Staff member


Leonardo Sarlabous Uranga

Postdoctoral Researcher
Biomedical Signal Processing and Interpretation
lsarlabous@ibecbarcelona.eu
+34 934 020 559
Staff member publications

Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2017). Onset and offset estimation of the neural inspiratory time in surface diaphragm electromyography: A pilot study in healthy subjects IEEE Journal of Biomedical and Health Informatics Epub ahead of print

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 diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of neural respiratory drive (NRD). 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/Ttot 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 non-invasive recordings of the electrical activity of the diaphragm that requires no filtering of cardiac muscle interference.

Keywords: Kernel density estimation (KDE),, Surface diaphragm electromyographic,, (EMGdi) signal,, Inspiratory time,, Neural respiratory drive (NRD),, Neural inspiratory time,, Fixed sample entropy (fSampEn)


Sarlabous, Leonardo, Torres, Abel, Fiz, José A., Martínez-Llorens, Juana M., Gea, Joaquim, Jané, Raimon, (2017). Inspiratory muscle activation increases with COPD severity as confirmed by non-invasive mechanomyographic analysis PLoS ONE 12, (5), e0177730

There is a lack of instruments for assessing respiratory muscle activation during the breathing cycle in clinical conditions. The aim of the present study was to evaluate the usefulness of the respiratory muscle mechanomyogram (MMG) for non-invasively assessing the mechanical activation of the inspiratory muscles of the lower chest wall in both patients with chronic obstructive pulmonary disease (COPD) and healthy subjects, and to investigate the relationship between inspiratory muscle activation and pulmonary function parameters. Both inspiratory mouth pressure and respiratory muscle MMG were simultaneously recorded under two different respiratory conditions, quiet breathing and incremental ventilatory effort, in 13 COPD patients and 7 healthy subjects. The mechanical activation of the inspiratory muscles was characterised by the non-linear multistate Lempel–Ziv index (MLZ) calculated over the inspiratory time of the MMG signal. Subsequently, the efficiency of the inspiratory muscle mechanical activation was expressed as the ratio between the peak inspiratory mouth pressure to the amplitude of the mechanical activation. This activation estimated using the MLZ index correlated strongly with peak inspiratory mouth pressure throughout the respiratory protocol in both COPD patients (r = 0.80, p<0.001) and healthy (r = 0.82, p<0.001). Moreover, the greater the COPD severity in patients, the greater the level of muscle activation (r = -0.68, p = 0.001, between muscle activation at incremental ventilator effort and FEV1). Furthermore, the efficiency of the mechanical activation of inspiratory muscle was lower in COPD patients than healthy subjects (7.61±2.06 vs 20.42±10.81, respectively, p = 0.0002), and decreased with increasing COPD severity (r = 0.78, p<0.001, between efficiency of the mechanical activation at incremental ventilatory effort and FEV1). These results suggest that the respiratory muscle mechanomyogram is a good reflection of inspiratory effort and can be used to estimate the efficiency of the mechanical activation of the inspiratory muscles. Both, inspiratory muscle activation and inspiratory muscle mechanical activation efficiency are strongly correlated with the pulmonary function. Therefore, the use of the respiratory muscle mechanomyogram can improve the assessment of inspiratory muscle activation in clinical conditions, contributing to a better understanding of breathing in COPD patients.


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2016). Improvement in neural respiratory drive estimation from diaphragm electromyographic signals using fixed sample entropy IEEE Journal of Biomedical and Health Informatics 20, (2), 476-485

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 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 work, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to 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???0.12, 0.27???0.11 and 0.11???0.13, respectively. Whereas at 33 cmH2O (maximum inspiratory load) were 0.83???0.02, 0.76???0.07 and 0.61???0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.

Keywords: Electromyography, diaphragm muscle, neural respiratory drive


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2016). Evaluating respiratory muscle activity using a wireless sensor platform Engineering in Medicine and Biology Society (EMBC) 38th Annual International Conference of the IEEE , IEEE (Orlando, USA) , 5769-5772

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.

Keywords: Biomedical monitoring, Electrodes, Medical services, Monitoring, Muscles, Wireless communication, Wireless sensor networks


Estrada, L., Torres, A., Garcia-Casado, J., Sarlabous, L., Prats-Boluda, G., Jané, R., (2016). Time-frequency representations of the sternocleidomastoid muscle electromyographic signal recorded with concentric ring electrodes Engineering in Medicine and Biology Society (EMBC) 38th Annual International Conference of the IEEE , IEEE (Orlando, USA) , 3785-3788

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 time-frequency 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.

Keywords: Electrodes, Interference, Kernel, Mouth, Muscles, Spectrogram, Time-frequency analysis


Sarlabous, Leonardo, Torres, Abel, Fiz, José A., Gea, Joaquim, Martínez-Llorens, Juana M., Jané, Raimon, (2015). Efficiency of mechanical activation of inspiratory muscles in COPD using sample entropy European Respiratory Journal 46, (6), 1808-1811

Respiratory muscle dysfunction is a common problem in patients with chronic obstructive pulmonary disease (COPD) and has mostly been related to pulmonary hyperinflation [1, 2]. Associated diaphragm shortening and deleterious changes in the muscle force-length relationship cause a reduction in the muscles' capacity to generate pressure, placing them at a mechanical disadvantage [1, 3]. Specifically, both inspiratory muscle strength and mechanical efficiency may be reduced in COPD patients [1, 4–6], although, at isovolume, the contractile strength of the diaphragm in COPD is preserved or may even be improved in some cases [7]. The ratio between transdiaphragmatic pressure and electrical diaphragm activity has been used as a measure of respiratory muscle efficiency [8, 9]. However, in clinical practice, it is complex to measure this parameter directly, as invasive measures are required and these are uncomfortable for patients [4].


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2015). EMG-derived respiration signal using the fixed sample entropy during an Inspiratory load protocol Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 1703-1706

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.

Keywords: Band-pass filters, Electrocardiography, Electromyography, Entropy, Mouth, Muscles, Protocols


Estrada, L., Torres, A., Garcia-Casado, J., Sarlabous, L., Prats-Boluda, G., Jané, R., (2015). Evaluation of sternocleidomastoid muscle activity by electromyography recorded with concentric ring electrodes CASEIB Proceedings XXXIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB 2015) , Sociedad Española de Ingeniería Biomédica (Madrid, Spain) , 183-186

Los sonidos adventicios continuos (CAS) son uno de los principales síntomas del asma. Dada su importancia clínica, el análisis de estas señales requiere del uso de técnicas que permitan segmentarlas y caracterizarlas con una precisión alta. Sin embargo, la mayoría de técnicas propuestas anteriormente estaban basadas en el análisis de Fourier o wavelet, técnicas que tienen una resolución limitada a priori y son altamente dependientes de la amplitud de los CAS. En este estudio se presenta una técnica alternativa para el análisis de CAS basada en el espectro de Hilbert. El método presentado combina la descomposición empírica en modos por conjuntos con el estimador de Kay de la frecuencia instantánea, para obtener una representación tiempo-frecuencia con una alta concentración de energía y una resolución temporal y frecuencial elevada. Con el fin de mostrar las ventajas que ofrece el método presentado, se ha aplicado a cuatro señales de sonidos respiratorios registradas en pacientes asmáticos que contienen distintos tipos de CAS, reforzando la hipótesis confirmada en nuestro estudio previo de que el espectro de Hilbert permite segmentar y caracterizar los CAS con mayor precisión que otras técnicas tradicionales ampliamente utilizadas, como el espectrograma.


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2015). Respiratory signal derived from the smartphone built-in accelerometer during a Respiratory Load Protocol Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 6768-6771

The scope of our work focuses on investigating the potential use of the built-in accelerometer of the smartphones for the recording of the respiratory activity and deriving the respiratory rate. Five healthy subjects performed an inspiratory load protocol. The excursion of the right chest was recorded using the built-in triaxial accelerometer of a smartphone along the x, y and z axes and with an external uniaxial accelerometer. Simultaneously, the respiratory airflow and the inspiratory mouth pressure were recorded, as reference respiratory signals. The chest acceleration signal recorded in the z axis with the smartphone was denoised using a scheme based on the ensemble empirical mode decomposition, a noise data assisted method which decomposes nonstationary and nonlinear signals into intrinsic mode functions. To distinguish noisy oscillatory modes from the relevant modes we use the detrended fluctuation analysis. We reported a very strong correlation between the acceleration of the z axis of the smartphone and the reference accelerometer across the inspiratory load protocol (from 0.80 to 0.97). Furthermore, the evaluation of the respiratory rate showed a very strong correlation (0.98). A good agreement was observed between the respiratory rate estimated with the chest acceleration signal from the z axis of the smartphone and with the respiratory airflow signal: Bland-Altman limits of agreement between -1.44 and 1.46 breaths per minute with a mean bias of -0.01 breaths per minute. This preliminary study provides a valuable insight into the use of the smartphone and its built-in accelerometer for respiratory monitoring.

Keywords: Acceleration, Accelerometers, Correlation, Empirical mode decomposition, Fluctuations, Protocols, Time series analysis


Sarlabous, Leonardo, Torres, Abel, Fiz, J. A., Jané, Raimon, (2014). Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values PLoS ONE 9, (2), e88902

The analysis of amplitude parameters of the diaphragm mechanomyographic (MMGdi) signal is a non-invasive technique to assess respiratory muscle effort and to detect and quantify the severity of respiratory muscle weakness. The amplitude of the MMGdi signal is usually evaluated using the average rectified value or the root mean square of the signal. However, these estimations are greatly affected by the presence of cardiac vibration or mechanocardiographic (MCG) noise. In this study, we present a method for improving the estimation of the respiratory muscle effort from MMGdi signals that is robust to the presence of MCG. This method is based on the calculation of the sample entropy using fixed tolerance values (fSampEn), that is, with tolerance values that are not normalized by the local standard deviation of the window analyzed. The behavior of the fSampEn parameter was tested in synthesized mechanomyographic signals, with different ratios between the amplitude of the MCG and clean mechanomyographic components. As an example of application of this technique, the use of fSampEn was explored also in recorded MMGdi signals, with different inspiratory loads. The results with both synthetic and recorded signals indicate that the entropy parameter is less affected by the MCG noise, especially at low signal-to-noise ratios. Therefore, we believe that the proposed fSampEn parameter could improve estimates of respiratory muscle effort from MMGdi signals with the presence of MCG interference.


Estrada, Luis, Torres, Abel, Sarlabous, Leonardo, Fiz, Jose A., Gea, Joaquim, Martinez-Llorens, Juana, Jané, Raimon, (2014). Estimation of bilateral asynchrony between diaphragm mechanomyographic signals in patients with Chronic Obstructive Pulmonary Disease Engineering in Medicine and Biology Society (EMBC) 36th Annual International Conference of the IEEE , IEEE (Chicago, USA) , 3813-3816

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.

Keywords: Accelerometers, Diseases, Estimation, Fatigue, IP networks, Protocols, Transforms


Sarlabous, L., Torres, A., Fiz, J.A., Gea, J., Martínez-Llorens, J.M., Jané, R., (2014). Relación entre la presión inspiratoria pico y la activación mecánica de los músculos inspiratorios durante respiración tranquila en pacientes con EPOC CASEIB Proceedings XXXII Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB 2014) , Sociedad Española de Ingeniería Biomédica (Barcelona, Spain) , 1-4

En la enfermedad pulmonar obstructiva crónica (EPOC) la fuerza muscular inspiratoria (FMI) y la eficiencia mecánica de los músculos inspiratorios (EMMI) podrían verse reducidas como consecuencia de la hiperinsuflación. En este trabajo se registraron la presión inspiratoria en boca (PIpico) y la activación mecánica de los músculos inspiratorios en 10 pacientes EPOC severos y muy severos, durante respiración tranquila. Para determinar la activación mecánica de los músculos inspiratorios se empleó la señal mecanomiográfica diafragmática: MMGdi. La amplitud de la señal MMGdi fue estimada a través de índices lineales (ARV: valor rectificado medio) y no lineales (MLZ: Lempel-Ziv multiestado, y fSampEn: entropía muestral con valores de tolerancia fijos). Nuestra hipótesis es que el ratio entre PIpico, que refleja la FMI, y la amplitud de la señal MMGdi constituye una expresión de la EMMI. Los resultados obtenidos muestran ligeras diferencias entre la PIpico registrada en EPOC severos y muy severos, así como una correlación débil a moderada con los parámetros de función pulmonar y los índices estudiados. Sin embargo, mientras mayor es el grado de severidad (que supone un mayor grado de hiperinsuflación) mayor es el nivel de activación mecánica de los músculos inspiratorios. La activación mecánica de los músculos inspiratorios y la EMMI estimadas mediante MLZ estuvieron mejor correlacionadas con la función pulmonar que ARV y fSampEn. Por consiguiente, la estimación de la actividad mecánica del diafragma mediante el MLZ de la señal MMGdi podría mejorar la estimación no invasiva de la FMI y la EMMI, incluso para niveles muy bajos de esfuerzo inspiratorio.


Estrada, L., Torres, A., Sarlabous, L., Fiz, J. A., Jané, R., (2014). Respiratory rate detection by empirical mode decomposition method applied to diaphragm mechanomyographic signals Engineering in Medicine and Biology Society (EMBC) 36th Annual International Conference of the IEEE , IEEE (Chicago, USA) , 3204-3207

Non-invasive evaluation of respiratory activity is an area of increasing research interest, resulting in the appearance of new monitoring techniques, ones of these being based on the analysis of the diaphragm mechanomyographic (MMGdi) signal. The MMGdi signal can be decomposed into two parts: (1) a high frequency activity corresponding to lateral vibration of respiratory muscles, and (2) a low frequency activity related to excursion of the thoracic cage. The purpose of this study was to apply the empirical mode decomposition (EMD) method to obtain the low frequency of MMGdi signal and selecting the intrinsic mode functions related to the respiratory movement. With this intention, MMGdi signals were acquired from a healthy subject, during an incremental load respiratory test, by means of two capacitive accelerometers located at left and right sides of rib cage. Subsequently, both signals were combined to obtain a new signal which contains the contribution of both sides of thoracic cage. Respiratory rate (RR) measured from the mechanical activity (RRMmg) was compared with that measured from inspiratory pressure signal (RRP). Results showed a Pearson's correlation coefficient (r = 0.87) and a good agreement (mean bias = -0.21 with lower and upper limits of -2.33 and 1.89 breaths per minute, respectively) between RRmmg and RRP measurements. In conclusion, this study suggests that RR can be estimated using EMD for extracting respiratory movement from low mechanical activity, during an inspiratory test protocol.

Keywords: Accelerometers, Band-pass filters, Biomedical measurement, Empirical mode decomposition, Estimation, IP networks, Muscles


Sarlabous, L., Torres, A., Fiz, J. A., Morera, J., Jané, R., (2013). Index for estimation of muscle force from mechanomyography based on the Lempel-Ziv algorithm Journal of Electromyography and Kinesiology 23, (3), 548-557

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.

Keywords: Diaphragm, Electromyography, Lempel-Ziv, Mechanomyography, Muscle force, Respiratory muscles


Sarlabous, L., Torres, A., Fiz, J. A., Jané, R., (2013). Cardiac interference reduction in diaphragmatic MMG signals during a Maintained Inspiratory Pressure Test Engineering in Medicine and Biology Society (EMBC) 35th Annual International Conference of the IEEE , IEEE (Osaka, Japan) , 3845-3848

A recursive least square (RLS) adaptive filtering algorithm for reduction of cardiac interference in diaphragmatic mecanomyographic (MMGdi) signals is addressed in this paper. MMGdi signals were acquired with a capacitive accelerometer placed between 7th and 8th intercostal spaces, on the right anterior axillary line, during a maintained inspiratory pressure test. Subjects were asked to maintain a constant inspiratory pressure with a mouthpiece connected to a closed tube (without breathing). This maneuver was repeated at five different contraction efforts: apnea (no effort), 20 cmH2O, 40 cmH2O, 60 cmH2O and maximum voluntary contraction. An adaptive noise canceller (ANC) using the RLS algorithm was applied on the MMGdi signals. To evaluate the behavior of the ANC, the MMGdi signals were analyzed in two segments: with and without cardiac interference (WCI and NCI, respectively). In both segments it was analyzed the power spectral density (PSD), and the ARV and RMS amplitude parameters for each contraction effort. With the proposed ANC algorithm the amplitude parameters of the WCI segments were reduced to a level similar to the one of the NCI segments. The obtained results showed that ANC using the RLS algorithm allows to significantly reduce the cardiac interference in MMGdi signals.


Torres, A., Sarlabous, L., Fiz, J.A., Jané, R., (2012). Evaluación de diferentes algoritmos adaptativos para la atenuación de la interferencia cardiaca en señales mecanomiográficas simuladas Libro de Actas XXX CASEIB 2012 XXX Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB2012) , Sociedad Española de Ingeniería Biomédica (San Sebastián, Spain) , 1-4

El estudio de la señal mecanomiográfica del músculo diafragma (MMGdi) es una técnica utilizada para evaluar el esfuerzo muscular respiratorio. El estudio de la relación entre los parámetros de amplitud y frecuencia de esta señal con el esfuerzo respiratorio realizado es de gran interés para investigadores y médicos debido a su potencial de diagnóstico sobre la función muscular respiratoria. Las señales MMGdi se ven afectas por una componente interferente correspondiente a la actividad vibratoria cardíaca o interferencia mecanocardiográfica (MCG). Para reducir o atenuar esta actividad se puede utilizar una cancelación adaptativa de interferencias (CAI). En este trabajo se ha evaluado el esquema de CAI propuesto mediante una señal MMGdi sintética generada con amplitud y frecuencia controlada a la que se le ha añadido ruido MCG real adquirido durante apnea. El coeficiente de correlación de Pearson (r) entre la amplitud y la frecuencia teóricas, y la amplitud y la frecuencia evaluadas mediante el RMS y la frecuencia media del espectro, respectivamente, disminuye considerablemente cuando se añade el ruido cardíaco a la señal MMGdi sintética: pasa de 0.95 a 0.87 para la amplitud, y de 0.97 a 0.76 para la frecuencia. Con los algoritmos de CAI propuestos el efecto del ruido MCG sobre la actividad MMGdi se reduce considerablemente (r de 0.93 para la amplitud y 0.97 para la frecuencia media). El método de CAI propuesto en este trabajo es una técnica adecuada para atenuar la interferencia MCG en señales MMGdi.


Sarlabous, L., Torres, A., Fiz, J. A., Morera, J., Jané, R., (2012). Evaluation and adaptive attenuation of the cardiac vibration interference in mechanomyographic signals Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 3400-3403

The study of the mechanomyographic signal of the diaphragm muscle (MMGdi) is a promising technique in order to evaluate the respiratory muscles effort. The relationship between amplitude and frequency parameters of this signal with the respiratory effort performed during respiration is of great interest for researchers and physicians due to its diagnostic potentials. However, MMGdi signals are frequently contaminated by a cardiac vibration or mechanocardiographic (MCG) signal. An adaptive noise cancellation (ANC) can be used to reduce the MCG interference in the recorded MMGdi activity. In this paper, it is evaluated the proposed ANC scheme by means of a synthetic MMGdi signal with a controlled MCG interference. The Pearson's correlation coefficient (PCC) between both root mean square (RMS) and mean frequency (fm) of the synthetic MMGdi signal are considerably reduced with the presence of cardiac vibration noise (from 0.95 to 0.87, and from 0.97 to 0.76, respectively). With the ANC algorithm proposed the effect of the MCG noise on the amplitude and frequency of MMG parameters is reduced considerably (PCC of 0.93 and 0.97 for the RMS and fm, respectively). The ANC method proposed in this work is an interesting technique to attenuate the cardiac interference in respiratory MMG signals. Further investigation should be carried out to evaluate the performance of the ANC algorithm in real MMGdi signals.

Keywords: Adaptive filters, Frequency modulation, Interference, Muscles, Noise cancellation, Vibrations, Cardiology, Medical signal processing, Muscle, Signal denoising, ANC algorithm, MCG interference, Pearson correlation coefficient, Adaptive noise cancellation, Cardiac vibration interference, Cardiac vibration noise, Diaphragm muscle, Mechanocardiographic signal, Mechanomyographic signals, Respiratory muscles effort


Sarlabous, L., Torres, A., Fiz, J.A., Jané, R., (2012). Reducción de interferencia cardíaca en señales MMG diafragmáticas registradas durante un protocolo de carga incremental sostenida mediante el algoritmo RLS Libro de Actas XXX CASEIB 2012 XXX Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB2012) , Sociedad Española de Ingeniería Biomédica (San Sebastián, Spain) , 1-4

En este trabajo se aplicó el filtrado adaptativo empleando el algoritmo RLS para reducir la interferencia de origen cardíaco en las señales mecanomiográficas diafragmáticas (MMGdi) registras durante un protocolo de carga incremental sostenida. La señal MMGdi fue dividida en tramos con y sin ruido cardíaco, CRC y SRC, respectivamente. En cada tramo se estudio el comportamiento de la densidad espectral de potencia (DEP), y los parámetros de amplitud RMS y ARV para cada una de las cargas inspiratorias que conforman el test. Los resultados obtenidos, empleando filtro adaptativo de orden =50, con el algoritmo RLS y valores de - = 1, permiten reducir considerablemente la interferencia cardíaca en las señales MMGdi.


Sarlabous, L., Torres, A., Fiz, J.A., Gea, J., Martinez-Llorens, J.M., Morera, J., Jané, R. , (2011). Evaluation of the respiratory muscles efficiency during an incremental flow respiratory test Engineering in Medicine and Biology Society 33rd Annual International Conference of the IEEE EMBS , IEEE (Boston, USA) Engineering in Medicine and Biology Society, 3820-3823

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.

Keywords: -----


Sarlabous, L., Torres, A., Fiz, J. A., Gea, J., Marti nez-Llorens, J. M., Morera, J., Jané, R., (2010). Interpretation of the approximate entropy using fixed tolerance values as a measure of amplitude variations in biomedical signals Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 5967-5970

A new method for the quantification of amplitude variations in biomedical signals through moving approximate entropy is presented. Unlike the usual method to calculate the approximate entropy (ApEn), in which the tolerance value (r) varies based on the standard deviation of each moving window, in this work ApEn has been computed using a fixed value of r. We called this method, moving approximate entropy with fixed tolerance values: ApEn/sub f/. The obtained results indicate that ApEn/sub f/ allows determining amplitude variations in biomedical data series. These amplitude variations are better determined when intermediate values of tolerance are used. The study performed in diaphragmatic mechanomyographic signals shows that the ApEn/sub f/ curve is more correlated with the respiratory effort than the standard RMS amplitude parameter. Furthermore, it has been observed that the ApEn/sub f/ parameter is less affected by the existence of impulsive, sinusoidal, constant and Gaussian noises in comparison with the RMS amplitude parameter.

Keywords: Practical, Theoretical or Mathematical/ biomechanics, Entropy, Gaussian noise, Medical signal processing, Muscle, Random processes/ approximate entropy interpretation, Fixed tolerance values, Diaphragmatic mechanomyographic signals, ApEnf curve, Respiratory effort, Gaussian noises


Torres, A., Sarlabous, L., Fiz, j A., Gea, J., Marti nez-Llorens, J. M., Morera, J., Jané, R., (2010). Noninvasive measurement of inspiratory muscle performance by means of diaphragm muscle mechanomyographic signals in COPD patients during an incremental load respiratory test Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 2493-2496

The study of mechanomyographic (MMG) signals of respiratory muscles is a promising noninvasive technique in order to evaluate the respiratory muscular effort and efficiency. In this work, the MMG signal of the diaphragm muscle it is evaluated in order to assess the respiratory muscular function in Chronic Obstructive Pulmonary Disease (COPD) patients. The MMG signals from left and right hemidiaphragm were acquired using two capacitive accelerometers placed on both left and right sides of the costal wall surface. The MMG signals and the inspiratory pressure signal were acquired while the COPD patients carried out an inspiratory load respiratory test. The population of study is composed of a group of 6 patients with severe COPD (FEV1>50% ref and DLCO<50% ref). We have found high positive correlation coefficients between the maximum inspiratory pressure (IPmax) developed in a respiratory cycle and different amplitude parameters of both left and right MMG signals (RMS, left: 0.68+/-0.11 - right: 0.69+/-0.12; Re nyi entropy, left: - 0.73+/-0.10 - right: 0.77+/-0.08; Multistate Lempel-Ziv, left: 0.73+/-0.17 - right: 0.74+/-0.08), and negative correlation between the Pmax and the maximum frequency of the MMG signal spectrum (left: -0.39+/-0.19 - right: -0.65+/-0.09). Furthermore, we found that the slope of the evolution of the MMG amplitude parameters, as the load increases during the respiratory test, has positive correlation with the %FEV1/FVC pulmonary function test parameter of the six COPD patients analyzed (RMS, left: 0.38 - right: 0.41; Re nyi entropy, left: 0.45 - right: 0.63; Multistate Lempel-Ziv, left: 0.39 - right: 0.64). These results suggest that the information provided by MMG signals could be used in order to evaluate the respiratory effort and the muscular efficiency in COPD patients.

Keywords: Accelerometers, Biomechanics, Biomedical measurement, Diseases, Medical signal processing, Muscle


Sarlabous, L., Torres, A., Fiz, J. A., Gea, J., Martinez-Llorens, J. M., Jané, R., (2009). Evaluation of the respiratory muscular function by means of diaphragmatic mechanomyographic signals in COPD patients Engineering in Medicine and Biology Society (EMBC) 31st Annual International Conference of the IEEE , IEEE (Minneapolis, USA) , 3925-3928

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.

Keywords: -----


Sarlabous, L., Torres, A., Fiz, J. A., Gea, J., Galdiz, J. B., Jané, R., (2009). Multistate Lempel-Ziv (MLZ) index interpretation as a measure of amplitude and complexity changes Engineering in Medicine and Biology Society (EMBC) 31st Annual International Conference of the IEEE , IEEE (Minneapolis, USA) , 4375-4378

The Lempel-Ziv complexity (LZ) has been widely used to evaluate the randomness of finite sequences. In general, the LZ complexity has been used to determine the complexity grade present in biomedical signals. The LZ complexity is not able to discern between signals with different amplitude variations and similar random components. On the other hand, amplitude parameters, as the root mean square (RMS), are not able to discern between signals with similar power distributions and different random components. In this work, we present a novel method to quantify amplitude and complexity variations in biomedical signals by means of the computation of the LZ coefficient using more than two quantification states, and with thresholds fixed and independent of the dynamic range or standard deviation of the analyzed signal: the Multistate Lempel-Ziv (MLZ) index. Our results indicate that MLZ index with few quantification levels only evaluate the complexity changes of the signal, with high number of levels, the amplitude variations, and with an intermediate number of levels informs about both amplitude and complexity variations. The study performed in diaphragmatic mechanomyographic signals shows that the amplitude variations of this signal are more correlated with the respiratory effort than the complexity variations. Furthermore, it has been observed that the MLZ index with high number of levels practically is not affected by the existence of impulsive, sinusoidal, constant and Gaussian noises compared with the RMS amplitude parameter.

Keywords: -----


Comments are closed