Comparative investigations of algorithms for the detection of breaths in newborns with disturbed respiratory signals

Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration

Objective.We aimed to fuse the outputs of different electrocardiogram-derived respiration (EDR) algorithms to create one higher quality EDR signal.Methods.We viewed each EDR algorithm as a software sensor that recorded breathing activity from a different vantage point, identified high-quality software sensors based on the respiratory signal quality index, aligned the highest-quality EDRs with a phase synchronization technique based on the graph connection Laplacian, and finally fused those aligned, high-quality EDRs. We refer to the output as the sync-ensembled EDR signal. The proposed algorithm was evaluated on two large-scale databases of whole-night polysomnograms. We evaluated the performance of the proposed algorithm using three respiratory signals recorded from different hardware sensors, and compared it with other existing EDR algorithms. A sensitivity analysis was carried out for a total of five cases: fusion by taking the mean of EDR signals, and the four cases of EDR signal alignment without and with synchronization and without and with signal quality selection.Results.The sync-ensembled EDR algorithm outperforms existing EDR algorithms when evaluated by the synchronized correlation (γ-score), optimal transport (OT) distance, and estimated average respiratory rate score, all with statistical significance. The sensitivity analysis shows that the signal quality selection and EDR signal alignment are both critical for the performance, both with statistical significance.Conclusion.The sync-ensembled EDR provides robust respiratory information from electrocardiogram.Significance.Phase synchronization is not only theoretically rigorous but also practical to design a robust EDR.

Paced breathing and respiratory movement responses evoked by bidirectional constant current stimulation in anesthetized rabbits

Objective: Diaphragm pacing (DP) is a long-term and effective respiratory assist therapy for patients with central alveolar hypoventilation and high cervical spinal cord injury. The existing DP system has some limitations, especially high price, inconvenience preoperative evaluation methods and diaphragm fatigue easily. Our objective was to develop a DP system and evaluated reliability through hardware testing and animal experiments. Methods: A DP system with bidirectional constant current was designed, manufactured and tested. Effects of a wide range of stimulus amplitudes (range: .5-2.5 mA) and frequencies (range: 10-250 Hz) on airflow and corresponding inspired volume were investigated during DP. Differences in airflow characteristics under various stimulation parameters were evaluated using power function. ECG interference in diaphragm electromyography (EMGdi) was filtered out using stationary wavelet transform to obtain pure EMGdi (EMGdi_p). 80-min period with a tendency for diaphragm fatigue by root mean square (RMS) and centroid frequency (f _c ) of EMGdi_p was studied. Results: The increase of stimulus frequency and amplitude in animals resulted in different degrees of increase in envoked volume. Significant difference in Airflow Index (b) between anesthesia and DP provided a simple, non-invasive and feasible solution for phrenic nerve conduction function test. Increased stimulation duration with the developed DP system caused less diaphragm fatigue. Conclusion: A modular, inexpensive and reliable DP was successfully developed. Its effectiveness was confirmed in animal experiments. Significance: This study is useful for design of future implantable diaphragmatic pacemakers for improving diaphragm fatigue and convenient assessment of respiratory activity in experiments.

Evaluation of Correlation between Surface Diaphragm Electromyography and Airflow Using Fixed Sample Entropy in Healthy Subjects

In clinic, the acquisition of airflow with nasal prongs, masks, thermistor to monitor respiratory function is more uncomfortable and inconvenience than surface diaphragm electromyography (EMGdi) using electrode pads. The EMGdi with strong electrocardiograph (ECG) interference affect the extraction of its characteristic information. In this work, surface EMGdi and airflow signals of 20 subjects were collected under 5 incremental inspiratory threshold loading protocols from quiet breathing to maximum forced breathing. First, we filtered out the ECG interference in EMGdi based on the combination of stationary wavelet transform and the positioning of ECG to obtain pure EMGdi (EMGdip). Second, the Spearman's rank correlation coefficients between EMGdi and EMGdip quantified by time series fixed sample entropy (fSampEn), root mean square (RMS), and envelope were compared to verify the robustness of the fSampEn to ECG. A comparative analysis of correlation between fSampEn of EMGdi and inspiratory airflow and the correlation between envelope of EMGdip (EMGdie) and inspiratory airflow found that there was no significant difference between the two, indicating the feasibility of using fSampEn to predict airflow. Moreover, fSampEn of EMGdi was used as characteristic parameter to build a quantitative relationship with the airflow by polynomial regression analysis. Mean coefficient of determination of all subjects in any breathing state is greater than 0.88. Finally, nonlinear programming method was used to solve a universal fitting coefficient between fSampEn of EMGdi and airflow for each subject to further evaluate the possibility of using surface EMGdi to monitor and control respiratory activity.

Tidal breathing flow profiles during sleep in wheezing children measured by impedance pneumography

For the first time, impedance pneumography (IP) enables a continuous analysis of the tidal breathing flow volume (TBFV), overnight. We studied how corticosteroid inhalation treatments, sleep stage, and time from sleep onset modify the nocturnal TBFV profiles of children. Seventy children, 1-5 years old and with recurrent wheezing, underwent three, full-night TBFVs recordings at home, using IP. The first recorded one week before ending a 3-months inhaled corticosteroids treatment, and remaining two, 2 and 4 weeks after treatment. TBFV profiles were grouped by hour from sleep onset and estimated sleep stage. Compared with on-medication, the off-medication profiles showed lower volume at exhalation peak flow, earlier interruption of expiration, and less convex middle expiration. The differences in the first two features were significant during non-rapid eye movement (NREM), and the differences in the third were more prominent during REM after 4 h of sleep. These combinations of TBFV features, sleep phase, and sleep time potentially indicate airflow limitation in young children.

Tidal breathing parameters measured by structured light plethysmography in children aged 2-12 years recovering from acute asthma/wheeze compared with healthy children

Measurement of lung function can be difficult in young children. Structured light plethysmography (SLP) is a novel, noncontact method of measuring tidal breathing that monitors displacement of the thoraco-abdominal wall. SLP was used to compare breathing in children recovering from an acute exacerbation of asthma/wheeze and an age-matched cohort of controls. Children aged 2-12 years with acute asthma/wheeze (n = 39) underwent two 5-min SLP assessments, one before bronchodilator treatment and one after. SLP was performed once in controls (n = 54). Nonparametric comparisons of patients to healthy children and of pre-bronchodilator to post-bronchodilator were made for all children, and also stratified by age group (2-5 vs. 6-12 years old). In the asthma/wheeze group, IE50_SLP (inspiratory to expiratory flow ratio) was higher (median 1.47 vs. 1.31; P = 0.002), thoraco-abdominal asynchrony (TAA) and left-right asynchrony were greater (both P < 0.001), and respiratory rate was faster (P < 0.001) than in controls. All other timing indices were shorter and displayed reduced variability (all P < 0.001). Variability in time to peak inspiratory flow was also reduced (P < 0.001). Younger children showed a greater effect than older children for TAA (interaction P < 0.05). After bronchodilator treatment, the overall cohort showed a reduction in within-subject variability in time to peak expiratory flow only (P < 0.001). Younger children exhibited a reduction in relative contribution of the thorax, TAA, and variability in TAA (interaction P < 0.05). SLP can be successfully performed in young children. The potential of SLP to monitor diseases such as asthma in children is worthy of further investigation. ClinicalTrials.gov identifier: NCT02543333.

Tidal breathing flow volume profiles during sleep in wheezing infants measured by impedance pneumography

Overnight analysis of tidal breathing flow volume (TBFV) loops, recorded by impedance pneumography (IP), has been successfully applied in the home monitoring of children with wheezing disorders. However, little is known on how sleep physiology modifies the relationship between TBFV profiles and wheeze. We studied such interactions in wheezing infants. Forty-three infants recruited because of recurrent lower airway symptoms were divided into three groups based on their risk of asthma: high (HR), intermediate (IR), or low (LR). Sedated patients underwent infant lung function testing including assessment of airway responsiveness to methacholine at the hospital and a full-night recording of TBFV profiles at home with IP during natural sleep. Overnight TBFV indexes were estimated from periods of higher and lower respiration variability, presumably belonging to active [rapid eye movement (REM)] and quiet [non-REM (NREM)] sleep, respectively. From 35 valid recordings, absolute time indexes showed intrasubject sleep phase differences. Peak flow relative to time and volume was lower in HR compared with LR only during REM, suggesting altered expiratory control. Indexes estimating the concavity/convexity of flow decrease during exhalation suggested limited flow during passive exhale in HR compared with IR and LR, similarly during NREM and REM. Moreover, during REM convexity was negatively correlated with maximal flow at functional residual capacity and methacholine responsiveness. We conclude that TBFV profiles determined from overnight IP recordings vary because of sleep phase and asthma risk. Physiological changes during REM, most likely decrease in respiratory muscle tone, accentuate the changes in TBFV profiles caused by airway obstruction. NEW & NOTEWORTHY Impedance pneumography was used to investigate overnight tidal breathing flow volume (TBFV) indexes and their interactions with sleep phase [rapid eye movement (REM) vs. non-REM] at home in wheezing infants. The study shows that TBFV indexes vary significantly because of sleep phase and asthma risk of the infant and that during REM the changes in TBFV indexes caused by airway obstruction are accentuated and better associated with lung function of the infant.

Optimized breath detection algorithm in electrical impedance tomography

OBJECTIVE

This paper defines a method for optimizing the breath delineation algorithms used in electrical impedance tomography (EIT). In lung EIT the identification of the breath phases is central for generating tidal impedance variation images, subsequent data analysis and clinical evaluation. The optimisation of these algorithms is particularly important in neonatal care since the existing breath detectors developed for adults may give insufficient reliability in neonates due to their very irregular breathing pattern.

APPROACH

Our approach is generic in the sense that it relies on the definition of a gold standard and the associated definition of detector sensitivity and specificity, an optimisation criterion and a set of detector parameters to be investigated. The gold standard has been defined by 11 clinicians with previous experience with EIT and the performance of our approach is described and validated using a neonatal EIT dataset acquired within the EU-funded CRADL project.

MAIN RESULTS

Three different algorithms are proposed that improve the breath detector performance by adding conditions on (1) maximum tidal breath rate obtained from zero-crossings of the EIT breathing signal, (2) minimum tidal impedance amplitude and (3) minimum tidal breath rate obtained from time-frequency analysis. As a baseline a zero-crossing algorithm has been used with some default parameters based on the Swisstom EIT device.

SIGNIFICANCE

Based on the gold standard, the most crucial parameters of the proposed algorithms are optimised by using a simple exhaustive search and a weighted metric defined in connection with the receiver operating characterics. This provides a practical way to achieve any desirable trade-off between the sensitivity and the specificity of the detectors.

Novel approach to computerized breath detection in lung function diagnostics

BACKGROUND

Breath detection, i.e. its precise delineation in time is a crucial step in lung function data analysis as obtaining any clinically relevant index is based on the proper localization of breath ends. Current threshold or smoothing algorithms suffer from severe inaccuracy in cases of suboptimal data quality. Especially in infants, the precise analysis is of utmost importance. The key objective of our work is to design an algorithm for accurate breath detection in severely distorted data.

METHODS

Flow and gas concentration data from multiple breath washout test were the input information. Based on universal physiological characteristics of the respiratory tract we designed an algorithm for breath detection. Its accuracy was tested on severely distorted data from 19 patients with different types of breathing disorders. Its performance was compared to the performance of currently used algorithms and to the breath counts estimated by human experts.

RESULTS

The novel algorithm outperformed the threshold algorithms with respect to their accuracy and had similar performance to human experts. It proved to be a highly robust and efficient approach in severely distorted data. This was demonstrated on patients with different pulmonary disorders.

CONCLUSION

Our newly proposed algorithm is highly robust and universal. It works accurately even on severely distorted data, where the other tested algorithms failed. It does not require any pre-set thresholds or other patient-specific inputs. Consequently, it may be used with a broad spectrum of patients. It has the potential to replace current approaches to the breath detection in pulmonary function diagnostics.

Evaluation of the agreement of tidal breathing parameters measured simultaneously using pneumotachography and structured light plethysmography

Structured light plethysmography (SLP) is a noncontact, noninvasive, respiratory measurement technique, which uses a structured pattern of light and two cameras to track displacement of the thoraco–abdominal wall during tidal breathing. The primary objective of this study was to examine agreement between tidal breathing parameters measured simultaneously for 45 sec using pneumotachography and SLP in a group of 20 participants with a range of respiratory patterns (“primary cohort”). To examine repeatability of the agreement, an additional 21 healthy subjects (“repeatability cohort”) were measured twice during resting breathing and once during increased respiratory rate (RR). Breath‐by‐breath and averaged RR, inspiratory time (tI), expiratory time (tE), total breath time (tTot), tI/tE, tI/tTot, and IE50 (inspiratory to expiratory flow measured at 50% of tidal volume) were calculated. Bland–Altman plots were used to assess the agreement. In the primary cohort, breath‐by‐breath agreement for RR was ±1.44 breaths per minute (brpm). tI, tE, and tTot agreed to ±0.22, ±0.29, and ±0.32 sec, respectively, and tI/tE, tI/tTot, and IE50/IE50_SLP to ±0.16, ±0.05, and ±0.55, respectively. When averaged, agreement for RR was ±0.19 brpm. tI, tE, and tTot were within ±0.16, ±0.16, and ±0.07 sec, respectively, and tI/tE, tI/tTot, and IE50 were within ±0.09, ±0.03, and ±0.25, respectively. A comparison of resting breathing demonstrated that breath‐by‐breath and averaged agreements for all seven parameters were repeatable (P > 0.05). With increased RR, agreement improved for tI, tE, and tTot (P ≤ 0.01), did not differ for tI/tE, tI/tTot, and IE50 (P > 0.05) and reduced for breath‐by‐breath (P < 0.05) but not averaged RR (P > 0.05).

Tidal breathing parameters measured using structured light plethysmography in healthy children and those with asthma before and after bronchodilator

Structured light plethysmography (SLP) is a light‐based, noncontact technique that measures tidal breathing by monitoring displacements of the thoracoabdominal (TA) wall. We used SLP to measure tidal breathing parameters and their within‐subject variability (v) in 30 children aged 7–16 years with asthma and abnormal spirometry (forced expiratory volume in 1 sec [FEV1] <80% predicted) during a routine clinic appointment. As part of standard care, the reversibility of airway obstruction was assessed by repeating spirometry after administration of an inhaled bronchodilator. In this study, SLP was performed before and after bronchodilator administration, and also once in 41 age‐matched controls. In the asthma group, there was a significant increase in spirometry‐assessed mean FEV1 after administration of bronchodilator. Of all measured tidal breathing parameters, the most informative was the inspiratory to expiratory TA displacement ratio (IE50_SLP, calculated as TIF50_SLP/TEF50_SLP, where TIF50_SLP is tidal inspiratory TA displacement rate at 50% of inspiratory displacement and TEF50_SLP is tidal expiratory TA displacement rate at 50% of expiratory displacement). Median (m) IE50_SLP and its variability (vIE50_SLP) were both higher in children with asthma (prebronchodilator) compared with healthy children (mIE50_SLP: 1.53 vs. 1.22, P < 0.001; vIE50_SLP: 0.63 vs. 0.47, P < 0.001). After administration of bronchodilators to the asthma group, mIE50_SLP decreased from 1.53 to 1.45 (P = 0.01) and vIE50_SLP decreased from 0.63 to 0.60 (P = 0.04). SLP‐measured tidal breathing parameters could differentiate between children with and without asthma and indicate a response to bronchodilator.

The Ultrasonic Directional Tidal Breathing Pattern Sensor: Equitable Design Realization Based on Phase Information

Pulmonary ailments are conventionally diagnosed by spirometry. The complex forceful breathing maneuver as well as the extreme cost of spirometry renders it unsuitable in many situations. This work is aimed to facilitate an emerging direction of tidal breathing-based pulmonary evaluation by designing a novel, equitable, precise and portable device for acquisition and analysis of directional tidal breathing patterns, in real time. The proposed system primarily uses an in-house designed blow pipe, 40-kHz air-coupled ultrasound transreceivers, and a radio frequency (RF) phase-gain integrated circuit (IC). Moreover, in order to achieve high sensitivity in a cost-effective design philosophy, we have exploited the phase measurement technique, instead of selecting the contemporary time-of-flight (TOF) measurement; since application of the TOF principle in tidal breathing assessments requires sub-micro to nanosecond time resolution. This approach, which depends on accurate phase measurement, contributed to enhanced sensitivity using a simple electronics design. The developed system has been calibrated using a standard 3-L calibration syringe. The parameters of this system are validated against a standard spirometer, with maximum percentage error below 16%. Further, the extracted respiratory parameters related to tidal breathing have been found to be comparable with relevant prior works. The error in detecting respiration rate only is 3.9% compared to manual evaluation. These encouraging insights reveal the definite potential of our tidal breathing pattern (TBP) prototype for measuring tidal breathing parameters in order to extend the reach of affordable healthcare in rural regions and developing areas.

An automated and reliable method for breath detection during variable mask pressures in awake and sleeping humans

Accurate breath detection is crucial in sleep and respiratory physiology research and in several clinical settings. However, this process is technically challenging due to measurement and physiological artifacts and other factors such as variable leaks in the breathing circuit. Recently developed techniques to quantify the multiple causes of obstructive sleep apnea, require intermittent changes in airway pressure applied to a breathing mask. This presents an additional unique challenge for breath detection. Traditional algorithms often require drift correction. However, this is an empirical operation potentially prone to human error. This paper presents a new algorithm for breath detection during variable mask pressures in awake and sleeping humans based on physiological landmarks detected in the airflow or epiglottic pressure signal (Pepi). The algorithms were validated using simulated data from a mathematical model and against the standard visual detection approach in 4 healthy individuals and 6 patients with sleep apnea during variable mask pressure conditions. Using the flow signal, the algorithm correctly identified 97.6% of breaths with a mean difference±SD in the onsets of respiratory phase compared to expert visual detection of 23±89ms for inspiration and 6±56ms for expiration during wakefulness and 10±74ms for inspiration and 3±28 ms for expiration with variable mask pressures during sleep. Using the Pepi signal, the algorithm correctly identified 89% of the breaths with accuracy of 31±156ms for inspiration and 9±147ms for expiration compared to expert visual detection during variable mask pressures asleep. The algorithm had excellent performance in response to baseline drifts and noise during variable mask pressure conditions. This new algorithm can be used for accurate breath detection including during variable mask pressure conditions which represents a major advance over existing time-consuming manual approaches.

Onset and Offset Estimation of the Neural Inspiratory Time in Surface Diaphragm Electromyography: A Pilot Study in Healthy Subjects

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 (T_i/T_tot) 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 (EMGdi_fse). The neural onset was detected through a dynamic threshold over the EMGdi_fse using the kernel density estimation method, while neural offset was detected by finding when the EMGdi_fse 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 T_i /T_tot 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 T_i/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 T_i/T_tot 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.

Tidal breathing patterns derived from structured light plethysmography in COPD patients compared with healthy subjects

PURPOSE

Differences in tidal breathing patterns have been reported between patients with chronic obstructive pulmonary disease (COPD) and healthy individuals using traditional measurement techniques. This feasibility study examined whether structured light plethysmography (SLP) - a noncontact, light-based technique - could also detect differences in tidal breathing patterns between patients with COPD and healthy subjects.

PATIENTS AND METHODS

A 5 min period of tidal (quiet) breathing was recorded in each patient with COPD (n=31) and each healthy subject (n=31), matched for age, body mass index, and sex. For every participant, the median and interquartile range (IQR; denoting within-subject variability) of 12 tidal breathing parameters were calculated. Individual data were then combined by cohort and summarized by its median and IQR.

RESULTS

After correction for multiple comparisons, inspiratory time (median tI) and its variability (IQR of tI) were lower in patients with COPD (p<0.001 and p<0.01, respectively) as were ratios derived from tI (tI/tE and tI/tTot, both p<0.01) and their variability (p<0.01 and p<0.05, respectively). IE50SLP (the ratio of inspiratory to expiratory flow at 50% tidal volume calculated from the SLP signal) was higher (p<0.001) in COPD while SLP-derived time to reach peak tidal expiratory flow over expiratory time (median tPTEFSLP/tE) was shorter (p<0.01) and considerably less variable (p<0.001). Thoraco-abdominal asynchrony was increased (p<0.05) in COPD.

CONCLUSION

These early observations suggest that, like traditional techniques, SLP is able to detect different breathing patterns in COPD patients compared with subjects with no respiratory disease. This provides support for further investigation into the potential uses of SLP in assessing clinical conditions and interventions.

Basic principles of respiratory function monitoring in ventilated newborns: A review

Respiratory monitoring during mechanical ventilation provides a real-time picture of patient-ventilator interaction and is a prerequisite for lung-protective ventilation. Nowadays, measurements of airflow, tidal volume and applied pressures are standard in neonatal ventilators. The measurement of lung volume during mechanical ventilation by tracer gas washout techniques is still under development. The clinical use of capnography, although well established in adults, has not been embraced by neonatologists because of technical and methodological problems in very small infants. While the ventilatory parameters are well defined, the calculation of other physiological parameters are based upon specific assumptions which are difficult to verify. Incomplete knowledge of the theoretical background of these calculations and their limitations can lead to incorrect interpretations with clinical consequences. Therefore, the aim of this review was to describe the basic principles and the underlying assumptions of currently used methods for respiratory function monitoring in ventilated newborns and to highlight methodological limitations.

Respiratory Variability during Sleep in Methadone Maintenance Treatment Patients

STUDY OBJECTIVES

Methadone maintenance treatment (MMT) patients have a high prevalence of central sleep apnea and ataxic breathing related to damage to central respiratory rhythm control. However, the quantification of sleep apnea indices requires laborious manual scoring, and ataxic breathing pattern is subjectively judged by visual pattern recognition. This study proposes a semi-automated technique to characterize respiratory variability in MMT patients.

METHODS

Polysomnography, blood, and functional outcomes of sleep questionnaire (FOSQ) from 50 MMT patients and 20 healthy subjects with matched age, sex, and body mass index, were analyzed. Inter-breath intervals (IBI) were extracted from the nasal cannula pressure signal. Variability of IBI over 100 breaths was quantified by standard deviation (SD), coefficient of variation (CV), and scaling exponent (α) from detrended fluctuation analysis. The relationships between these variability measures and blood methadone concentration, central sleep apnea index (CAI), apnea-hypopnea index (AHI), and clinical outcome (FOSQ), were then examined.

RESULTS

MMT patients had significantly higher SD and CV during all sleep stages. During NREM sleep, SD and CV were correlated with blood methadone concentration (Spearman R = 0.52 and 0.56, respectively; p < 0.01). SD and CV were also correlated with CAI (R = 0.63 and 0.71, p < 0.001, respectively), and AHI (R = 0.45 and 0.58, p < 0.01, respectively). Only α showed significant correlation with FOSQ (R = -0.33, p < 0.05).

CONCLUSIONS

MMT patients have a higher respiratory variability during sleep than healthy controls. Semi-automated variability measures are related to apnea indices obtained by manual scoring and may provide a new approach to quantify opioid-related sleep-disordered breathing.

Characterising non-linear dynamics in nocturnal breathing patterns of healthy infants using recurrence quantification analysis

Breathing dynamics vary between infant sleep states, and are likely to exhibit non-linear behaviour. This study applied the non-linear analytical tool recurrence quantification analysis (RQA) to 400 breath interval periods of REM and N-REM sleep, and then using an overlapping moving window. The RQA variables were different between sleep states, with REM radius 150% greater than N-REM radius, and REM laminarity 79% greater than N-REM laminarity. RQA allowed the observation of temporal variations in non-linear breathing dynamics across a night's sleep at 30s resolution, and provides a basis for quantifying changes in complex breathing dynamics with physiology and pathology.

Application of recurrence quantification analysis to automatically estimate infant sleep states using a single channel of respiratory data

Previous work has identified that non-linear variables calculated from respiratory data vary between sleep states, and that variables derived from the non-linear analytical tool recurrence quantification analysis (RQA) are accurate infant sleep state discriminators. This study aims to apply these discriminators to automatically classify 30 s epochs of infant sleep as REM, non-REM and wake. Polysomnograms were obtained from 25 healthy infants at 2 weeks, 3, 6 and 12 months of age, and manually sleep staged as wake, REM and non-REM. Inter-breath interval data were extracted from the respiratory inductive plethysmograph, and RQA applied to calculate radius, determinism and laminarity. Time-series statistic and spectral analysis variables were also calculated. A nested cross-validation method was used to identify the optimal feature subset, and to train and evaluate a linear discriminant analysis-based classifier. The RQA features radius and laminarity and were reliably selected. Mean agreement was 79.7, 84.9, 84.0 and 79.2 % at 2 weeks, 3, 6 and 12 months, and the classifier performed better than a comparison classifier not including RQA variables. The performance of this sleep-staging tool compares favourably with inter-human agreement rates, and improves upon previous systems using only respiratory data. Applications include diagnostic screening and population-based sleep research.

Tracheal tube airleak in clinical practice and impact on tidal volume measurement in ventilated neonates

OBJECTIVE

To determine the prevalence, size, and factors affecting tracheal tube (TT) leak in clinical practice and their influence on the displayed tidal volume (Vt) in ventilated newborn infants using uncuffed TTs. Monitoring of Vt is important for implementation of lung-protective ventilation strategies but becomes meaningless in the presence of large TT airleaks.

DESIGN

Retrospective clinical study.

SETTING

Neonatal intensive care unit.

PATIENTS

Patient records of 163 neonates ventilated with Babylog 8000 for ≥ 5 hrs with a median (range) gestation age of 31.1 wks (23.3-41.9 wks) and a median birth weight of 1470 g (410-4475 g) were evaluated.

INTERVENTIONS

: Ventilatory settings, TT leak, and Vt were recorded every 3 hrs. The lowest, median, and highest TT leaks were noted on the day the first TT leak (>5%) occurred, the day on which TT leak peaked, and the day of extubation.

MEASUREMENTS AND MAIN RESULTS

A TT leak of >5% was seen in 122 (75%) infants. Neonates with TT leak, compared with those without TT leak, had a longer duration of mechanical ventilation (p < .001), a lower gestational age (p = .004), a reduced birth weight (p = .005), and a higher prevalence of reintubation (p = .003). The greatest TT leak was seen in infants ventilated with a TT of <3-mm diameter. During the entire duration of mechanical ventilation, 42.3% of all neonates experienced at least one TT leak of >40% commonly seen on the third day of mechanical ventilation. Regression analysis showed that a TT leak of 40% indicated that the displayed Vt was underestimated by 1.2 mL/kg (about 24% of target Vt).

CONCLUSIONS

TT leak is highly variable, and TT leak of >40% with clinically relevant Vt errors occurred in nearly half of all ventilated neonates. Preterm infants of low birth weight and with small-diameter TTs ventilated for a long period were at greater risk of TT leak.

Characterising infant inter-breath interval patterns during active and quiet sleep using recurrence plot analysis

Breathing patterns are characteristically different between active and quiet sleep states in infants. It has been previously identified that breathing dynamics are governed by a non-linear controller which implies the need for a nonlinear analytical tool. Further, it has been shown that quantified nonlinear variables are different between adult sleep states. This study aims to determine whether a nonlinear analytical tool known as recurrence plot analysis can characterize breath intervals of active and quiet sleep states in infants. Overnight polysomnograms were obtained from 32 healthy infants. The 6 longest periods each of active and quiet sleep were identified and a software routine extracted inter-breath interval data for recurrence plot analysis. Determinism (DET), laminarity (LAM) and radius (RAD) values were calculated for an embedding dimension of 4, 6, 8 and 16, and fixed recurrence of 0.5, 1, 2, 3.5 and 5%. Recurrence plots exhibited characteristically different patterns for active and quiet sleep. Active sleep periods typically had higher values of RAD, DET and LAM than for quiet sleep, and this trend was invariant to a specific choice of embedding dimension or fixed recurrence. These differences may provide a basis for automated sleep state classification, and the quantitative investigation of pathological breathing patterns.

Automated breath detection on long-duration signals using feedforward backpropagation artificial neural networks

A new breath-detection algorithm is presented, intended to automate the analysis of respiratory data acquired during sleep. The algorithm is based on two independent artificial neural networks (ANN(insp) and ANN(expi)) that recognize, in the original signal, windows of interest where the onset of inspiration and expiration occurs. Postprocessing consists in finding inside each of these windows of interest minimum and maximum corresponding to each inspiration and expiration. The ANN(insp) and ANN(expi) correctly determine respectively 98.0% and 98.7% of the desired windows, when compared with 29,820 inspirations and 29,819 expirations detected by a human expert, obtained from three entire-night recordings. Postprocessing allowed determination of inspiration and expiration onsets with a mean difference with respect to the same human expert of (mean +/- SD) 34 +/- 71 ms for inspiration and 5 +/- 46 ms for expiration. The method proved to be effective in detecting the onset of inspiration and expiration in full night continuous recordings. A comparison of five human experts performing the same classification task yielded that the automated algorithm was undifferentiable from these human experts, falling within the distribution of human expert results. Besides being applicable to adult respiratory volume data, the presented algorithm was also successfully applied to infant sleep data, consisting of uncalibrated rib cage and abdominal movement recordings. A comparison with two previously published algorithms for breath detection in respiratory volume signal shows that the presented algorithm has a higher specificity, while presenting similar or higher positive predictive values.

In vitro assessment of equipment and software to assess tidal breathing parameters in infants

The aim of this in vitro study was to compare the measurement accuracy of two currently available devices for measuring tidal breathing in infants. A mechanical model pump was used to generate flow profiles which simulated those observed in infants. A range of flows was applied simultaneously to two different devices, namely the commercially available SensorMedics 2600 (SM 2600) and more recently developed, custom-made equipment based on the flow-through technique (FTT). Automatically derived values from both devices were compared with one another and with manual calculations of printouts of the same breaths. There were no differences in the raw flow signal obtained from the two devices, nor between values calculated automatically or manually from the FTT. Similarly, the deviations between the FTT and SM 2600 were <3% for tidal volume, respiratory frequency and minute ventilation. However, when comparing either with manually calculated values or those derived automatically from the FTT, there was a systematic and highly significant underestimation of shape-dependent parameters, such as the time to peak tidal expiratory flow as a proportion of tidal expiratory time (tPTEF/tE), derived by the SM 2600. The lower the applied flow, the higher the observed deviations, the underestimation being up to 60% when flows simulating those observed in preterm neonates were applied. These errors appear to result from differences in signal processing such as the algorithms used for breath detection and can only be detected if appropriate nonsinusoidal flow profiles representing those seen in infants are used to evaluate equipment.

Effect of apparatus dead space on breathing parameters in newborns: "flow-through" versus conventional techniques

Commercial devices for tidal breathing measurements in newborns allow only short-term measurements, due to the high apparatus dead space of the face mask and pneumotachometer. The flow-through technique (FTT) minimizes the dead space by a background flow, thereby allowing long-term measurements. The aim of this study was to investigate the comparability of tidal breathing parameters using both techniques. Paired measurements of tidal breathing were performed in 86 sleeping infants (median (range) body weight 2.8 kg (1.9-5.3 kg), age 65 days (3-150 days)), using the FTT and SensorMedics 2600 (SM 2600). There was a significant bias (p <0.001) in all tidal breathing parameters. Compared with the FTT, increases (95% confidence interval (CI)) in tidal volume (VT), respiratory frequency (fR), and minute ventilation (V'E) were 0.74 (0.5-1.0) mL.kg(-1), 9.0 (6.9-11.2).min(-1) and 92 (74-109) mL.min(-1).kg(-1) when measured with the SM 2600, representing average increases of 13, 17 and 30%, respectively, in response to the added dead space. By contrast, time to peak tidal expiratory flow as a proportion of expiratory time (tPTEF/tE) was changed by -0.09 (-0.11-0.08). The mean (95% CI) change in tPTEF/tE of -54 (-62-45)%, when measured in infants by the SM 2600, was remarkably similar to that observed during in vitro validation studies (-59 (-73-44)%), suggesting that the discrepancies in timing parameters may be largely attributable to differences in signal processing. In conclusion, differences in measurement technique and precision of the devices used can result in significant differences in tidal breathing parameters. This may impede the comparison of results within and between infants and the clinical interpretation of tidal breathing measurements in newborns.