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[EN] Surface electromyography (sEMG) can be used for the evaluation of respiratory muscle activity. Recording sEMG involves the use of surface electrodes in a bipolar configuration. However, electrocardiographic (ECG) interference and electrode orientation represent considerable drawbacks to bipolar acquisition. As an alternative, concentric ring electrodes (CREs) can be used for sEMG acquisition and offer great potential for the evaluation of respiratory muscle activity due to their enhanced spatial resolution and simple placement protocol, which does not depend on muscle fiber orientation. The aim of this work was to analyze the performance of CREs during respiratory sEMG acquisitions. Respiratory muscle sEMG was applied to the diaphragm and sternocleidomastoid muscles using a bipolar and a CRE configuration. Thirty-two subjects underwent four inspiratory load spontaneous breathing tests which was repeated after interchanging the electrode positions. We calculated parameters such as (1) spectral power and (2) median frequency during inspiration, and power ratios of inspiratory sEMG without ECG in relation to (3) basal sEMG without ECG (R-ins/noise), (4) basal sEMG with ECG (R-ins/cardio) and (5) expiratory sEMG without ECG (R-ins/exp). Spectral power, R-ins/noise and R-ins/cardio increased with the inspiratory load. Significantly higher values (p < 0.05) of R-ins/cardio and significantly higher median frequencies were obtained for CREs. R-ins/noise and R-ins/exp were higher for the bipolar configuration only in diaphragm sEMG recordings, whereas no significant differences were found in the sternocleidomastoid recordings. Our results suggest that the evaluation of respiratory muscle activity by means of sEMG can benefit from the remarkably reduced influence of cardiac activity, the enhanced detection of the shift in frequency content and the axial isotropy of CREs which facilitates its placement., This work was supported in part by the CERCA Program/Generalitat de Catalunya, in part by the Secretaria d'Universitats i Recerca de la Generalitat de Catalunya under Grant GRC 2017 SGR 01770, in part by the Spanish Grants RTI2018-098472-B-I00, RTI2018-094449-A-I00-AR (MCIU/AEI/FEDER, UE) and DPI2015-68397-R (MINECO/FEDER), and in part by the Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN, Instituto de Salud Carlos III/FEDER). The first author was supported by the IFARHU-SENACYT Scholarship Program from the Panama Government under Grant 270-2012-273.

Conventional MRI measures of traumatic spinal cord injury severity largely rely on 2-dimensional injury characteristics such as intramedullary lesion length and cord compression. Recent advances in spinal cord (SC) analysis have led to the development of a robust anatomic atlas incorporated into an open-source platform called the Spinal Cord Toolbox (SCT) that allows for quantitative volumetric injury analysis. In the current study, we evaluate the prognostic value of volumetric measures of spinal cord injury on MRI following registration of T2-weighted (T2w) images and segmented lesions from acute SCI patients with a standardized atlas. This IRB-approved prospective cohort study involved the image analysis of 60 blunt cervical SCI patients enrolled in the TRACK-SCI clinical research protocol. Axial T2w MRI data obtained within 24 h of injury were processed using the SCT. Briefly, SC MRIs were automatically segmented using the sct_deepseg_sc tool in the SCT and segmentations were manually corrected by a neuro-radiologist. Lesion volume data were used as predictor variables for correlation with lower extremity motor scores at discharge. Volumetric MRI measures of T2w signal abnormality comprising the SCI lesion accurately predict lower extremity motor scores at time of patient discharge. Similarly, MRI measures of injury volume significantly correlated with motor scores to a greater degree than conventional 2-D metrics of lesion size. The volume of total injury and of injured spinal cord motor regions on T2w MRI is significantly and independently associated with neurologic outcome at discharge after injury.

This study aims to investigate noninvasive indices of neuromechanical coupling (NMC) and mechanical efficiency (MEff) of parasternal intercostal muscles. Gold standard assessment of diaphragm NMC requires using invasive techniques, limiting the utility of this procedure. Noninvasive NMC indices of parasternal intercostal muscles can be calculated using surface mechanomyography (sMMGpara) and electromyography (sEMGpara). However, the use of sMMGpara as an inspiratory muscle mechanical output measure, and the relationships between sMMGpara, sEMGpara, and simultaneous invasive and noninvasive pressure measurements have not previously been evaluated. sEMGpara, sMMGpara, and both invasive and noninvasive measurements of pressures were recorded in twelve healthy subjects during an inspiratory loading protocol. The ratios of sMMGpara to sEMGpara, which provided muscle-specific noninvasive NMC indices of parasternal intercostal muscles, showed nonsignificant changes with increasing load, since the relationships between sMMGpara and sEMGpara were linear (R2 = 0.85 (0.75–0.9)). The ratios of mouth pressure (Pmo) to sEMGpara and sMMGpara were also proposed as noninvasive indices of parasternal intercostal muscle NMC and MEff, respectively. These indices, similar to the analogous indices calculated using invasive transdiaphragmatic and esophageal pressures, showed nonsignificant changes during threshold loading, since the relationships between Pmo and both sEMGpara (R2 = 0.84 (0.77–0.93)) and sMMGpara (R2 = 0.89 (0.85–0.91)) were linear. The proposed noninvasive NMC and MEff indices of parasternal intercostal muscles may be of potential clinical value, particularly for the regular assessment of patients with disordered respiratory mechanics using noninvasive wearable and wireless devices.

Background: Heart failure (HF) is common in COPD and contributes to increased breathlessness and adverse clinical outcomes. Aims and Objectives: To test the hypothesis that COPD-HF patients exhibit greater impairments in respiratory mechanics and are more breathless during inspiratory threshold loading (ITL) than COPD alone,. Methods: COPD and COPD-HF patients underwent incremental ITL at 12, 24, 36, 48 and 60% of maximal inspiratory mouth pressure (PImax). Neural respiratory drive (NRD) was recorded continuously using 2nd intercostal space transcutaneous electromyography (EMGpara). NRD index (NRDI=EMGpara%max x respiratory rate), neuromechanical uncoupling (NMU=NRDI/PTPmo), mBorg breathlessness intensity and Multidimensional Dyspnea Profile (MDP) scores were compared at the highest ITL achieved. Results: 11 COPD (mean (SD) age 69 (7) years, FEV1%pred 49.3 (16.4)%, 10 male) and 12 COPD-HF patients (mean (SD) age 72 (6) years, FEV1%pred 54.3 (13.1)%, 9 male) were studied. Median (IQR) mMRC dyspnoea was significantly higher in COPD-HF (COPD-HF: mMRC=3 (2 – 3.75), COPD: mMRC=2 (1 - 3); p=0.032). NRDI/PTPmo, MDP work/effort and mental effort were significantly higher, and Pmo pressure swings lower, in COPD-HF than in COPD at peak ITL (Table 1). Conclusions: Despite lower peak ITL load, both NMU and MDP work/effort were higher in COPD-HF than COPD. Contributory factors require further study.

Diaphragm neuromechanical coupling (NMC), which reflects the efficiency of conversion of neural activation to transdiaphragmatic pressure (Pdi), is increasingly recognized to be a useful clinical index of diaphragm function and respiratory mechanics in neuromuscular weakness and cardiorespiratory disease. However, the current gold standard assessment of diaphragm NMC requires invasive measurements of Pdi and crural diaphragm electromyography (oesEMGdi), which complicates the measurement of diaphragm NMC in clinical practice. This is the first study to compare invasive measurements of diaphragm NMC (iNMC) using the relationship between Pdi and oesEMGdi, with noninvasive assessment of NMC (nNMC) using surface mechanomyography (sMMGlic) and electromyography (sEMGlic) of lower chest wall inspiratory muscles. Both invasive and noninvasive measurements were recorded in twelve healthy adult subjects during an inspiratory threshold loading protocol. A linear relationship between noninvasive sMMGlic and sEMGlic measurements was found, resulting in little change in nNMC with increasing inspiratory load. By contrast, a curvilinear relationship between invasive Pdi and oesEMGdi measurements was observed, such that there was a progressive increase in iNMC with increasing inspiratory threshold load. Progressive recruitment of lower ribcage muscles, serving to enhance the mechanical advantage of the diaphragm, may explain the more linear relationship between sMMGlic and sEMGlic (both representing lower intercostal plus costal diaphragm activity) than between Pdi and crural oesEMGdi. Noninvasive indices of NMC derived from sEMGlic and sMMGlic may prove to be useful indices of lower chest wall inspiratory muscle NMC, particularly in settings that do not have access to invasive measures of diaphragm function.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Neural respiratory drive as measured by the electromyography allows the study of the imbalance between the load on respiratory muscles and its capacity. Surface respiratory electromyography (sEMG) is a non-invasive tool used for indirectly assessment of NRD. It also provides a way to evaluate the level and pattern of respiratory muscle activation. The prevalence of electrocardiographic activity (ECG) in respiratory sEMG signals hinders its proper evaluation. Moreover, the occurrence of abnormal heartbeats or cardiac arrhythmias in respiratory sEMG measures can make even more challenging the NRD estimation. Respiratory sEMG can be evaluated using the fixed sample entropy (fSampEn), a technique which is less affected by cardiac artefacts. The aim of this work was to investigate the performance of the fSampEn, the root mean square (RMS) and the average rectified value (ARV) on respiratory sEMG signals with supraventricular arrhythmias (SVA) for NRD estimation. fSampEn, ARV and RMS parameters increased as the inspiratory load increased during the test. fSampEn was less influenced by ECG with SVAs for the NRD estimation showing a greater response to respiratory sEMG, reflected with a higher percentage increase with increasing load (228 % total increase, compared to 142 % and 135 % for ARV and RMS, respectively).

Introduction and objectives Heart failure is a common comorbidity of COPD and contributes to increased breathlessness and adverse clinical outcomes. Neural respiratory drive (NRD) is closely related to breathlessness intensity in COPD. This study aimed to investigate the impact of comorbid left heart failure (COPD-HF) on NRD in patients with COPD. We hypothesised that NRD would be higher during an inspiratory threshold loading protocol (ITL) in COPD-HF than in COPD patients without left heart failure. Methods COPD and COPD-HF patients underwent incremental ITL at 12%, 24%, 36%, 48% and 60% of maximal inspiratory mouth pressure (PImax). NRD was recorded continuously using 2nd intercostal space transcutaneous electromyography (EMGpara). EMGpara signals were converted to root mean square (RMS), normalised to peak RMS EMGpara during maximal inspiratory manoeuvres (EMGpara%max) and multiplied by respiratory rate to calculate NRD index (NRDI). NRDI in COPD and COPD-HF were compared at each load using mixed effect model repeated measurement analysis. Results 11 COPD patients without left heart failure (mean (SD) age 69(7) years, FEV1%predicted 49.3 (16.4)%, VC%predicted 99.8 (22.0)%, PIMax 55.7 (15.8)cmH2O) and 11 COPD-HF patients (mean (SD) age 72(6) years, FEV1%predicted 54.8 (13.6)%, VC%predicted 86.8 (17.4)%), PIMax 53.1 (30.9)cmH2O) were studied. mMRC dyspnoea scores were higher in COPD-HF (median (IQR) 3 (2 – 4) than in COPD (median (IQR) 2 (1 to 3), p=0.0406). 11/11 COPD patients completed all loads of the ITL protocol to 60% PImax, compared to 4/11 patients in the COPD-HF group (p=0.0039). There were significant fixed effects of diagnosis (p=0.0136), load (p Conclusions Observations of higher levels of NRDI at equivalent inspiratory threshold loads in COPD-HF suggests that heart failure further increases the mechanical load on the respiratory muscles in COPD. Contributions of potential aetiological factors, such as reduced lung and chest wall compliance, require further study.

Using wearable devices in clinical routines could reduce healthcare costs and improve the quality of assessment in patients with chronic respiratory diseases. The purpose of this study is to evaluate the capability of a Shimmer3 wearable device device to extract reliable cardiorespiratory parameters from surface diaphragm electromyography (EMGdi). Twenty healthy volunteers underwent an incremental load respiratory test whilst EMGdi was recorded with a Shimmer3 wearable device (EMGdiW). Simultaneously, a second EMGdi (EMGdiL), the inspiratory mouth pressure (Pmouth) and the lead-I electrocardiogram (ECG) were recorded via a standard wired laboratory acquisition system. Different cardiorespiratory parameters have been extracted from both EMGdiW and EMGdiL signals.: heart rate, respiratory rate, respiratory muscle activity and mean frequency of EMGdi signals. Alongside these, similar parameters were also extracted from reference signals (Pmouth and ECG). High correlations were found between the data extracted from the EMGdiW and the reference signal data: heart rate (R = 0.947), respiratory rate (R = 0.940), respiratory muscle activity (R = 0.877), and mean frequency (R = 0.895). Moreover, similar increments in EMGdiW and EMGdiL activity were observed when Pmouth was raised, enabling the study of respiratory muscle activation. In summary, the Shimmer3 device is a promising and cost-effective solution for ambulatory monitoring of respiratory muscle function in chronic respiratory diseases.

The electrical activity of the diaphragm measured by surface electromyography (sEMGdi) provides indirect information on neural respiratory drive. Moreover, it allows evaluating the ventilatory pattern from the onset and offset (ntoff) estimation of the neural inspiratory time. sEMGdi amplitude variation was quantified using the fixed sample entropy (fSampEn), a less sensitive method to the interference from cardiac activity. The detection of the ntoff is controversial, since it is located in an intermediate point between the maximum value and the cessation of sEMGdi inspiratory activity, evaluated by the fSampEn. In this work ntoff detection has been analyzed using thresholds between 40% and 100 % of the fSampEn peak. Furthermore, fSampEn was evaluated analyzing the r parameter from 0.05 to 0.6, using a m equal to 1 and a sliding window size equal to 250 ms. The ntoff has been compared to the offset time (toff) obtained from the airflow during a controlled respiratory protocol varying the fractional inspiratory time from 0.54 to 0.18 whilst the respiratory rate was constant at 16 bpm. Results show that the optimal threshold values were between 66.0 % to 77.0 % of the fSampEn peak value. r values between 0.25 to 0.50 were found suitable to be used with the fSampEn.

The relationship between surface diaphragm mechanomyography (sMMGdi), as a noninvasive measure of inspiratory muscle mechanical activation, and crural diaphragm electromyography (oesEMGdi), as the invasive gold standard measure of diaphragm electrical activation, had not previously been examined. To investigate this relationship, oesEMGdi and sMMGdi were measured simultaneously in 6 healthy subjects during an incremental inspiratory threshold loading protocol, and analyzed using fixed sample entropy (fSampEn). A positive curvilinear relationship was observed between mean fSampEn sMMGdi and oesEMGdi (r = 0.67). Accordingly, an increasing electromechanical ratio was also observed with increasing inspiratory load. These findings suggest that sMMGdi could provide useful noninvasive measures of inspiratory muscle mechanical activation.

The assessment of respiratory muscle activity by surface electromyography (sEMG) is a promising noninvasive technique for the diagnosis and monitoring of chronic obstructive pulmonary disease. The diaphragm is the most important muscle in breathing, although in forced inspiration other muscles, such as sternocleidomastoid, are activated and contribute to the respiratory process. The measurement of the sEMG in these muscles (sEMGdi and sEMGscm, respectively) by means of two electrodes in conventional bipolar configuration (BEs) is a common practice to evaluate the respiratory muscle activity and allows to indirectly quantify the level of muscular activation. However, the resulting signals are usually contaminated by electrocardiographic (ECG) activity, hindering the assessment of the activity of these muscles. sEMG signals can also be recorded using concentric ring electrodes (CREs). CREs have greater spatial resolution and attenuate distant bioelectrical interferences. In this scenario, the objective of this work has been to evaluate the applicability of CREs for the acquisition of sEMGdi and sEMGscm. For this purpose, both sEMG signals were recorded simultaneously with BEs and CREs in healthy subjects while performing an inspiratory load protocol. To evaluate the effect of the cardiac interference, the ratio between the mean power in inspiratory segments without ECG and the mean power in expiratory segments with ECG (Rcardio) was calculated. Additionally, the ratio between the mean power in inspiratory segments without ECG and the mean power in expiratory segments without ECG (Rinex) was also calculated. The results revealed that the Rcardio and bandwidth is greater in sEMG signals acquired with the CREs, while the Rinex is higher in the signals acquired with BEs. These results suggest that the use of CREs is a recommended alternative for the acquisition of sEMG in muscles with high cardiac interference, such as the diaphragm muscle.

Fixed sample entropy (fSampEn) is a robust technique that allows the evaluation of inspiratory effort in diaphragm electromyography (EMGdi) signals, and has potential utility in sleep studies. To appropriately estimate respiratory effort, fSampEn requires the adjustment of several parameters. The aims of the present study were to evaluate the influence of the embedding dimension m, the tolerance value r, the size of the moving window, and the sampling frequency, and to establish recommendations for estimating the respiratory activity when using the fSampEn on surface EMGdi recorded for different inspiratory efforts. Values of m equal to 1 and r ranging from 0.1 to 0.64, and m equal to 2 and r ranging from 0.13 to 0.45, were found to be suitable for evaluating respiratory activity. fSampEn was less affected by window size than classical amplitude parameters. Finally, variations in sampling frequency could influence fSampEn results. In conclusion, the findings suggest the potential utility of fSampEn for estimating muscle respiratory effort in further sleep studies.

Measuring diaphragmatic electromyography (EMGdi) provides an indirect quantification of neural respiratory drive and allows the delimitation of diaphragm neural activation and deactivation during inspiration. EMGdi recordings have been incorporated in novel modes of assisted mechanical ventilation, such as neurally adjusted ventilatory assist (NAVA), to trigger and cycle-off the ventilator. The EMGdi signal improves the assistance delivered by more conventional ventilatory modes, in which the ventilator is synchronized with the patient employing a pneumatic triggering. In this work, we evaluate the time delay between the onset and offset of inspiratory activity estimated from EMGdi and three respiratory mechanical signals: the respiratory flow (FL), the transdiaphragmatic pressure (Pdi) and the diaphragm length (Ldi) signals. To this purpose, these signals were acquired in three mongrel dogs surgically instrumented under general anesthesia. Onsets and offsets were estimated manually and by automatic algorithms on these signals. The highest delays were obtained between EMGdi and FL (100 ms) while the lowest delays were obtained between EMGdi and Pdi (8 ms). Moreover, differences between manual and automatic estimations showed a mean absolute error lower than 45 ms. In conclusion, our study points out that both EMGdi and Pdi signals detect the onset and offset of inspiratory activity earlier than the FL signal, and would therefore be better for the improvement of patient-ventilator synchrony.

The use of non-invasive methods for the study of respiratory muscle signals can provide clinical information for the evaluation of the respiratory muscle function. The aim of this study was to evaluate time-frequency characteristics of the electrical activity of the sternocleidomastoid muscle recorded superficially by means of concentric ring electrodes (CREs) in a bipolar configuration. The CREs enhance the spatial resolution, attenuate interferences, as the cardiac activity, and also simplify the orientation problem associated to the electrode location. Five healthy subjects underwent a respiratory load test in which an inspiratory load was imposed during the inspiratory phase. During the test, the electromyographic signal of the sternocleidomastoid muscle (EMGsc) and the inspiratory mouth pressure (Pmouth) were acquired. Time-frequency characteristics of the EMGsc signal were analyzed by means of eight timefrequency representations (TFRs): the spectrogram (SPEC), the Morlet scalogram (SCAL), the Wigner-Ville distribution (WVD), the Choi-Williams distribution (CHWD), two generalized exponential distributions (GED1 and GED2), the Born- Jordan distribution (BJD) and the Cone-Kernel distribution (CKD). The instantaneous central frequency of the EMGsc showed an increasing behavior during the inspiratory cycle and with the increase of the inspiratory load. The bilinear TFRs (WVD, CHWD, GEDs and BJD) were less sensitive to cardiac activity interference than classical TFRs (SPEC and SCAL). The GED2 was the TFR that shown the best results for the characterization of the instantaneous central frequency of the EMGsc.

Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of the neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this study, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to the traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson's correlation values between inspiratory mouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV, and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were $0.38\pm 0.12$ , $0.27\pm 0.11$ , and $0.11\pm 0.13$ , respectively. Whereas at 33 cmH2O (maximum inspiratory load) were $0.83\pm 0.02$ , $0.76\pm 0.07$ , and $0.61\pm 0.19$ , respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.

background. Near-infrared reflectance-mode confocal scanning laser microscopy (RCM) represents a novel imaging technique for microscopic analysis of skin lesions and may provide a noninvasive modality for the diagnosis of basal cell carcinoma (BCC). objective. To determine the feasibility of detecting residual or clinically equivocal BCC using RCM. methods. In this pilot study, RCM was used in three cases to characterize the histologic features of index lesions in vivo. These were subsequently correlated with corresponding hematoxylin-eosin–stained sections obtained during Mohs micrographic surgery. results. Evaluation of clinically equivocal lesions by RCM revealed features characteristic of BCC, including tightly packed nests of elongated, monomorphic, polarized nuclei and subjacent ectatic blood vessels with lymphocytes undergoing margination and rolling. Conventional histology confirmed the presence of BCC in all cases. conclusion. We report the use of RCM in the confirmation of residual BCC in two cases and the tentative diagnosis with subsequent pathologic conformation of a third case in which a biopsy was previously inadequate. Our results demonstrate that confocal microscopy may facilitate diagnosis of BCC in vivo and warrant further prospective study to quantify the sensitivity and specificity of this rapidly evolving imaging modality.

Obstructive Sleep Apnea (OSA) is currently diagnosed by a full nocturnal polysomnography (PSG), a very expensive and time-consuming method. In previous studies we were able to distinguish patients with OSA through formant frequencies of breath sound during sleep. In this study we aimed at identifying OSA patients from breath sound analysis during wakefulness. The respiratory sound was acquired by a tracheal microphone simultaneously to PSG recordings. We selected several cycles of consecutive inspiration and exhalation episodes in 10 mild-moderate (AHI=30) OSA patients during their wake state before getting asleep. Each episode's formant frequencies were estimated by linear predictive coding. We studied several formant features, as well as their variability, in consecutive inspiration and exhalation episodes. In most subjects formant frequencies were similar during inspiration and exhalation. Formant features in some specific frequency band were significantly different in mild OSA as compared to severe OSA patients, and showed a decreasing correlation with OSA severity. These formant characteristics, in combination with some anthropometric measures, allowed the classification of OSA subjects between mild-moderate and severe groups with sensitivity (specificity) up to 88.9% (84.6%) and accuracy up to 86.4%. In conclusion, the information provided by formant frequencies of tracheal breath sound recorded during wakefulness may allow identifying subjects with severe OSA.

Extracting clinical information from one single measurement represents a step forward in the assessment of the respiratory muscle function. This attracting idea entails the reduction of the instrumentation and fosters to develop new medical integrated technologies. We present the use of the fixed sample entropy (fSampEn) as a more direct method to non-invasively derive the breathing activity from the diaphragm electromyographic (EMGdi) signal, and thus to extract the respiratory rate, an important vital sign which is cumbersome and time-consuming to be measured by clinicians. fSampEn is a method to evaluate the EMGdi activity that is less sensitive to the cardiac activity (ECG) and its application has proven to be useful to evaluate the load of the respiratory muscles. The behavior of the proposed method was tested in signals from two subjects that performed an inspiratory load protocol, which consists of increments in the inspiratory mouth pressure (Pmouth). Two respiratory signals were derived and compared to the Pmouth signal: the ECG-derived respiration (EDR) signal from the lead-I configuration, and the EMG-derived respiration (EMGDR) signal by applying the fSampEn method over the EMGdi signal. The similitude and the lag between signals were calculated through the cross-correlation between each derived respiratory signal and the Pmouth. The EMGDR signal showed higher correlation and lower lag values (= 0.91 and = 0.70 s, respectively) than the EDR signal (= 0.83 and = 0.99 s, respectively). Additionally, the respiratory rate was estimated with the Pmouth, EDR and EMGDR signals showing very similar values. The results from this preliminary work suggest that the fSampEn method can be used to derive the respiration waveform from the respiratory muscle electrical activity.

The aim of the present study was to measure bilateral asynchrony in patients suffering from Chronic Obstructive Pulmonary Disease (COPD) performing an incremental inspiratory load protocol. Bilateral asynchrony was estimated by the comparison of respiratory movements derived from diaphragm mechanomyographic (MMGdi) signals, acquired by means of capacitive accelerometers placed on left and right sides of the rib cage. Three methods were considered for asynchrony evaluation: Lissajous figure, Hilbert transform and Motto's algorithm. Bilateral asynchrony showed an increase at 20, 40 and 60% (values of normalized inspiratory pressure by their maximum value reached in the last inspiratory load) while the very severe group showed and increase at 20, 40, 80, and 100 % during the protocol. These increments in the phase's shift can be due to an increase of the inspiratory load along the protocol, and also as a consequence of distress and fatigue. In summary, this work evidenced the capability to estimate bilateral asynchrony in COPD patients. These preliminary results also showed that the use of capacitive accelerometers can be a suitable sensor for recording of respiratory movement and evaluation of asynchrony in COPD patients.

Diaphragm electromyography (EMGdi) provides important information on diaphragm activity, to detect neuromuscular disorders of the most important muscle in the breathing inspiratory phase. EMGdi is habitually recorded using needles or esophageal catheters, with the implication of being invasive for patients. Surface electrodes offer an alternative for the non-invasive assessment of diaphragm activity. Ag/AgCl surface disc electrodes are used in monopolar or bipolar configuration to record EMGdi signals. On the other hand, Laplacian surface potential can be estimated by signal recording through active concentric ring electrodes. This kind of recording could reduce physiological interferences, increase the spatial selectivity and reduce orientation problems in the electrode location. The aim of this work is to compare EMGdi signals recorded simultaneously with disc electrodes in bipolar configuration and a Laplacian ring electrode over chest wall. EMGdi signal was recorded in one healthy subject during a breath hold maneuver and a static inspiratory maneuver based on Mueller’s technique. In order to estimate the covered frequency range and the degree of noise contamination in both bipolar and Laplacian EMGdi signals, the cumulative percentage of the power spectrum and the signal to noise ratio in sub-bands were determined. Furthermore, diaphragm fatigue was evaluated by means of amplitude and frequency parameters. Our findings suggest that Laplacian EMGdi recording covers a broader frequency range although with higher noise contamination compared to bipolar EMGdi recording. Finally, in Laplacian recording fatigue indexes showed a clearer trend for muscle fatigue detection and also a reduced cardiac interference, providing an alternative to bipolar recording for diaphragm fatigue studies.

Diaphragm electromyography (EMGdi) provides important information on diaphragm activity, to detect neuromuscular disorders of the most important muscle in the breathing inspiratory phase. EMGdi is habitually recorded using needles or esophageal catheters, with the implication of being invasive for patients. Surface electrodes offer an alternative for the non-invasive assessment of diaphragm activity. Ag/AgCl surface disc electrodes are used in monopolar or bipolar configuration to record EMGdi signals. On the other hand, Laplacian surface potential can be estimated by signal recording through active concentric ring electrodes. This kind of recording could reduce physiological interferences, increase the spatial selectivity and reduce orientation problems in the electrode location. The aim of this work is to compare EMGdi signals recorded simultaneously with disc electrodes in bipolar configuration and a Laplacian ring electrode over chest wall. EMGdi signal was recorded in one healthy subject during a breath hold maneuver and a static inspiratory maneuver based on Mueller’s technique. In order to estimate the covered frequency range and the degree of noise contamination in both bipolar and Laplacian EMGdi signals, the cumulative percentage of the power spectrum and the signal to noise ratio in sub-bands were determined. Furthermore, diaphragm fatigue was evaluated by means of amplitude and frequency parameters. Our findings suggest that Laplacian EMGdi recording covers a broader frequency range although with higher noise contamination compared to bipolar EMGdi recording. Finally, in Laplacian recording fatigue indexes showed a clearer trend for muscle fatigue detection and also a reduced cardiac interference, providing an alternative to bipolar recording for diaphragm fatigue studies.

Surface electromyography (sEMG) is a noninvasive technique for monitoring the electrical activity produced by the muscles. Usually, sEMG is performed by carrying out monopolar or bipolar recordings by means of conventional Ag/AgCl electrodes. In contrast, Laplacian recordings of sEMG could also be obtained by using coaxial ring electrodes. Laplacian recordings increase spatial resolution and attenuate other distant bioelectric interferences. Nevertheless, the spectral characteristics of this kind of recordings have been scarcely studied. The objective of this paper is to characterize the sEMG signals recorded with a Laplacian ring electrode and to compare them with traditional bipolar recordings with disc electrodes. Both kinds of signals were collected simultaneously in two healthy subjects during resting and sustained isometric voluntary contraction activities in biceps brachii. The conducted study computed the cumulative percentage of the power spectrum of sEMG so as to determine the energy bandwidth of the two kinds of recordings and the signal to noise ratio in different bands of the sEMG spectrum. Also, muscle fatigue, a condition when muscle force is reduced, was assessed using indexes from amplitude and frequency domain. The results of this study suggest that Laplacian sEMG has higher spectral bandwidth but a lower signal to noise ratio in comparison to bipolar sEMG. In addition, frequency fatigue indexes showed that Laplacian recording had better response than bipolar recording, which suggests that Laplacian electrode can be useful to study muscular fatigue due to better spatial resolution.

In this work, it has been analyzed the performance of the Empirical Mode Decomposition (EMD) of electroencephalographic (EEG) signals for classification of different mental tasks. The EMD is a suitable method for processing nonstationary and nonlinear signals, as the EEG. Moreover this method is adaptive to the signal and it is able to decompose the analyzed signal into a set of adaptive frequency bands. This is quite different from the traditional approach, where EEG signals, using a spectral analysis technique, are divided in several frequency bands with fixed bandwidth, namely, δ ( 30 Hz). This paper presents an analysis of these adaptive bands. In order to contrast results, the proposed and the traditional methods were applied in a database of EEG signals acquired in 6 subjects performing 5 mental tasks in a Brain- Computer Interface experiment. It was found that using adaptive frequency bands of EMD technique the results were improved on an average of 12% respect to fixed bands. Also, it was observed an adaptation process trial over trial in the spectral content of adaptive frequency bands. Additionally, frequency content of adaptive bands shows some relationship with the performed mental task.

The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the signal. Both parameters can be used to estimate MMG activity, as they correlate well with muscle force. These estimations are, however, greatly affected by the presence of structured impulsive noise that overlaps in frequency with the MMG signal. In this paper, we present a method for assessing muscle activity based on the Lempel–Ziv algorithm: the Multistate Lempel–Ziv (MLZ) index. The behaviour of the MLZ index was tested with synthesised signals, with various amplitude distributions and degrees of complexity, and with recorded diaphragm MMG signals. We found that this index, like the ARV and RMS parameters, is positively correlated with changes in amplitude of the diaphragm MMG components, but is less affected by components that have non-random behaviour (like structured impulsive noise). Therefore, the MLZ index could provide more information to assess the MMG–force relationship.

The aim of this study was to evaluate the respiratory muscles efficiency during a progressive incremental flow (IF) respiratory test in healthy and Chronic Obstructive Pulmonary Disease (COPD) subjects. To achieve this, the relationship between mouth Inspiratory Pressure (IP) increment, which is a measure of the force produced by respiratory muscles, and respiratory muscular activity increment, evaluated by means of Mechanomyografic (MMG) signals of the diaphragm muscle, was analyzed. Moreover, the correlation between the respiratory efficiency measure and the obstruction severity of the subjects was also examined. Data from two groups of subjects were analyzed. One group consisted of four female subjects (two healthy subjects and two moderate COPD patients) and the other consisted of ten male subjects (six severe and four very severe COPD patients). All subjects performed an easy IF respiratory test, in which small IP values were reached. We have found that there is an increase of amplitude and a displacement towards low frequencies in the MMG signals when the IP increases. Furthermore, it has also been found that respiratory muscles efficiency is lower when greater the obstructive severity of the patients is, and it is lower in women than in men. These results suggest that the information provided by MMG signals could be used to evaluate the muscular efficiency in healthy and COPD subjects

Statistical analysis, power spectral density, and Lempel Ziv complexity, are used in a multi-parameter approach to analyze four temporal series obtained from the Electrocardiographic and Respiratory Flow signals of 126 patients on weaning trials. In which, 88 patients belong to successful group (SG), and 38 patients belong to failure group (FG), i.e. failed to maintain spontaneous breathing during trial. It was found that mean values of cardiac inter-beat and breath durations give higher values for SG than for FG; Kurtosis coefficient of the spectrum of the rapid shallow breathing index is higher for FG; also Lempel Ziv complexity mean values associated with the respiratory flow signal are bigger for FG. Patients were then classified with a pattern recognition neural network, obtaining 80% of correct classifications (81.6% for FG and 79.5% for SG).

Background: Often after biopsy a skin cancer appears to resolve clinically and a repeat biopsy may be done on the area in question before proceeding with further treatment. Objective: Our purpose was to assess the value of a subsequent biopsy in the treatment of skin cancers previously diagnosed by biopsy results. Methods: The results of a subsequent biopsy were compared with the results of Mohs micrographic surgery in 291 patients with biopsy-established basal cell carcinoma and squamous cell carcinoma. Pre-Mohs surgery curettings were examined in 60 of these patients to evaluate whether these could have caused false-negative Mohs results. Results: One hundred nineteen patients had a negative second biopsy, of which 75 (63%) had residual tumor at surgery. Eight of 60 patients in whom the curettings were examined had negative results from both biopsy and Mohs surgery; tumor in the curettings was shown in six of these eight patients (75%). Conclusion: This study suggests that 63% or more of subsequent biopsy specimens for skin cancer may yield false-negative results and casts doubt on the usefulness of a subsequent biopsy before surgery.

Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates the energy of each IMF and performs the detection based on an energy threshold and a minimum duration decision. The algorithm was tested in 9 invasive EEG records provided and validated by the Epilepsy Center of the University Hospital of Freiburg. In 90 segments analyzed (39 with epileptic seizures) the sensitivity and specificity obtained with the method were of 56.41% and 75.86% respectively. It could be concluded that EMD is a promissory method for epileptic seizure detection in EEG records.

In this work, it is proposed a technique for the feature extraction of electroencephalographic (EEG) signals for classification of mental tasks which is an important part in the development of Brain Computer Interfaces (BCI). The Empirical Mode Decomposition (EMD) is a method capable to process nonstationary and nonlinear signals as the EEG. This technique was applied in EEG signals of 7 subjects performing 5 mental tasks. For each mode obtained from the EMD and each EEG channel were computed six features: Root Mean Square (RMS), Variance, Shannon Entropy, Lempel-Ziv Complexity Value, and Central and Maximum Frequencies, obtaining a feature vector of 180 components. The Wilks' lambda parameter was applied for the selection of the most important variables reducing the dimensionality of the feature vector. The classification of mental tasks was performed using Linear Discriminate Analysis (LD) and Neural Networks (NN). With this method, the average classification over all subjects in database was 91+/-5% and 87+/-5% using LD and NN, respectively. It was concluded that the EMD allows getting better performances in the classification of mental tasks than the obtained with other traditional methods, like spectral analysis.

An apnea detection method based on spectral analysis was used to assess the performance of three ECG derived respiratory (EDR) signals. They were obtained on R wave area (EDR1), heart rate variability (EDR2) and R peak amplitude (EDR3) of ECG record in 8 patients with sleep apnea syndrome. The mean, central, peak and first quartile frequencies were computed from the spectrum every 1 min for each EDR. For each frequency parameter a threshold-based decision was carried out on every 1 min segment of the three EDR, classifying it as 'apnea' when its frequency value was below a determined threshold or as 'not apnea' in other cases. Results indicated that EDR1, based on R wave area has better performance in detecting apnea episodes with values of specificity (Sp) and sensitivity (Se) near 90%; EDR2 showed similar Sp but lower Se (78%); whereas EDR3 based on R peak amplitude did not detect appropriately the apneas episodes reaching Sp and Se values near 60%.

In this paper we compare three different spectral estimation techniques for the classification of mental tasks. These techniques are the standard periodogram, the Welch periodogram and the Burg method, applied to electroencephalographic (EEG) signals. For each one of these methods we compute two parameters: the mean power and the root mean square (RMS), in various frequency bands. The classification of the mental tasks was conducted with a linear discriminate analysis. The Welch periodogram and the Burg method performed better than the standard periodogram. The use of the RMS allows better classification accuracy than the obtained with the power of EEG signals.

As the incidence of nonmelanoma skin cancer (NMSC) continues to rise, topical therapies will be used with increasing frequency. Topical therapies are currently being utilized as primary or adjunctive means of treating an array of NMSCs. Although surgical therapies, such as Mohs Micrographic Surgery (MMS), remain the mainstay for tumor removal, topical therapy provides an alternative treatment modality for some skin cancer patients as well as serving as a useful adjunct to surgery. Topical therapies may also increase overall efficacy by treating subclinical lesions and identifying asymmetrical growth of NMSCs. In some patients, such as high-risk surgical candidates, they can be used to avoid surgery altogether or to minimize the extent of surgery. Topical therapies may also be helpful in a diagnostic manner. In instances where biopsy sites are equivocal, topical therapies may facilitate tumor identification prior to surgery.

The study of the mechanomyographic (MMG) signal of respiratory muscles is a promising technique in order to evaluate the respiratory muscles effort. The relationship between amplitude and power parameters of this signal with the respiratory effort performed during respiration is of great interest for researchers and physicians due to its diagnostic potentials. In this study, it was analyzed the MMG signal of the diaphragm muscle acquired by means of a capacitive accelerometer applied on the costal wall. The new methodology investigated was based in the calculation of the Shannon entropy of the MMG signal during the diaphragm muscle voluntary contraction. The method was tested in an animal model, with two incremental respiratory protocols performed by two non anesthetized mongrel dogs. The results obtained in the respiratory tests analyzed indicate that the Shannon entropy was superior to other amplitude parameter methods, obtaining higher correlation coefficients (with p-values lower than 0.001) with the mean and maximum inspiratory pressures. Furthermore in this study we have proposed a moving mode high pass filter in order to eliminate the very low frequency component recorded by the sensor and due to movement artifacts and the gross movement of the thorax during respiration. With this non linear filtering method we have obtained higher correlation coefficients (with both entropy and amplitude parameters) than with the Wavelet multiresolution technique proposed in a previous work.

Heart sound is often a serious source of noise in the analysis of respiratory sounds. The interference of heart sound is important when breath sounds are analyzed, since the intensity of heart sound is 1 to 10 times greater than the intensity of breath sound. Methods to reduce heart sound interference in breath sound analysis had been suggested. However, the majority of those methods require acquisition of an additional signal and knowledge of the spectral content of heart sound. In this paper it has been proposed an algorithm for the detection and adaptive filtering of heart sounds using only the sound signal and, minimizing distortion in the respiratory sound. The main components of the power spectral density (PSD) of the filtered tracheal sound are comparable with the PSD of the original signal. The experimental results shown reduction of the heart sound interference when the adaptive filter is applied. This kind of filter could facilitate the analysis and a better interpretation of the respiratory sound during spontaneous ventilation.

Background The current standard diagnostic procedure for basal cell carcinoma (BCC) is histologic examination after invasive biopsy. Reflectance-mode confocal microscopy (RCM) offers noninvasive high-resolution imaging of human skin in vivo. Objective The objective of this study was to explore the sensitivity and specificity of RCM for diagnosis of BCC. Methods This was a retrospective study of RCM images from 4 institutions of 152 skin lesions representing a variety of benign and malignant diagnoses. These 152 lesions were examined clinically, with biopsies recorded for all the 83 BCCs detected. Based on a previous study, a set of 5 histologically correlated confocal imaging criteria for diagnosing BCC was established, eg, the presence of elongated monomorphic nuclei. Blinded retrospective analysis of the images from the 152 lesions was carried out by a single novice reviewer to determine the sensitivity and specificity of these 5 RCM criteria for diagnosing BCC. The accuracy of combining the probability of BCC based on examination of clinical photographs with the predicted probability of BCC based on confocal criteria was also evaluated. Results The presence of two or more criteria is 100% sensitive for the diagnosis of BCC, and with 4 or more RCM criteria present the specificity was 95.7% and sensitivity was 82.9%. These results were found to have little variability across study sites and across BCC subtypes. The combination of RCM with photography-based predictions of clinical probability of BCC significantly improved the accuracy for noninvasive diagnosis of BCC. Conclusion RCM offers a sensitive and specific tool for the noninvasive diagnosis of BCC in vivo.

Analysis of sternomastoid muscle (SMM) could become a non-invasive method for diagnosis of chronic obstructive pulmonary disease (COPD). This work studies electromyographic (EMG) and vibromyographic (VMG) signals from SMM during respiratory load tests, in six COPD patients and six normal subjects. These signals are related to electrical and mechanical activity of this muscle that could be different in patients and normal subjects. Time and frequency analysis are performed by means of root-mean-square (RMS) values, cross-correlation of EMG and VMG (EVC), mean and median frequency, and ratio of high and low frequency components (H/L). RMS values and H/L ratio show different behaviour at the end of respiratory tests between groups. Parameters calculated from EVC during tests are different in patient and control group.

© 2013 IEEE. This study evaluates the onset and offset of neural inspiratory time estimated from surface diaphragm electromyographic (EMGdi) recordings. EMGdi and airflow signals were recorded in ten healthy subjects according to two respiratory protocols based on respiratory rate (RR) increments, from 15 to 40 breaths per minute (bpm), and fractional inspiratory time (Ti/Ttot) decrements, from 0.54 to 0.18. The analysis of EMGdi signal amplitude is an alternative approach for the quantification of neural respiratory drive. The EMGdi amplitude was estimated using the fixed sample entropy computed over a 250 ms moving window of the EMGdi signal (EMGdifse). The neural onset was detected through a dynamic threshold over the EMGdifse using the kernel density estimation method, while neural offset was detected by finding when the EMGdifse had decreased to 70% of the peak value reached during inspiration. The Bland-Altman analysis between airflow and neural onsets showed a global bias of 46 ms in the RR protocol and 22 ms in the Ti/Ttot protocol. The Bland-Altman analysis between airflow and neural offsets reveals a global bias of 11 ms in the RR protocol and -2 ms in the Ti/T tot protocol. The relationship between pairs of RR values (Pearson's correlation coefficient of 0.99, Bland-=Altman limits of -2.39 to 2.41 bpm, and mean bias of 0.01 bpm) and between pairs of Ti/Ttot values (Pearson's correlation coefficient of 0.86, Bland-Altman limits of -0.11 to 0.10, and mean bias of -0.01) showed a good agreement. In conclusion, we propose a method for determining neural onset and neural offset based on noninvasive recordings of the electrical activity of the diaphragm that requires no filtering of cardiac muscle interference.

The study of mechanomyographic (MMG) signals of respiratory muscles is a promising technique in order to evaluate the respiratory muscular effort. In this work MMG signals from left and right hemidiaphragm (MMGl and MMGr, respectively) acquired during a respiratory protocol have been analyzed. The acquisition of both MMG signals was carried out by means of two capacitive accelerometers placed on both left and right sides of the costal wall. The signals were recorded in a group of six patients with Chronic Obstructive Pulmonary Disease (COPD). It has been observed that with the increase of inspiratory pressure it takes place an increase of the amplitude and a displacement toward low frequencies in both left and right MMG signals. Furthermore, it has been seen that the increase of amplitude and the decrease of frequency in MMG signals are more pronounced in severe COPD patients. This behaviour is similar for both MMGl and MMGr signals. Results suggest that the use of MMG signals could be potentially useful for the evaluation of the respiratory muscular function in COPD patients.

Wireless sensors are an emerging technology that allows to assist physicians in the monitoring of patients health status. This approach can be used for the non-invasive recording of the electrical respiratory muscle activity of the diaphragm (EMGdi). In this work, we acquired the EMGdi signal of a healthy subject performing an inspiratory load test. To this end, the EMGdi activity was captured from a single channel of electromyography using a wireless platform which was compared with the EMGdi and the inspiratory mouth pressure (Pmouth) recorded with a conventional lab equipment. From the EMGdi signal we were able to evaluate the neural respiratory drive, a biomarker used for assessing the respiratory muscle function. In addition, we evaluated the breathing movement and the cardiac activity, estimating two cardio-respiratory parameters: the respiratory rate and the heart rate. The correlation between the two EMGdi signals and the Pmouth improved with increasing the respiratory load (Pearson's correlation coefficient ranges from 0.33 to 0.85). The neural respiratory drive estimated from both EMGdi signals showed a positive trend with an increase of the inspiratory load and being higher in the conventional EMGdi recording. The respiratory rate comparison between measurements revealed similar values of around 16 breaths per minute. The heart rate comparison showed a root mean error of less than 0.2 beats per minute which increased when incrementing the inspiratory load. In summary, this preliminary work explores the use of wireless devices to record the muscle respiratory activity to derive several physiological parameters. Its use can be an alternative to conventional measuring systems with the advantage of being portable, lightweight, flexible and operating at low energy. This technology can be attractive for medical staff and may have a positive impact in the way healthcare is being delivered.