single deformation that best registers more pairs of images is estimated. All these images are extracted by applying different operators to the two original ones, processing local neighbors of each pixel. The following five images were found to be appropriate for MRI registration: the raw image and those obtained by contrast-limited adaptive histogram equalization, local median, local entropy and phase symmetry. Thus, each local point in the images is supplemented by augmented information coming by processing its neighbor. Moreover, image pairs are processed in alternation for each iteration of the algorithm (in a balanced way), computing both a forward and a backward registration. The new method (called balanced multi-image demons) is tested on sagittal MRIs from 10 patients, both in simulated and experimental conditions, improving the performances over the classical demons approach with minimal increase of the computational cost (processing time around twice that of standard demons). Specifically, a simulated deformation was applied to the MRIs (either original or corrupted by additive Gaussian or speckle noises). In all tested cases, the new algorithm improved the estimation of the simulated deformation (squared estimation error decreased by about 65% in the average). Moreover, statistically significant improvements were obtained in experimental tests, in which different brain regions (i.e., brain, posterior fossa and cerebellum) were identified by the atlas approach and compared to those manually delineated (in the average, Dice coefficient increased of about 6%). The conclusion is that a balanced method applied to multiple information extracted from neighboring pixels is a low cost approach to improve registration of MRIs.

The pulsatility of the inferior vena cava (IVC) reflects the volume status of patients. It can be investigated by ultrasounds (US), offering an important non-invasive tool supporting fluid management. However, the method has limitations attributable to many confounding factors, e.g., related to IVC movements and non-regular shapes. Short- or long-axis views have been used, both having advantages and limitations in counteracting such confounding factors, depending on the specific condition. The aim of this study is to investigate IVC pulsatility in the different directions on the transverse plane and to assess its variability. Moreover, different components of this pulsatility (induced by either respiratory or cardiac activity) are investigated. The method is tested on 10 healthy patients, with large variations across them of IVC section (mean diameters in the range 1 cm to 3 cm), shape and pulsatility (average caval index [CI] ranging from approximately 20% to 70%). The average coefficient of variation of the CI estimated on 10 different directions was 13% (21% and 20% for the respiratory and cardiac components, respectively), with a range that was approximately 50% of the mean CI across different directions (approximately the same for the 2 different components). The minimum and maximum CI were found close to the directions of maximum and minimum IVC diameter, respectively. The investigation of IVC dynamics in the entire cross-section is crucial to obtain a more repeatable and reliable characterization of IVC pulsatility. The calculation of a CI based on the "equivalent" diameter (proportional to the square root of the IVC cross-sectional area) is encouraged.

Slow biphasic complexes (SBC) have been identified in the EEG of patients suffering for inflammatory brain diseases. Their amplitude, location and frequency of appearance were found to correlate with the severity of encephalitis. Other characteristics of SBCs and of EEG traces of patients could reflect the grade of pathology. Here, EEG rhythms are investigated together with SBCs for a better characterization of encephalitis. EEGs have been acquired from pediatric patients: ten controls and ten encephalitic patients. They were split by neurologists into five classes of different severity of the pathology. The relative power of EEG rhythms was found to change significantly in EEGs labeled with different severity scores. Moreover, a significant variation was found in the last seconds before the appearance of an SBC. This information and quantitative indexes characterizing the SBCs were used to build a binary classification decision tree able to identify the classes of severity. True classification rate of the best model was 76.1% (73.5% with leave-one-out test). Moreover, the classification errors were among classes with similar severity scores (precision higher than 80% was achieved considering three instead of five classes). Our classification method may be a promising supporting tool for clinicians to diagnose, assess and make the follow-up of patients with encephalitis.

Background In clinical practice, as stated in the ASE guidelines, the echocardiographic estimation of right atrial pressure (RAP) is based on the size of the inferior vena cava (IVC) and its inspiratory collapse. However, this method has proven to have limits of reliability and reproducibility. The use of a recently developed software that with a semi-automatic technique highlight the edges of the IVC could help to standardize the echocardiographic assessment of RAP. Aim of the study: The aim of the study was to assess feasibility and accuracy of a new semi-automated approach to estimate the RAP. Standard acquired echocardiographic images were processed with a semi-automatic technique, indexes related to the collapsibility of the vessel during inspiration (Caval Index, CI), during the whole respiratory cycle (Respiratory Caval Index, RCI) and through the heart cycle transmitted movements’ (Cardiac Caval Index (CCI) were derived (figure 1). Using these indexes, we developed two models: a) the Binary Tree Model (BTM), further divided in BTM3 and BTM5 (RAP estimated in 3 and 5 classes, respectively); b) the Regression Model (RM), further divided in RM linear (continuous model) and RM3 and RM5 (RAP estimated in 3 and 5 classes respectively). RAP assessed using these innovative techniques were compared with two standard estimation (SE) echocardiographic methods A and B. Direct RAP measurements obtained during a right heart catheterization (RHC), performed within 6 hours, were used as reference. Results 62 consecutive ‘all-comers’ patients that had a RHC were enrolled; 13 patients were excluded for technical reasons. Therefore 49 patients were included in this study (26 males and 23 females; mean age of 62.2 ± 15.2 years, 75.5% pulmonary hypertension, 34.7% severe left ventricular dysfunction and 51% right ventricular dysfunction). The two SE methods showed poor accuracy for RAP estimation (method A: ME = 51%, R2= 0.22; method B: ME = 69%, R2= 0.26). Instead, the new semi-automatic methods BTM3 and BTM5 based on parameters derived from IVC edge tracking (mean IVC diameter, CI, CCI and RCI) had a misclassification error of only 14% (R2 = 0.47) and 22% (R2 = 0.61), respectively, to classify RAP. The accuracy was lower for RM than BTM (RM3: ME = 61%, R2 = 0.39; RM5: ME = 55%, R2 = 0.39). However, the RM showed the lowest mean bias in estimating RAP: 0.23 [-8.34; 8.81] mmHg. Conclusions A multi-parametric approach using the new indexes, such as CCI and RCI, derived from a semi-automated edge tracking of the IVC is a promising tool for a more accurate estimation of RAP. This study proposes an innovative method for the non-invasive estimation of the RAP, which requires confirmation on larger population. Abstract P892 Figure 1

The echocardiographic estimation of right atrial pressure (RAP) is based on the size and inspiratory collapse of the inferior vena cava (IVC). However, this method has proven to have limits of reliability. The aim of this study is to assess feasibility and accuracy of a new semi-automated approach to estimate RAP. Standard acquired echocardiographic images were processed with a semi-automated technique. Indexes related to the collapsibility of the vessel during inspiration (Caval Index, CI) and new indexes of pulsatility, obtained considering only the stimulation due to either respiration (Respiratory Caval Index, RCI) or heartbeats (Cardiac Caval Index, CCI) were derived. Binary Tree Models (BTM) were then developed to estimate either 3 or 5 RAP classes (BTM3 and BTM5) using indexes estimated by the semi-automated technique. These BTMs were compared with two standard estimation (SE) echocardiographic methods, indicated as A and B, distinguishing among 3 and 5 RAP classes, respectively. Direct RAP measurements obtained during a right heart catheterization (RHC) were used as reference. 62 consecutive ‘all-comers’ patients that had a RHC were enrolled; 13 patients were excluded for technical reasons. Therefore 49 patients were included in this study (mean age 62.2 ± 15.2 years, 75.5% pulmonary hypertension, 34.7% severe left ventricular dysfunction and 51% right ventricular dysfunction). The SE methods showed poor accuracy for RAP estimation (method A: misclassification error, ME = 51%, R2 = 0.22; method B: ME = 69%, R2 = 0.26). Instead, the new semi-automated methods BTM3 and BTM5 have higher accuracy (ME = 14%, R2 = 0.47 and ME = 22%, R2 = 0.61, respectively). In conclusion, a multi-parametric approach using IVC indexes extracted by the semi-automated approach is a promising tool for a more accurate estimation of RAP.

Assessment of volume status is important to correctly plan the treatment of patients admitted and managed by cardiology, emergency and internal medicine departments. Non-invasive assessment of volume status by echography of the inferior vena cava (IVC) is a promising possibility, but its clinical use is limited by poor reproducibility of current standard procedures. We have developed new algorithms to extract reliable information from non-invasive IVC monitoring by ultrasound (US) imaging. Both long and short axis US B-mode video-clips were taken from 50 patients, in either hypo-, eu-, or hyper-volemic conditions. The video-clips were processed to extract static and dynamic indexes characterizing the IVC behaviour. Different binary tree models (BTM) were developed to identify patient conditions on the basis of those indexes. The best classifier was a BTM using IVC pulsatility indexes as input features. Its accuracy (78.0% when tested with a leave-one-out approach) is superior to that achieved using indexes measured by the standard clinical method from M-mode US recordings. These results were obtained with patients in conditions of normal respiratory function and cardiac rhythm. Further studies are necessary to extend this approach to patients with more complex cardio-respiratory conditions.

The electroencephalogram (EEG) of patients suffering from inflammatory diseases of the brain may show specific waveforms called slow biphasic complexes (SBC). Recent studies indicated a correlation between the severity of encephalitis and some features of SBCs, such as location, amplitude and frequency of appearance. Moreover, EEG rhythms were found to vary before the onset of an SBC, as if the brain was preparing to the discharge (actually with a slowing down of the EEG oscillation). Here, we investigate possible variations of EEG functional connectivity (FC) in EEGs from pediatric patients with different levels of severity of encephalitis. FC was measured by the maximal crosscorrelation of EEG rhythms in different bipolar channels. Then, the indexes of network patterns (namely strength, clustering coefficient, efficiency and characteristic path length) were estimated to characterize the global behavior when they are measured during SBCs or far from them. EEG traces showed statistical differences in the two conditions: clustering coefficient, efficiency and strength are higher close to an SBC, whereas the characteristic path length is lower. Moreover, for more severe conditions, an increase in clustering coefficient, efficiency and strength and a decrease in characteristic path length were observed in the delta–theta band. These outcomes support the hypothesis that SBCs result from the anomalous coordination of neurons in different brain areas affected by the inflammation process and indicate FC as an additional key for interpreting the EEG in encephalitis patients.

Objectives Respirophasic variation of inferior vena cava (IVC) size is affected by large variability with spontaneous breathing. This study aims at characterizing the dependence of IVC size on controlled changes in intrathoracic pressure. Methods Ten healthy subjects, in supine position, performed controlled isovolumetric respiratory efforts at functional residual capacity, attaining positive (5, 10, and 15 mmHg) and negative (−5, −10, and −15 mmHg) alveolar pressure levels. The isovolumetric constraint implies that equivalent changes are exhibited by alveolar and intrathoracic pressures during respiratory tasks. Results The IVC cross-sectional area equal to 2.88 ± 0.43 cm2 at baseline (alveolar pressure = 0 mmHg) was progressively decreased by both expiratory and inspiratory efforts of increasing strength, with diaphragmatic efforts producing larger effects than thoracic ones: −55 ± 15% decrease, at +15 mmHg of alveolar pressure (P

Chiari I Malformation (CM-I) is a disorder characterized by herniation of the cerebellar tonsils through the foramen magnum. The choice of the optimal surgical management of CM-I is still an open problem, as there are no guidelines for the most suitable approach in symptomatic patients. We assessed the possibility of predicting the optimal intervention on the basis of morphological properties of the brain, posterior fossa and cerebellum. The boundaries of these regions were estimated by non-rigid registration of test sagittal magnetic resonance images (MRI) over an atlas. Different features characterizing the estimated regions were extracted and used to develop Naive Bayes classifiers. Classification was tested on a database of 30 patients, which were either healthy or pathological, with either mild or severe manifestation of CM-I. The best cross-validated classifier selected input features related to the shape and relative dimension of different brain regions (specifically, cerebellum and posterior fossa), the possible presence and dimension of the hernia and the regularity of the boundary of the cerebellum. The best classification accuracy (tested with a leave-one-out approach) was about 83%. These promising results suggest investigating further the possibility of defining the surgical treatment of CM-I on the basis of morphometric parameters from sagittal MRIs.

Inflammatory brain diseases have been associated to the presence of slow biphasic complexes (SBC)in the EEG. An automated method has been developed to identify them. A dataset of 128 EEGs was recorded from pediatric controls and patients showing encephalitis with different levels of severity. Experts assigned a severity score with 5 levels to each trace, considering both electrophysiological and clinical manifestations. The number, amplitude and location of SBCs were used to identify automatically the severity scores using a binary classification decision tree. True classifications have been obtained in the 64.1 % of cases (55.6% using a leave-one-out approach)and misclassifications were among close severity scores (about 80 % of accuracy was obtained considering 3 instead of 5 severity scores), indicating that SBCs may support the identification, assessment and follow-up of encephalitis.

Pulsatility of the inferior vena cava (IVC) provides information on volume status in healthy subjects and in many clinical conditions. The ultrasound (US) approach to estimating the caval index (CI) is not standardized, as it is operator dependent and vulnerable to measurement errors because of different factors, including movements of the IVC and non-uniform IVC pulsatility along its longitudinal axis. We propose and test in healthy subjects an innovative automated approach, which tracks the IVC movements registered in a B-mode US video clip and estimates the pulsatility of an entire portion of the vein rather than of a single arbitrary section. Large variations in CI estimates were observed along the longitudinal axis (in the worst case, CI ranged between 15% and 60%), indicating the importance of investigating a whole portion of the vessel.

The pulsatility of the inferior vena cava (IVC) reflects the volume status and central venous pressure of patients. The standard clinical indicator of IVC pulsatility is the caval index (CI), measured from ultrasound recordings. However, its estimation is not standardized and is vulnerable to artifacts, mostly because of IVC movements during respiration. Thus, we used a (recently patented) semi-automated method that tracks IVC movements and averages the CI across an entire section of the vein, which provides a more stable indication of pulsatility. This algorithm was used to estimate the CI, pulsatility indicators reflecting either respiratory or cardiac stimulation and the mean diameter of the IVC. These IVC indices, together with anthropometric information, were used as potential features to build an innovative model for the estimation of the right atrial pressure (RAP) recorded from 49 catheterized patients. An exhaustive search was carried out for the best among all possible models that could be obtained by using combinations of these features. The model with minimum estimation error (tested with a leave-one-out approach) was selected. This model estimated RAP with an error of about 3.6 ± 2.6 mm Hg (mean ± standard deviation); the error when using only operator measured variables, without software, was about 4.0 ± 2.5 mm Hg. These promising results underline the need for further study of our RAP estimation method on a larger data set.

The inferior vena cava (IVC) shows variations of cross section over time (pulsatility) induced by different stimulations (e.g., breathing and heartbeats). Pulsatility is affected by patients’ volume status and can be investigated by ultrasound (US) measurements. An index of IVC pulsatility based on US visualization and called caval index (CI) was proposed as a non-invasive indirect measurement of the volume status. However, its estimation is not standardized, operator dependent and affected by movements of the vein and non-uniform pulsatility. We introduced a software that processes B-mode US video clips to track IVC movements and estimate CI on an entire portion of the vein. This method is here compared to the standard approach in terms of repeatability of the estimated CI, reporting on the variability over different respiratory cycles, longitudinal IVC sections and intra-/inter-observers. Our method allows to reduce the variability of CI assessment, making a step toward its standardization.

Anatomical studies on the external anal sphincter (EAS) indicate that superficial muscle fibres are circular at low depth within the anal canal. A more complex geometry of the fibres is documented for increasing depth within the muscle and along the anal canal. Monopolar intra-anal EMG signals recorded using an array of electrodes placed in circular direction have no common mode components if the muscle fibres are circular, with constant depth within the muscle and parallel to the detection array. Thus, the presence of common mode signals may provide indications about the geometry of muscle fibres of EAS. Intra-anal EMG signals were recorded from EAS of 12 subjects using an anal probe carrying three circumferential arrays of 16 electrodes at three depths within the anal canal. Contribution of common mode components in single MUAPs was lower for MUs located superficially in the muscle (Pearson correlation coefficient: R=-0.75, p≪0.001) and at a lower depth within the anal canal (non-parametric one way Kruskal-Wallis ANOVA, Χ=17.3, p

This work investigated motor unit (MU) recruitment during transcutaneous electrical stimulation (TES) of the tibialis anterior (TA) muscle, using experimental and simulated data. Surface electromyogram (EMG) and torque were measured during electrically-elicited contractions at different current intensities, on eight healthy subjects. EMG detected during stimulation (M-wave) was simulated selecting the elicited MUs on the basis of: (a) the simulated current density distribution in the territory of each MU and (b) the excitation threshold characteristic of the MU. Exerted force was simulated by adding the contribution of each of the elicited MUs. The effects of different fat layer thickness (between 2 and 8mm), different distributions of excitation thresholds (random excitation threshold, higher threshold for larger MUs or smaller MUs), and different MU distributions within the muscle (random distribution, larger MU deeper in the muscle, smaller MU deeper) on EMG variables and torque were tested. Increase of the current intensity led to a first rapid increase of experimental M-wave amplitude, followed by a plateau. Further increases of the stimulation current determined an increase of the exerted force, without relevant changes of the M-wave. Similar results were obtained in simulations. Rate of change of conduction velocity (CV) and leading coefficient of the second order polynomial interpolating the force vs. stimulation level curve were estimated as a function of increasing current amplitudes. Experimental data showed an increase of estimated CV with increasing levels of the stimulation current (for all subjects) and a positive leading coefficient of force vs. stimulation current curve (for five of eight subjects). Simulations matched the experimental results only when larger MUs were preferably located deeper in the TA muscle (in line with a histochemical study). Marginal effect of MU excitation thresholds was observed, suggesting that MUs closer to the stimulation electrode are recruited first during TES regardless of their excitability.

The detection of surface electromyogram (EMG) by multi-electrode systems is applied in many research studies. The signal is usually recorded by means of spatial filters (linear combination of the potential under at least two electrodes) with vanishing sum of weights. Nevertheless, more information could be extracted from monopolar signals measured with respect to a reference electrode away from the muscle. Under certain conditions, surface EMG signal along a curve parallel to the fibre path has zero mean (property approximately satisfied when EMG is sampled by an array of electrodes that covers the entire support of the signal in space). This property allows estimating monopolar from single differential (SD) signals by pseudoinversion of the matrix relating monopolar to SD signals. The method applies to EMG signals from the external anal sphincter muscle, recorded using a specific cylindrical probe with an array of electrodes located along the circular path of the fibres. The performance of the algorithm for the estimation of monopolar from SD signals is tested on simulated signals. The estimation error of monopolar signals decreases by increasing the number of channels. Using at least 12 electrodes, the estimation error is negligible. The method applies to single fibre action potentials, single motor unit action potentials, and interference signals. The same method can also be applied to reduce common mode interference from SD signals from muscles with rectilinear fibres. In this case, the last SD channel defined as the difference between the potentials of the last and the first electrodes must be recorded, so that the sum of all the SD signals vanishes. The SD signals estimated from the double differential signals by pseudoinvertion are free of common mode.

Quantifying muscle force and fatigue is important in designing ergonomic work stations, in planning appropriate work-rest patterns, and in preventing/assessing the progress of disorders. In 14 subjects (seven males, seven females), muscle force and fatigue were estimated by subjective perception (based on Borg scale CR10) and objective indexes extracted from surface electromyogram (EMG). The experimental protocol consisted of an isometric task selective for the upper trapezius muscle at different force levels (10-80% of maximal voluntary contraction--MVC, in steps of 10%MVC) and one fatiguing contraction (constant force level at 50%MVC until exhaustion). Surface EMG signals were detected by a two-dimensional (2D) array of electrodes placed half way between C7 and the acromion. The following variables were calculated from EMG signals: muscle fibre conduction velocity (CV), root mean square value (RMS), mean frequency of the power spectrum (MNF), fractal dimension (FD), and entropy. All detected signals were also used to build topographical maps of RMS. Both subjective and objective indications of force and fatigue can provide information on exerted force and endurance time (ET). In particular, Borg ratings, RMS, and entropy were significantly related to force, and the rate of change of CV, MNF, FD, and Borg ratings were predictive of the endurance time. Moreover, significant differences were found in Borg ratings between males and females. The correlation coefficient of pairs of topographical maps of RMS was high (of the order of 0.8). This reflects a characteristic spatial-temporal recruitment of upper trapezius motor units that is not affected by force levels or fatigue.

This study analytically describes surface electromyogram (EMG) signals generated by a planar multilayer volume conductor constituted by different subdomains modeling muscle, bone (or blood vessel), fat, and skin tissues. The bone is cylindrical in shape, with a semicircular section. The flat portion of the boundary of the bone subdomain is interfaced with the fat layer tissue, the remaining part of the boundary is in contact with the muscle layer. The volume conductor is a model of physiological tissues in which the bone is superficial, as in the case of the tibia bone, backbone, and bones of the forearm. The muscle fibers are considered parallel to the axes of the bone, so that the model is space invariant in the direction of propagation of the action potential. The proposed model, being analytical, allows faster simulations of surface EMG with respect to previously developed models including bone or blood vessels based on the finite-element method. Surface EMG signals are studied by simulating a library of single-fiber action potentials (SFAP) of fibers in different locations within the muscle domain, simulating the generation, propagation, and extinction of the action potential. The decay of the amplitude of the SFAPs in the direction transversal to the fibers is assessed. The decay in the direction of the bone has a lower rate with respect to the opposite direction. Similar results are obtained by simulating motor unit action potentials (MUAPs) constituted by 100 fibers with territory 5 mm2. M waves and interference EMG signals are also simulated based on the library of SFAPs. Again, the decay of the amplitude of the simulated interference EMG signals is lower approaching the bone with respect to going farther from it. The findings of this study indicate the effect of a superficial bone in enhancing the EMG signals in the transversal direction with respect to the fibers of the considered muscle. This increases the effect of crosstalk. The same mathematical method used to simulate a superficial bone can be applied to simulate other physiological tissues. For example, superficial blood vessels (e.g., basilic vein, brachial artery) can influence the recorded EMG signals. As the electrical conductivity of blood is high (it is of the same order as the longitudinal conductivity in the muscle), the effect on EMG signals is opposite compared to the effect of a superficial bone.

The aim of this simulation study was to assess the bias in estimating muscle fiber conduction velocity (CV) from surface electromyographic (EMG) signals in muscles with one and two pinnation angles. The volume conductor was a layered medium simulating anisotropic muscle tissue and isotropic homogeneous subcutaneous tissue. The muscle tissue was homogeneous for one pinnation angle and inhomogeneous for bipinnate muscles (two fiber directions). Interference EMG signals were obtained by simulating recruitment thresholds and discharge patterns of a set of 100 and 200 motor units for the pinnate and bipinnate muscle, respectively (15 degrees pinnation angel in both cases). Without subcutaneous layer and muscle fibers with CV 4m/s, average CV estimates from the pinnate (bipinnate) muscle were 4.81+/-0.18 m/s (4.80+/-0.18 m/s) for bipolar, 4.71+/-0.19 m/s (4.71+/-0.12 m/s) for double differential, and 4.78+/-0.16 m/s (4.79+/-0.15m/s) for Laplacian recordings. When subcutaneous layer was added (thickness 1mm) in the same conditions, estimated CV values were 4.93+/-0.25 m/s (5.16+/-0.41 m/s), 4.70+/-0.21 m/s (4.83+/-0.33 m/s), and 4.89+/-0.21 m/s (4.99+/-0.39 m/s), for the three recording systems, respectively. The main factor biasing CV estimates was the propagation of action potentials in the two directions which influenced the recording due to the scatter of the projection of end-plate and tendon locations along the fiber direction, as a consequence of pinnation. The same problem arises in muscles with the line of innervation zone locations not perpendicular to fiber direction. These results indicate an important limitation in reliability of CV estimates from the interference EMG when the innervation zone and tendon locations are not distributed perpendicular to fiber direction.

Everyday clinical cardiovascular evaluation is still largely based on brachial systolic and diastolic pressures. However, several clinical studies have demonstrated the higher diagnostic capacities of the aortic pressure, as well as the need to assess the aortic mechanical properties (e.g., by measuring the aortic pulse wave velocity). In order to fill this gap, we propose to exploit a set of easy-to-obtain physical characteristics to estimate the aortic pressure and pulse wave velocity. To this aim, a large population of virtual subjects is created by a validated mathematical model of the cardiovascular system. Quadratic regressive models are then fitted and statistically selected in order to obtain reliable estimations of the aortic pressure and pulse wave velocity starting from the knowledge of the subject age, height, weight, brachial pressure, photoplethysmographic measures and either electrocardiogram or phonocardiogram. The results are very encouraging and foster clinical studies aiming to apply a similar technique to a real population.

Assessment of respirophasic fluctuations in the diameter of the inferior vena cava (IVC) is detrimentally affected by its concomitant displacements. This study was aimed at presenting and validating a method to compensate for IVC movement artifacts while continuously measuring IVC diameter in an automated fashion (with minimal interaction with the user) from a longitudinal B-mode ultrasound clip. Performance was tested on both experimental ultrasound clips collected from four healthy patients and simulations, implementing rigid IVC displacements and pulsation. Compared with traditional M-mode measurements, the new approach systematically reduced errors in caval index assessment (range over maximum diameter value) to an extent depending on individual vessel geometry, IVC movement and choice of the M-line (the line along which the diameter is computed). In experimental recordings, this approach identified both the cardiac and respiratory components of IVC movement and pulsatility and evidenced the spatial dependence of IVC pulsatility. IVC tracking appears to be a promising approach to reduce movement artifacts and to improve the reliability of IVC diameter monitoring.

PurposeDeveloping a real time method to estimate generation, extinction and propagation of muscle fibre action potentials from bi-dimensional and high density surface electromyogram (EMG). MethodA multi-frame generalization of an optical flow technique including a source term is considered. A model describing generation, extinction and propagation of action potentials is fit to epochs of surface EMG. ResultsThe algorithm is tested on simulations of high density surface EMG (inter-electrode distance equal to 5mm) from finite length fibres generated using a multi-layer volume conductor model. The flow and source term estimated from interference EMG reflect the anatomy of the muscle, i.e. the direction of the fibres (2? of average estimation error) and the positions of innervation zone and tendons under the electrode grid (mean errors of about 1 and 2mm, respectively). The global conduction velocity of the action potentials from motor units under the detection system is also obtained from the estimated flow. The processing time is about 1ms per channel for an epoch of EMG of duration 150ms. ConclusionsA new real time image processing algorithm is proposed to investigate muscle anatomy and activity. Potential applications are proposed in prosthesis control, automatic detection of optimal channels for EMG index extraction and biofeedback. Muscle fibre contractions is induced by action potentials which are generated at the innervation zone (IZ), propagate along the muscle fibres and extinguish at the tendon endings. Surface EMG reflects this bioelectrical activity of the muscle fibres. This paper proposes an innovative method which fits 2D high density surface EMG to a model describing production and flow, estimating the generation/extinction and propagation of action potentials. Two representative examples of applications are shown in Fig. 1. The method is real time, opening new possible applications: it investigates automatically muscle anatomy and activity, supporting the study of dynamic contractions, the control of prosthesis or the development of a biofeedback; moreover, it can support the automatic selection the optimal locations of the electrodes (far from IZ and tendons) from which EMG indexes can be reliably estimated.Display Omitted New algorithm to estimate generation, propagation and extinction of muscle fibre action potentials from EMG.Application 1: investigation of muscle anatomy (orientation of fibres and position of innervation zone and tendons).Application 2: investigation of muscle activity (conduction velocity of the action potentials along the fibres).Application 3: selection of optimal locations of the channels from which to extract reliable EMG indexes.The method is real time, opening potential applications in prosthesis control and in biofeedback.

Using computerized pupillometry, our previous research established that the autonomic nervous system (ANS) is dysregulated in patients suffering from temporomandibular disorders (TMDs), suggesting a potential role for ANS dysfunction in pain modulation and the etiology of TMD. However, pain modulation hypotheses for TMD are still lacking. The periaqueductal gray (PAG) is involved in the descending modulation of defensive behavior and pain through μ, κ, and δ opioid receptors. Transcutaneous electrical nerve stimulation (TENS) has been extensively used for pain relief, as low-frequency stimulation can activate µ receptors. Our aim was to use pupillometry to evaluate the effect of low-frequency TENS stimulation of μ receptors on opioid descending pathways in TMD patients. In accordance with the Research Diagnostic Criteria for TMD, 18 females with myogenous TMD and 18 matched-controls were enrolled. All subjects underwent subsequent pupillometric evaluations under dark and light conditions before, soon after (end of stimulation) and long after (recovery period) sensorial TENS. The overall statistics derived from the darkness condition revealed no significant differences in pupil size between cases and controls; indeed, TENS stimulation significantly reduced pupil size in both groups. Controls, but not TMD patients, displayed significant differences in pupil size before compared with after TENS. Under light conditions, TMD patients presented a smaller pupil size compared with controls; the pupil size was reduced only in the controls. Pupil size differences were found before and during TENS and before and after TENS in the controls only. Pupillometry revealed that stimulating the descending opioid pathway with low-frequency sensory TENS of the fifth and seventh pairs of cranial nerves affects the peripheral target. The TMD patients exhibited a different pattern of response to TENS stimulation compared with the controls, suggesting that impaired modulation of the descending pain system may be involved in TMD.

Recently, it has been proposed that obstructive sleep apnea syndrome (OSAS) is characterized by an imbalance in autonomic nervous tone. Pupil size has been considered a valid test for studying the autonomic nervous system (ANS). Pupillometry is a simple and non-invasive tool to assess the size and dynamics of the pupil. The purpose of this study was to evaluate, by pupillometry, the hypothesis that subjects with OSAS present ANS dysregulation.The study group included 10 males aged between 40 and 50 years with polysomnographic diagnoses of mild OSAS. The control group included 10 males with similar ages with an apnea-hypopnea index (AHI) of less than 5, after polysomnography. Pupillometry was performed by digital infrared pupillometer (25 frame/s). Recordings were processed to measure the area of the pupil frame by frame. The subjects underwent four subsequent recordings: infrared light at rest mandible position (RP); infrared light at forced habitual occlusion (FHO); yellow-green light at RP; and yellow-green light at FHO. According to literature, linear and non-linear information was extracted from the recordings.As expected, the two groups did not differ statistically in age and body mass index (BMI), while there was a significant difference in the AHI. In the within-group comparison of pupil size, there were significant differences between RP and FHO under infrared conditions in the control group. There was a significant difference in the determinism percentage (Det%) in the RP infrared condition between the control and OSAS groups.The results of the current study confirm ANS dysregulation in OSAS patients and provide a new possible strategy for studying this pathology by using pupillometry through linear and non-linear mathematical models.

Pupil is controlled by the autonomous nervous system. Patients with temporomandibular disorders (TMD) and with obstructive sleep apnea syndrome (OSAS) are affected by a dysregulation of the autonomous system. Pupillometry is here used to investigate the state of the autonomous system in 3 groups: control, TMD and OSAS. Different indexes are extracted from the pupillogram to characterize pupil dynamics investigated in rest and under stationary stimulations. All possible sets of 3 and 4 indexes are used as features to train support vector machines (SVM) to identify the correct groups. The indexes providing optimal classification are identified.

Diagnosis of bruxism is difficult since not all contractions of masticatory muscles during sleeping are bruxism episodes. In this paper, we propose the use of both EMG and ECG signals for the detection of sleep bruxism. Data have been acquired from 21 healthy volunteers and 21 sleep bruxers. The masseter surface EMGs were detected with bipolar concentric electrodes and the ECG with monopolar electrodes located on the clavicular regions. Recordings were made at the subjects' homes during sleeping. Bruxism episodes were automatically detected as characterized by masseter EMG amplitude greater than 10% of the maximum and heart rate increasing by more than 25% with respect to baseline within 1 s before the increase in EMG amplitude above the 10% threshold. Furthermore, the subjects were classified as bruxers and nonbruxers by a neural network. The number of bruxism episodes per night was 24.6 ± 8.4 for bruxers and 4.3 ± 4.5 for controls ( P

The purpose of this work is the estimation of the Glasgow outcome scale (GOS) from a single continuous electroencephalogram (c-EEG) routinely recorded to monitor comatose patients in the neurosurgical intensive care unit. c-EEG was recorded from 13 patients in the acute phase: five with GOS = 5, four with GOS = 3 and four with GOS = 1. Different indexes were extracted from epochs of c-EEG (classical: amplitude and spectral estimators; non classical: from recurrence quantification analysis—RQA—and approximate entropy). Descriptors of different indexes (temporal variation and mean, standard deviation, skewness of the distribution across epochs) were used to train support vector machines to identify the correct GOS. We found classifiers allowing correct classification of the patients. Spectral indexes allowed to get optimal performances in classifying GOS 1 and 3. Nonlinear indexes (especially determinism from RQA) were optimal for identifying GOS = 5. Thus, the integration of information from classical/linear and nonlinear c-EEG descriptors in a multi-index classifier is important for GOS estimation.

Simulation of surface electromyogram (EMG) has provided support for the development and testing of algorithms (e.g., for the extraction of amplitude or spectral properties of the EMG or for the estimation of the muscle fiber conduction velocity) and for the interpretation of experimental results. This is the second part of a pair of papers: the first explains the methods for the development of structure based models of surface EMG; this one provides a summary of interesting applications for the interpretation of signals and testing of algorithms. Simulations from some models already introduced in the literature are compared. Moreover, estimation of indexes from an innovative layered volume conductor including a subcutaneous tissue with variable thickness in space is studied.

The role of the autonomic nervous system (ANS) was recently investigated in Temporomandibular disorders (TMD). Several authors argue that in subjects with TMD there is a dysregulation of ANS. Recent literature support that Pupillometry is a simple non-invasive tool to study ANS. The aim of this study was to investigate the relationship between TMD and ANS activity using pupillometry recording in Infrared light at rest Mandible Position (RP); Infrared light at Forced Habitual Occlusion (FHO); Yellow-green light at RP; Yellow-green light at FHO. Forty female subjects were enrolled: 20 case patients showed TMD based on the Research Diagnostic Criteria for TMD, and 20 control patients, aged matched, had no signs or symptoms of TMD. Statistical analysis was performed on average pupil size. Ratio between pupil size in FHO and RP (FHO/RP ratio) and yellow-green and infrared (light/darkness ratio) lighting were carried out. Within group differences of pupil size and of “ratio” were analyzed using a paired t test, while differences of pupil size between groups were tested using an unpaired t test. Statistical comparisons between groups showed no significant differences of absolute values of pupil dimension in RP and FHO, both in yellow-green and in infrared lighting. In addition, there were no significant differences within groups comparing RP and FHO in yellow-green light. In within group comparison of pupil size, differences between RP and FHO were significant in infrared conditions. Control subjects increased, whereas TMD patients decreased pupil size at FHO in infrared lightening. FHO/RP ratio in darkness and light/darkness ratio in RP were significantly different between groups. Taken together, these data suggest that TMD subjects have an impairment of the sympathetic-adrenergic component of the ANS to be activated under stress. The present study provides preliminary pupillometric data confirming that adrenergic function is dysregulated in patients with TMD.

Air pollution is an important problem concerning the quality of living and health conditions of the population in urban areas (Pasero & Mesin, 2010). Indeed, the issue of air quality is now a major concern for many governments worldwide. Since the early 1970s, the EU has been working to improve air quality by controlling emissions of harmful substances into the atmosphere, by improving fuel quality and by integrating environmental protection requirements into the transport and energy sectors. As the result of EU legislation, much progress has been made in tackling air pollutants. However air quality continues to cause problems. As an example, photochemical smog, particularly active in sunny days, regularly exceeds a safe limit over main European metropolitan areas. EU legislation established an hourly average of 180μg/m3 as the threshold of safe limit for ozone (Directive 2002/3/EC) beyond which authorities have to inform population. According to the indications of the Environment Commissioner Janez Potocnik (Potocnik, 2010), air pollution is responsible for 370.000 premature deaths in EU each year. Airborne particles (e.g. Particulate Matter with diameter lower or equal to 10 m, PM10) are mainly present in pollutant emissions from industry, traffic and domestic heating. They can cause asthma, cardiovascular problems, lung cancer and premature death. The EU Directive 2008/50/EC requires Member States to ensure that certain limit values for PM10 are met. These limits, which were to be met by 2005, impose both an annual average concentration value (40 ┤g/m3), and a daily concentration value (50 ┤g/m3) which must not be exceeded more than 35 times per calendar year (European Environmental Bureau, 2005). The World Health Organization pointed out that USA traffic fatalities are over 40.000 per year, while air pollution claims 70.000 lives annually (Air Quality Guidelines, WHO, 2006). Experimental studies carried on Oslo urban site pointed out the temporal connection between cardiopulmonary inflammatory state of sick citizens and high concentration of PM in the area, especially in winter and early spring time (Schwarze P.E. et al, 2010). The impact of air pollution is on human health and on ecosystems also, as marine, freshwater, grassland, heat or forest ecosystem. The air pollution is directly linked to acidification of forests and water ecosystems, and eutrophication of soils and waters, leading to limited supply of oxygen in rivers and lakes. The benefits of air pollution abatement in the heat and grassland ecosystem, typical European farm environment, have been estimated as two hundred millions of euro each year saved (DeSmet et al, 2007). Indeed, air pollution not only affects

Interpretation of surface electromyograms (EMG) is usually based on the assumption that the surface representation of action potentials does not change during their propagation. This assumption does not hold for muscles whose fibers are oblique to the skin. Consequently, the interpretation of surface EMGs recorded from pinnate muscles unlikely prompts from current knowledge. Here we present a complete analytical model that supports the interpretation of experimental EMGs detected from muscles with oblique architecture. EMGs were recorded from the medial gastrocnemius muscle during voluntary and electrically elicited contractions. Preliminary indications obtained from simulated and experimental signals concern the spatial localization of surface potentials and the myoelectric fatigue. Specifically, the spatial distribution of surface EMGs was localized about the fibers superficial extremity. Strikingly, this localization increased with the pinnation angle, both for the simulated EMGs and the recorded M-waves. Moreover, the average rectified value (ARV) and the mean frequency (MNF) of interference EMGs increased and decreased with simulated fatigue, respectively. The degree of variation in ARV and MNF did not depend on the pinnation angle simulated. Similar variations were observed for the experimental EMGs, although being less evident for a higher fiber inclination. These results are discussed on a physiological context, highlighting the relevance of the model proposed here for the interpretation of gastrocnemius EMGs and for conceiving future experiments on muscles with pinnate geometry.

The issue of air quality is now a major concern for many citizens worldwide. Local air quality forecasting can be made on the basis of meteorological variables and air pollutants concentration time series. We propose an adaptive filter technique based on an artificial neural network (ANN) to make 24-hours maximal daily ozone-concentrations forecasts.

Aims Knowledge of the distribution of the innervation zones (IZs) of the external anal sphincter (EAS) may be useful for preventing anal sphincter incompetence during vaginal delivery. A method proposed for the automatic estimation of the distribution of IZs of EAS from high-density surface electromyography (EMG) was evaluated for repeatability in continent volunteers. Methods In 13 healthy female subjects (age: 35 ± 11 years) surface EMG signals were acquired using an anal probe with three circumferential electrode arrays (of 16 contacts each) at different depths within the anal canal (15 mm distance between the centers of adjacent arrays), during four independent experimental sessions. Three maximal voluntary contractions (MVCs) of 10 sec were performed for each session for a total of 12 contractions per subject. Repeatability of the estimation of the distribution of IZ was tested by evaluating the coefficient of multiple correlations (CMC) between the IZ distributions estimated from the signals recorded from each subject. Results A high repeatability (CMC > 0.8) was found comparing IZ distributions estimated from signals recorded by each array within the same session. A slightly lower value was obtained considering signals recorded during different sessions (CMC > 0.7), but a higher value (CMC > 0.8) was obtained after aligning the estimated IZ distributions. The realignment compensates for the operator's error in repositioning the probe in the same position during different sessions. Conclusion This result justifies clinical studies using high-density surface EMG in routine examinations, providing information about IZs of EAS and assessing the possibilities of preventing neuronal trauma during vaginal delivery. Neurourol. Urodynam. 29:449–457, 2010. © 2009 Wiley-Liss, Inc.

Surface electromyograms (EMGs) recorded with a couple of electrodes are meant to comprise representative information of the whole muscle activation. Nonetheless, regional variations in neuromuscular activity seem to occur in numerous conditions, from standing to passive muscle stretching. In this study, we show how local activation of skeletal muscles can be automatically tracked from EMGs acquired with a bi-dimensional grid of surface electrodes (a grid of 8 rows and 15 columns was used). Grayscale images were created from simulated and experimental EMGs, filtered and segmented into clusters of activity with the watershed algorithm. The number of electrodes on each cluster and the mean level of neuromuscular activity were used to assess the accuracy of the segmentation of simulated signals. Regardless of the noise level, thickness of fat tissue and acquisition configuration (monopolar or single differential), the segmentation accuracy was above 60%. Accuracy values peaked close to 95% when pixels with intensity below approximately 70% of maximal EMG amplitude in each segmented cluster were excluded. When simulating opposite variations in the activity of two adjacent muscles, watershed segmentation produced clusters of activity consistently centered on each simulated portion of active muscle and with mean amplitude close to the simulated value. Finally, the segmentation algorithm was used to track spatial variations in the activity, within and between medial and lateral gastrocnemius muscles, during isometric plantar flexion contraction and in quiet standing position. In both cases, the regionalization of neuromuscular activity occurred and was consistently identified with the segmentation method.

Increasing the selectivity of the detection system in surface electromyography (EMG) is beneficial in the collection of information of a specific portion of the investigated muscle and to reduce the contribution of undesired components, such as non-propagating components (due to generation or end-of-fibre effects) or crosstalk from nearby muscles. A comparison of the ability of different spatial filters to reduce the amount of crosstalk in surface EMG measurements was conducted in this paper using simulated signals. It focused on the influence of different properties of the muscle anatomy (changing subcutaneous layer thickness, skin conductivity, fibre length) and detection system (single, double and normal double differential, with two inter-electrode distances - IED) on the amount of crosstalk present in the measurements. A cylindrical multilayer (skin, subcutaneous tissue, muscle, bone) analytical model was used to simulate single fibre action potentials (SFAPs). Fibres were grouped together in motor units (MUs) and motor unit action potentials (MUAPs) were obtained by adding the SFAPs of the corresponding fibres. Interference surface EMG signals were obtained, modelling the recruitment of MUs and rate coding. The average rectified value (ARV) and mean frequency (MNF) content of the EMG signals were studied and used as a basis for determining the selectivity of each spatial filter. From these results it was found that the selectivity of each spatial filter varies depending on the transversal location of the measurement electrodes and on the anatomy. An increase in skin conductivity favourably affects the selectivity of normal double differential filters as does an increase in subcutaneous layer thickness. An increase in IED decreases the selectivity of all the analysed filters.

Traumas of the innervation zone (IZ) of the external anal sphincter (EAS), e.g. during delivery, can promote the development of faecal incontinence. Recently developed probes allow high-resolution detection of EMG signals from the EAS. The analysis of pelvic floor muscles by surface EMG (in particular, the estimation of the location of the IZ) has potential applications in the diagnosis and investigation of the mechanisms of incontinence. An automatic method (based on matched filter approach) for the estimation of the IZ distribution of EAS from surface EMG is discussed and tested using an analytical model of generation of EMG signals from sphincter muscles. Simulations are performed varying length of the fibres, thickness of the mucosa, position of the motor units, and force level. Different distributions of IZs are simulated. The performance of the proposed method in the estimation of the IZ distribution is affected by surface MUAP amplitude (as the estimation made by visual inspection), by mucosa thickness (performance decreases when fibre length is higher) and by different MU distributions. However, in general the method is able to identify the position of two IZ locations and can measure asymmetry of the IZ distribution. This strengthens the potential applications of high density surface EMG in the prevention and investigation of incontinence.

Two physiological factors are assumed in this paper to mainly determine the myoelectric manifestations of fatigue: (1) the decrease of the conduction velocity (CV) of motor unit action potentials (MUAP) (peripheral fatigue), and (2) the increase of MU synchronization by the central nervous system (central fatigue). To describe separately the peripheral and central components of the myoelectric manifestations of fatigue, we investigated the following indexes: (1) mean spectral frequency – MNF, (2) median spectral frequency – MDF, (3) root mean square – RMS, (4) average rectified value – ARV, (5) estimation of muscle fiber conduction velocity – ECV, (6) percentage of determinism – %DET, (7) spectral indexes defined as the ratio between signal spectral moments – FI k , (8) MNF estimated by autoregressive analysis – MNF AR , (9) MNF estimated by Choi–Williams time-frequency representation – MNF CWD , (10) MNF estimated by continuous wavelet transform – MNF CWT , (11) signal entropy – S, (12) fractal dimension – FD. The indexes were tested with a set of synthetic EMG signals, with different CV distribution and level of MU synchronization. The indexes were calculated on epochs of 0.5s. It was observed that ECV is uncorrelated with the level of simulated synchronization (promising index of peripheral fatigue). On the other hand FD was the index least affected by CV changes and most related to the level of synchronism (promising index of central fatigue). A representative application to some experimental signals from vastus lateralis muscle during an isometric endurance test supported the results of the simulations. The vector (ECV, FD) is suggested to provide selective indications of peripheral and central fatigue. The description of EMG fatigue by a bi-dimensional vector opens new perspectives in the assessment of muscle properties, with potential application in both clinical and sport sciences.

Background Recording surface electromyogram (EMG) signals from sphincter muscles has become of increasing interest due to potential applications in diagnosis or investigation of the mechanisms of incontinence. Recently developed probes allow high-resolution detection of EMG signal from the external anal sphincter. One of the main issues in the interpretation of experimental signals is the detection volume of the recording electrodes. Methods An analytical model of generation of EMG from the anal sphincter was applied to simulate single fiber action potentials varying the fiber length, conductivity and thickness of the mucosa, shape of the electrodes, and detection system (monopolar, bipolar, and double differential). Results The new probe is more selective than classical probes with big electrodes and large interelectrode distance. The decay of the recorded surface EMG action potentials with distance of the fiber was faster for increasing depth than axial distance (this is due to the geometry of the volume conductor, as indicated by comparison with simulations with a planar volume conductor). Point electrodes led to smaller detection volumes than rectangular electrodes, and the double differential system was the most selective recording configuration. The relative decrease of the detected potential generated by more distant fibers was lower for increasing thickness and conductivity of the mucosa. End-of-fiber components are enhanced by the circular geometry of sphincter muscles with respect to the case of a planar volume conductor. Conclusions The detection volume of EMG recording systems from sphincter muscles extends more in the axial than in the depth direction and is affected by many parameters that cannot be estimated in practical situations, thus introducing a rather large variability in the muscle portion investigated among subjects. More selective information can be obtained using the recently developed multi-channel probe with respect to classical probes. Selectivity is increased with small electrodes and double differential recordings.

Objective A method for conduction block (CB) estimation, based on compound muscle action potentials (CMAP) elicited by stimulation at sites proximal and distal to the region in which a block is suspected, which is less sensitive to temporal dispersion than methods based on area and amplitude estimation, routinely used in clinical practice. Methods The method is based on deconvolution of CMAPs. It provides the delay distribution that convolved with a kernel (estimated by an optimisation method) gives a reconstruction of the CMAPs. The integral of the delay distribution was used to estimate CB. The method was tested on phenomenological signals (sum of delayed and amplitude scaled versions of the same signal), structure based simulated signals (from a plane layer generation model of surface EMG), and experimental signals (eight healthy subjects; CMAPs recorded over abductor digiti minimi; different temporal dispersions obtained comparing above-elbow stimulation of ulnar nerve with below-elbow stimulation or with wrist stimulation; conduction distances about 10 and 35 cm, respectively). Results Deconvolution method gives more precise estimates of the simulated CB with respect to area and amplitude methods (phenomenological signals: bias in CB estimation in the worst case about 10% for deconvolution, 30% for area, 60% for amplitude). Experimental data: by increasing temporal dispersion, in the average CB estimation increases 4% for area and 10% for amplitude, no increase for deconvolution. Conclusions The new method for CB estimation is less sensitive to temporal dispersion than area and amplitude methods. Significance The proposed method provides a precise CB estimation. Being stable to temporal dispersion, it allows to diagnose CB with a lower confidence threshold than in the case of area and amplitude.

Discussion: The experimental setup showed here represents a sensitive tool to detect the presence of the perceptive impairment in patients with SD. Although with high variability, results showed different behaviors in patients with motor disability compared to the perceptuals. The presence of perceptive facilitation ‘raised floor’ in the FRT trials yielded to an improvement of the performance only in the perceptual, as measured by movement smoothness during the task (NJS) and of the SA during the static posture. Further experiments and more detailed statistical analysis are needed to characterize the absence and the magnitude of the perceptive impairment in patients with SD in an exhaustive way.

A finite-element model for the generation of single fiber action potentials in a muscle undergoing various degrees of fiber shortening is developed. The muscle is assumed fusiform with muscle fibers following a curvilinear path described by a Gaussian function. Different degrees of fiber shortening are simulated by changing the parameters of the fiber path and maintaining the volume of the muscle constant. The conductivity tensor is adapted to the muscle fiber orientation. In each point of the volume conductor, the conductivity of the muscle tissue in the direction of the fiber is larger than that in the transversal direction. Thus, the conductivity tensor changes point-by-point with fiber shortening, adapting to the fiber paths. An analytical derivation of the conductivity tensor is provided. The volume conductor is then studied with a finite-element approach using the analytically derived conductivity tensor. Representative simulations of single fiber action potentials with the muscle at different degrees of shortening are presented. It is shown that the geometrical changes in the muscle, which imply changes in the conductivity tensor, determine important variations in action potential shape, thus affecting its amplitude and frequency content. The model provides a new tool for interpreting surface EMG signal features with changes in muscle geometry, as it happens during dynamic contractions.