Noninvasive Assessment of Neuromechanical Coupling and Mechanical Efficiency of Parasternal Intercostal Muscle during Inspiratory Threshold Loading.

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.

Performance Evaluation of Fixed Sample Entropy in Myographic Signals for Inspiratory Muscle Activity Estimation.

Fixed sample entropy (fSampEn) has been successfully applied to myographic signals for inspiratory muscle activity estimation, attenuating interference from cardiac activity. However, several values have been suggested for fSampEn parameters depending on the application, and there is no consensus standard for optimum values. This study aimed to perform a thorough evaluation of the performance of the most relevant fSampEn parameters in myographic respiratory signals, and to propose, for the first time, a set of optimal general fSampEn parameters for a proper estimation of inspiratory muscle activity. Different combinations of fSampEn parameters were used to calculate fSampEn in both non-invasive and the gold standard invasive myographic respiratory signals. All signals were recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing, thus allowing the performance of fSampEn to be evaluated for a variety of inspiratory muscle activation levels. The performance of fSampEn was assessed by means of the cross-covariance of fSampEn time-series and both mouth and transdiaphragmatic pressures generated by inspiratory muscles. A set of optimal general fSampEn parameters was proposed, allowing fSampEn of different subjects to be compared and contributing to improving the assessment of inspiratory muscle activity in health and disease.

Estimation of Gait Parameters in Huntington's Disease Using Wearable Sensors in the Clinic and Free-living Conditions.

In Huntington's disease (HD), wearable inertial sensors could capture subtle changes in motor function. However, disease-specific validation of methods is necessary. This study presents an algorithm for walking bout and gait event detection in HD using a leg-worn accelerometer, validated only in the clinic and deployed in free-living conditions. Seventeen HD participants wore shank- and thigh-worn tri-axial accelerometers, and a wrist-worn device during two-minute walk tests in the clinic, with video reference data for validation. Thirteen participants wore one of the thigh-worn tri-axial accelerometers (AP: ActivPAL4) and the wrist-worn device for 7 days under free-living conditions, with proprietary AP data used as reference. Gait events were detected from shank and thigh acceleration using the Teager-Kaiser energy operator combined with unsupervised clustering. Estimated step count (SC) and temporal gait parameters were compared with reference data. In the clinic, low mean absolute percentage errors were observed for stride (shank/thigh: 0.6/0.9%) and stance (shank/thigh: 3.3/7.1%) times, and SC (shank/thigh: 3.1%). Similar errors were observed for proprietary AP SC (3.2%), with higher errors observed for the wrist-worn device (10.9%). At home, excellent agreement was observed between the proposed algorithm and AP software for SC and time spent walking (ICC [Formula: see text]). The wrist-worn device overestimated SC by 34.2%. The presented algorithm additionally allowed stride and stance time estimation, whose variability correlated significantly with clinical motor scores. The results demonstrate a new method for accurate estimation of HD gait parameters in the clinic and free-living conditions, using a single accelerometer worn on either the thigh or shank.

Differences in acoustic features of cough by pneumonia severity in patients with COVID-19: a cross-sectional study.

Background: Acute respiratory syndrome due to coronavirus 2 (SARS-CoV-2) is characterised by heterogeneous levels of disease severity. It is not necessarily apparent whether a patient will develop severe disease or not. This cross-sectional study explores whether acoustic properties of the cough sound of patients with coronavirus disease 2019 (COVID-19), the illness caused by SARS-CoV-2, correlate with their disease and pneumonia severity, with the aim of identifying patients with severe disease. Methods: Voluntary cough sounds were recorded using a smartphone in 70 COVID-19 patients within the first 24 h of their hospital arrival, between April 2020 and May 2021. Based on gas exchange abnormalities, patients were classified as mild, moderate or severe. Time- and frequency-based variables were obtained from each cough effort and analysed using a linear mixed-effects modelling approach. Results: Records from 62 patients (37% female) were eligible for inclusion in the analysis, with mild, moderate and severe groups consisting of 31, 14 and 17 patients respectively. Five of the parameters examined were found to be significantly different in the cough of patients at different disease levels of severity, with a further two parameters found to be affected differently by the disease severity in men and women. Conclusions: We suggest that all these differences reflect the progressive pathophysiological alterations occurring in the respiratory system of COVID-19 patients, and potentially would provide an easy and cost-effective way to initially stratify patients, identifying those with more severe disease, and thereby most effectively allocate healthcare resources.

Noninvasive Assessment of Neuromechanical and Neuroventilatory Coupling in COPD.

This study explored the use of parasternal second intercostal space and lower intercostal space surface electromyogram (sEMG) and surface mechanomyogram (sMMG) recordings (sEMGpara and sMMGpara, and sEMGlic and sMMGlic, respectively) to assess neural respiratory drive (NRD), neuromechanical (NMC) and neuroventilatory (NVC) coupling, and mechanical efficiency (MEff) noninvasively in healthy subjects and chronic obstructive pulmonary disease (COPD) patients. sEMGpara, sMMGpara, sEMGlic, sMMGlic, mouth pressure (Pmo), and volume (Vi) were measured at rest, and during an inspiratory loading protocol, in 16 COPD patients (8 moderate and 8 severe) and 9 healthy subjects. Myographic signals were analyzed using fixed sample entropy and normalized to their largest values (fSEsEMGpara%max, fSEsMMGpara%max, fSEsEMGlic%max, and fSEsMMGlic%max). fSEsMMGpara%max, fSEsEMGpara%max, and fSEsEMGlic%max were significantly higher in COPD than in healthy participants at rest. Parasternal intercostal muscle NMC was significantly higher in healthy than in COPD participants at rest, but not during threshold loading. Pmo-derived NMC and MEff ratios were lower in severe patients than in mild patients or healthy subjects during threshold loading, but differences were not consistently significant. During resting breathing and threshold loading, Vi-derived NVC and MEff ratios were significantly lower in severe patients than in mild patients or healthy subjects. sMMG is a potential noninvasive alternative to sEMG for assessing NRD in COPD. The ratios of Pmo and Vi to sMMG and sEMG measurements provide wholly noninvasive NMC, NVC, and MEff indices that are sensitive to impaired respiratory mechanics in COPD and are therefore of potential value to assess disease severity in clinical practice.

Assessment of the Non-linear Response of the fSampEn on Simulated EMG Signals.

Fixed sample entropy (fSampEn) is a promising technique for the analysis of respiratory electromyographic (EMG) signals. Its use has shown outperformance of amplitude-based estimators such as the root mean square (RMS) in the evaluation of respiratory EMG signals with cardiac noise and a high correlation with respiratory signals, allowing changes in respiratory muscle activity to be tracked. However, the relationship between the fSampEn response to a given muscle activation has not been investigated. The aim of this study was to analyze the nature of the fSampEn measurements that are produced as the EMG activity increases linearly. Simulated EMG signals were generated and increased linearly. The effect of the parameters r and the size of the moving window N of the fSampEn were evaluated and compared with those obtained using the RMS. The RMS showed a linear trend throughout the study. A non-linear, sigmoidal-like behavior was found when analyzing the EMG signals using the fSampEn. The lower the values of r, the higher the non-linearity observed in the fSampEn results. Greater moving windows reduced the variation produced by too small values of r.Clinical Relevance- Understanding the inherent non-linear relationship produced when using the fSampEn in EMG recordings will contribute to the improvement of the respiratory muscle activation assessment at different levels of respiratory effort in patients with respiratory conditions, particularly during the inspiratory phase.

Combining Bioimpedance and Myographic Signals for the Assessment of COPD During Loaded Breathing.

Chronic Obstructive Pulmonary Disease (COPD) is one of the most common chronic conditions. The current assessment of COPD requires a maximal maneuver during a spirometry test to quantify airflow limitations of patients. Other less invasive measurements such as thoracic bioimpedance and myographic signals have been studied as an alternative to classical methods as they provide information about respiration. Particularly, strong correlations have been shown between thoracic bioimpedance and respiratory volume. The main objective of this study is to investigate bioimpedance and its combination with myographic parameters in COPD patients to assess the applicability in respiratory disease monitoring. We measured bioimpedance, surface electromyography and surface mechanomyography in forty-three COPD patients during an incremental inspiratory threshold loading protocol. We introduced two novel features that can be used to assess COPD condition derived from the variation of bioimpedance and the electrical and mechanical activity during each respiratory cycle. These features demonstrate significant differences between mild and severe patients, indicating a lower inspiratory contribution of the inspiratory muscles to global respiratory ventilation in the severest COPD patients. In conclusion, the combination of bioimpedance and myographic signals provides useful indices to noninvasively assess the breathing of COPD patients.

Performance Evaluation of Fixed Sample Entropy for Lung Sound Intensity Estimation.

Lung sound (LS) signals are often contaminated by impulsive artifacts that complicate the estimation of lung sound intensity (LSI) using conventional amplitude estimators. Fixed sample entropy (fSampEn) has proven to be robust to cardiac artifacts in myographic respiratory signals. Similarly, fSampEn is expected to be robust to artifacts in LS signals, thus providing accurate LSI estimates. However, the choice of fSampEn parameters depends on the application and fSampEn has not previously been applied to LS signals. This study aimed to perform an evaluation of the performance of the most relevant fSampEn parameters on LS signals, and to propose optimal fSampEn parameters for LSI estimation. Different combinations of fSampEn parameters were analyzed in LS signals recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing. The performance of fSampEn was assessed by means of its cross-covariance with flow signals, and optimal fSampEn parameters for LSI estimation were proposed.

Spatial Distribution of Normal Lung Sounds in Healthy Individuals under Varied Inspiratory Load and Flow Conditions.

Respiratory sounds yield pertinent information about respiratory function in both health and disease. Normal lung sound intensity is a characteristic that correlates well with airflow and it can therefore be used to quantify the airflow changes and limitations imposed by respiratory diseases. The dual aims of this study are firstly to establish whether previously reported asymmetries in normal lung sound intensity are affected by varying the inspiratory threshold load or the airflow of respiration, and secondly to investigate whether fixed sample entropy can be used as a valid measure of lung sound intensity. Respiratory sounds were acquired from twelve healthy individuals using four contact microphones on the posterior skin surface during an inspiratory threshold loading protocol and a varying airflow protocol. The spatial distribution of the normal lung sounds intensity was examined. During the protocols explored here the normal lung sound intensity in the left and right lungs in healthy populations was found to be similar, with asymmetries of less than 3 dB. This agrees with values reported in other studies. The fixed sample entropy of the respiratory sound signal was also calculated and compared with the gold standard root mean square representation of lung sound intensity showing good agreement.

Analysis of Tracheal and Pulmonary Continuous Adventitious Respiratory Sounds in Asthma.

Continuous adventitious sounds (CAS) are commonly observed in obstructive pulmonary diseases and are of great clinical interest. However, their evaluation is generally subjective. We have previously developed an automatic CAS segmentation and classification algorithm for CAS recorded on the chest surface. The aim of this study is to establish whether these pulmonary CAS can be identified in a similar way using a tracheal microphone. Respiratory sounds were originally recorded from 25 participants using five contact microphones, four on the chest and one on the trachea, during three progressive respiratory maneuvers. In this work CAS component detection was performed on the tracheal channel using our automatic algorithm based on the Hilbert spectrum. The tracheal CAS detected were then compared to the previously analyzed pulmonary CAS. The sensitivity of CAS identification was lower at the tracheal microphone, with CAS that appeared simultaneously in all four pulmonary recordings more likely to be identified in the tracheal recordings. These observations could be due to the CAS being obscured by the lower SNR present in the tracheal recordings or not being transmitted through the airways to the trachea. Further work to optimize the algorithm for the tracheal recordings will be conducted in the future.

Neural Offset Time Evaluation in Surface Respiratory Signals during Controlled Respiration.

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.

Surface mechanomyography and electromyography provide non-invasive indices of inspiratory muscle force and activation in healthy subjects.

The current gold standard assessment of human inspiratory muscle function involves using invasive measures of transdiaphragmatic pressure (Pdi) or crural diaphragm electromyography (oesEMGdi). Mechanomyography is a non-invasive measure of muscle vibration associated with muscle contraction. Surface electromyogram and mechanomyogram, recorded transcutaneously using sensors placed over the lower intercostal spaces (sEMGlic and sMMGlic respectively), have been proposed to provide non-invasive indices of inspiratory muscle activation, but have not been directly compared to gold standard Pdi and oesEMGdi measures during voluntary respiratory manoeuvres. To validate the non-invasive techniques, the relationships between Pdi and sMMGlic, and between oesEMGdi and sEMGlic were measured simultaneously in 12 healthy subjects during an incremental inspiratory threshold loading protocol. Myographic signals were analysed using fixed sample entropy (fSampEn), which is less influenced by cardiac artefacts than conventional root mean square. Strong correlations were observed between: mean Pdi and mean fSampEn |sMMGlic| (left, 0.76; right, 0.81), the time-integrals of the Pdi and fSampEn |sMMGlic| (left, 0.78; right, 0.83), and mean fSampEn oesEMGdi and mean fSampEn sEMGlic (left, 0.84; right, 0.83). These findings suggest that sMMGlic and sEMGlic could provide useful non-invasive alternatives to Pdi and oesEMGdi for the assessment of inspiratory muscle function in health and disease.

Assessment of Inspiratory Muscle Activation using Surface Diaphragm Mechanomyography and Crural Diaphragm Electromyography.

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.

Novel approach to continuous adventitious respiratory sound analysis for the assessment of bronchodilator response.

BACKGROUND: A thorough analysis of continuous adventitious sounds (CAS) can provide distinct and complementary information about bronchodilator response (BDR), beyond that provided by spirometry. Nevertheless, previous approaches to CAS analysis were limited by certain methodology issues. The aim of this study is to propose a new integrated approach to CAS analysis that contributes to improving the assessment of BDR in clinical practice for asthma patients. METHODS: Respiratory sounds and flow were recorded in 25 subjects, including 7 asthma patients with positive BDR (BDR+), assessed by spirometry, 13 asthma patients with negative BDR (BDR-), and 5 controls. A total of 5149 acoustic components were characterized using the Hilbert spectrum, and used to train and validate a support vector machine classifier, which distinguished acoustic components corresponding to CAS from those corresponding to other sounds. Once the method was validated, BDR was assessed in all participants by CAS analysis, and compared to BDR assessed by spirometry. RESULTS: BDR+ patients had a homogenous high change in the number of CAS after bronchodilation, which agreed with the positive BDR by spirometry, indicating high reversibility of airway obstruction. Nevertheless, we also found an appreciable change in the number of CAS in many BDR- patients, revealing alterations in airway obstruction that were not detected by spirometry. We propose a categorization for the change in the number of CAS, which allowed us to stratify BDR- patients into three consistent groups. From the 13 BDR- patients, 6 had a high response, similar to BDR+ patients, 4 had a noteworthy medium response, and 1 had a low response. CONCLUSIONS: In this study, a new non-invasive and integrated approach to CAS analysis is proposed as a high-sensitive tool for assessing BDR in terms of acoustic parameters which, together with spirometry parameters, contribute to improving the stratification of BDR levels in patients with obstructive pulmonary diseases.