Breathing pattern disorder in chronic rhinosinusitis with severe asthma: nasal obstruction and polyps do not increase prevalence.

OBJECTIVES: Chronic rhinosinusitis (CRS) with severe asthma are associated with breathing pattern disorder (BPD). Mouth breathing is a sign of breathing pattern disorder, and nose breathing a fundamental part of breathing pattern retraining for BPD. The prevalence of BPD in relation to CRS subtypes and the relationship of nasal obstruction to BPD in CRS and associated severe asthma is unknown. The breathing pattern assessment tool (BPAT) can identify BPD. Our objective was to thus investigate the prevalence of BPD, nasal airflow obstruction and measures of airway disease severity in CRS with (CRSwNP) and without nasal polyps (CRSsNP) in severe asthma. METHODS: We determined whether CRS status, peak nasal inspiratory flow (PNIF) or polyp disease increased BPD prevalence. Demographic factors, measures of airway function and breathlessness in relation to BPD status and CRS subtypes were also evaluated. RESULTS: 130 Patients were evaluated (n = 69 had BPD). The prevalence of BPD in CRS with severe asthma was 53.1%. There was no difference between BPD occurrence between CRSwNP and CRSsNP. The mean polyp grade and PNIF were not statistically different between the BPD and non-BPD group. The presence of nasal polyps did not increase breathlessness. CONCLUSIONS: BPD and CRS are commonly co-associated. CRS status and nasal obstruction per se does not increase BPD prevalence.

Variations in respiratory and functional symptoms at four months after hospitalisation due to COVID-19: a cross-sectional study.

BACKGROUND: Much remains unknown about complex respiratory symptoms after COVID-19. Here we aimed to describe and analyse patients' various respiratory symptoms 4 months after discharge from hospitalisation for COVID-19, focusing on sex, previous pulmonary disease, and prolonged mechanical ventilation. METHODS: This cross-sectional study involved five hospitals and included 52 patients with self-assessed respiratory dysfunction at 4 months after discharge from hospitalisation for severe COVID-19. Their average age was 63 years, 38% were women, 15 had a previous diagnosed pulmonary disease, and 29 were current or previous smokers. Additionally, 31 had required intensive care-among whom 21 were intubated and 11 needed mechanical ventilation for ≥20 days. Respiratory function was tested concerning lung volumes, expiratory flow, muscle strength, physical capacity (including concurrent oxygen saturation), thoracic expansion, and respiratory movements. RESULTS: Among 52 patients, 47 (90%) had one or several objectively measured respiratory function abnormalities. Decreased thoracic expansion was observed in 32 patients (62%), abnormal respiratory movements in 30 (58%), decreased vital capacity in 21 (40%), low physical function in 13 (26%), and desaturation during the test in 9 (17%). Respiratory inspiratory muscle strength was more commonly diminished than expiratory strength (27% vs. 8%). We did not observe differences between men and women, or between patients with versus without diagnosed pulmonary disease, except that those with pulmonary disease had significantly lower physical capacity assessed with 6MWD (70% vs. 88% predicted, p = 0.013). Compared to those who did not, patients who required ≥20 days of mechanical ventilation performed similarly on most tests, except that all thoracic breathing movements were significantly smaller (p < 0.05). The numbers and combinations of abnormal findings varied widely, without clear patterns. CONCLUSION: Patients with remaining respiratory symptoms 4 months after discharge from hospitalization due to COVID-19 may suffer from various abnormal breathing functions, and dysfunctional breathing that is not detected using traditional measurements. These patients may benefit from multidimensional measuring of breathing movement, thoracic expansion, and respiratory muscle strength, along with traditional measurements, to assess their symptoms and enable prescription of optimal treatment interventions and rehabilitation. TRIAL REGISTRATION: FoU i Sverige (Research & Development in Sweden, Registration number: 274476, registered 2020-05-28).

Differential control of respiratory frequency and tidal volume during exercise.

The lack of a testable model explaining how ventilation is regulated in different exercise conditions has been repeatedly acknowledged in the field of exercise physiology. Yet, this issue contrasts with the abundance of insightful findings produced over the last century and calls for the adoption of new integrative perspectives. In this review, we provide a methodological approach supporting the importance of producing a set of evidence by evaluating different studies together-especially those conducted in 'real' exercise conditions-instead of single studies separately. We show how the collective assessment of findings from three domains and three levels of observation support the development of a simple model of ventilatory control which proves to be effective in different exercise protocols, populations and experimental interventions. The main feature of the model is the differential control of respiratory frequency (fR) and tidal volume (VT); fR is primarily modulated by central command (especially during high-intensity exercise) and muscle afferent feedback (especially during moderate exercise) whereas VT by metabolic inputs. Furthermore, VT appears to be fine-tuned based on fR levels to match alveolar ventilation with metabolic requirements in different intensity domains, and even at a breath-by-breath level. This model reconciles the classical neuro-humoral theory with apparently contrasting findings by leveraging on the emerging control properties of the behavioural (i.e. fR) and metabolic (i.e. VT) components of minute ventilation. The integrative approach presented is expected to help in the design and interpretation of future studies on the control of fR and VT during exercise.

Experiences of Diagnosis, Symptoms, and Use of Reliever Inhalers in Patients With Asthma and Concurrent Inducible Laryngeal Obstruction or Breathing Pattern Disorder: Qualitative Analysis of a UK Asthma Online Community.

BACKGROUND: Breathing pattern disorders (BPDs) and inducible laryngeal obstruction (ILO) cause similar symptoms to asthma, including dyspnea and chest tightness, with an estimated prevalence of up to one-fifth of patients with asthma. Both conditions can be comorbid with asthma, and there is evidence that they are misdiagnosed and mistreated as asthma. OBJECTIVE: This study aims to explore whether the symptoms of ILO and BPD were topics of discussion in a UK asthma online health community and patient experiences of diagnosis and treatment, in particular their use of reliever inhalers. METHODS: A qualitative thematic analysis was performed with posts from an asthma community between 2018 and 2022. A list of key ILO or BPD symptoms was created from the literature. Posts were identified using the search terms "blue inhaler" and "breath" and included if describing key symptoms. Discussion threads of included posts were also analyzed. RESULTS: The search retrieved a total of 1127 relevant posts: 1069 written by 302 users and 58 posted anonymously. All participants were adults, except 2 who were parents writing about their children. Sex and age were only available for 1.66% (5/302; 3 females and 2 males) and 9.93% (30/302) of participants (27 to 73 years old), respectively. The average number of posts written by each participant was 3.54 (range 1-63). Seven participants wrote >20 posts each. Participants experiencing undiagnosed ILO or BPD symptoms, whether or not comorbid with asthma, expressed frustration with the "one-size-fits-all" approach to diagnosis, as many felt that their asthma diagnosis did not fully explain symptoms. Some suspected or were formally diagnosed with BPD or ILO, the latter reporting relief on receiving a diagnosis and appropriate management. Participants showed awareness of their inappropriate salbutamol use or overuse due to lack of effect on symptoms. BPD and ILO symptoms were frequently comorbid with asthma. The asthma online community was a valuable resource: engagement with peers not only brought comfort but also prompted action with some going back to their clinicians and reaching a diagnosis and appropriate management. CONCLUSIONS: Undiagnosed ILO and BPD symptoms and lack of effects of asthma treatment were topics of discussion in an asthma online community, caused distress and frustration in participants, and affected their relationship with health care professionals, showing that patients experiencing BPD and ILO have unmet needs. Clinicians' education on BPD and ILO diagnosis and management, as well as increased access to appropriate management options, such as respiratory physiotherapy and speech and language therapy, are warranted particularly in primary care. Qualitative evidence that engagement with the online community resulted in patients taking action going back to their clinicians and reaching a diagnosis of ILO and BPD prompts future research on online peer support from an established online health community as a self-management resource for patients.

[Nursing Experience of Using Caring Theory in Caring for an Patient in Isolation Facing Bereavement].

A nursing experience using caring theory to care for the grief experienced by a patient with COVID-19 during their period of isolation from June 4 to June 15, 2021 is described in this article. The patient was assessed using physical, psychological, social, and spiritual framework assessments. Data were collected using care, observation, interviews, and medical records. The healthcare problems were identified as inefficient breathing patterns, anxiety, and grief. The patient transmitted COVID-19 to her father, who subsequently died of related respiratory failure. During the nursing process, we used a mobile application (app) to provide the patient with information about novel coronavirus pneumonia to relieve her anxiety. When the patient was physically unwell, we delivered drugs and oxygen, and provided comfortable prone position and breathing training to resolve her low-efficiency breathing patterns. Also, we cooperated with the psychological and spiritual team to resolve the patient's psychological problems, used hand-painted illustrations and words to provide encouragement, and provided information on the hospital's funeral services provider to help complete her father's funeral arrangements to reduce her sense of grief. It is suggested that, in the clinical care of similar patients, nurses should pay more attention to their psychological problems. In addition, nurses may use the concepts of caring theory to integrate a holistic approach, provide patient-specific resources, and accompanying the patient through the process of grief. This nursing experience may be used as a reference in the future care of similar patients to improve the quality of clinical nursing care.

[Exploratory study on quantitative analysis of nocturnal breathing patterns in patients with acute heart failure based on wearable devices].

Patients with acute heart failure (AHF) often experience dyspnea, and monitoring and quantifying their breathing patterns can provide reference information for disease and prognosis assessment. In this study, 39 AHF patients and 24 healthy subjects were included. Nighttime chest-abdominal respiratory signals were collected using wearable devices, and the differences in nocturnal breathing patterns between the two groups were quantitatively analyzed. Compared with the healthy group, the AHF group showed a higher mean breathing rate (BR_mean) [(21.03 ± 3.84) beat/min vs. (15.95 ± 3.08) beat/min, P < 0.001], and larger R_RSBI_cv [70.96% (54.34%-104.28)% vs. 58.48% (45.34%-65.95)%, P = 0.005], greater AB_ratio_cv [(22.52 ± 7.14)% vs. (17.10 ± 6.83)%, P = 0.004], and smaller SampEn (0.67 ± 0.37 vs. 1.01 ± 0.29, P < 0.001). Additionally, the mean inspiratory time (TI_mean) and expiration time (TE_mean) were shorter, TI_cv and TE_cv were greater. Furthermore, the LBI_cv was greater, while SD1 and SD2 on the Poincare plot were larger in the AHF group, all of which showed statistically significant differences. Logistic regression calibration revealed that the TI_mean reduction was a risk factor for AHF. The BR_ mean demonstrated the strongest ability to distinguish between the two groups, with an area under the curve (AUC) of 0.846. Parameters such as breathing period, amplitude, coordination, and nonlinear parameters effectively quantify abnormal breathing patterns in AHF patients. Specifically, the reduction in TI_mean serves as a risk factor for AHF, while the BR_mean distinguishes between the two groups. These findings have the potential to provide new information for the assessment of AHF patients.

Phase- and state-dependent modulation of breathing pattern by preBötzinger complex somatostatin expressing neurons.

As neuronal subtypes are increasingly categorized, delineating their functional role is paramount. The preBötzinger complex (preBötC) subpopulation expressing the neuropeptide somatostatin (SST) is classified as mostly excitatory, inspiratory-modulated and not rhythmogenic. We further characterized their phenotypic identity: 87% were glutamatergic and the balance were glycinergic and/or GABAergic. We then used optogenetics to investigate their modulatory role in both anaesthetized and freely moving mice. In anaesthetized mice, short photostimulation (100 ms) of preBötC SST+ neurons modulated breathing-related variables in a combinatory phase- and state-dependent manner; changes in inspiratory duration, inspiratory peak amplitude (Amp), and phase were different at higher (≥2.5 Hz) vs. lower (<2.5 Hz) breathing frequency (f). Moreover, we observed a biphasic effect of photostimulation during expiration that is probabilistic, that is photostimulation given at the same phase in consecutive cycles can evoke opposite responses (lengthening vs. shortening of the phase). These unexpected probabilistic state- and phase-dependent responses to photostimulation exposed properties of the preBötC that were not predicted and cannot be readily accounted for in current models of preBötC pattern generation. In freely moving mice, prolonged photostimulation decreased f in normoxia, hypoxia or hypercapnia, and increased Amp and produced a phase advance, which was similar to the results in anaesthetized mice when f ≥ 2.5 Hz. We conclude that preBötC SST+ neurons are a key mediator of the extraordinary and essential lability of breathing pattern. KEY POINTS: PreBötzinger complex (preBötC) SST+ neurons, which modulate respiratory pattern but are not rhythmogenic, were transfected with channelrhodopsin to investigate phase- and state-dependent modulation of breathing pattern in anaesthetized and freely behaving mice in normoxia, hypoxia and hypercapnia. In anaesthetized mice, photostimulation during inspiration increased inspiratory duration and amplitude regardless of baseline f, yet the effects were more robust at higher f. In anaesthetized mice with low f (<2.5 Hz), photostimulation during expiration evoked either phase advance or phase delay, whereas in anaesthetized mice with high f (≥2.5 Hz) and in freely behaving mice in normoxia, hypoxia or hypercapnia, photostimulation always evoked phase advance. Phase- and state-dependency is a function of overall breathing network excitability. The f-dependent probabilistic modulation of breathing pattern by preBötC SST+ neurons was unexpected, requiring reconsideration of current models of preBötC function, which neither predict nor can readily account for such responses.

Does breathing pattern affect cerebrovascular reactivity?

NEW FINDINGS: What is the central question of this study? Is cerebrovascular reactivity affected by isocapnic changes in breathing pattern? What is the main finding and its importance? Cerebrovascular reactivity does not change with isocapnic variations in tidal volume and frequency. ABSTRACT: Deviations of arterial carbon dioxide tension from resting values affect cerebral blood vessel tone and thereby cerebral blood flow. Arterial carbon dioxide tension also affects central respiratory chemoreceptors, adjusting respiratory drive. This coincidence raises the question: does respiratory drive also affect the cerebral blood flow response to carbon dioxide? A change in cerebral blood flow for a given change in the arterial carbon dioxide tension is defined as cerebrovascular reactivity (CVR). Two studies have reached conflicting conclusions on this question, using voluntary control of breathing as a disturbing factor during measurements of CVR. Here, we address some of the methodological limitations of both studies by using sequential gas delivery and targeted control of carbon dioxide and oxygen to enable a separation of the effects of carbon dioxide on CVR from breathing vigour. We confirm that there is no detectable superimposed effect of breathing efforts on CVR.

Cheyne-stokes respiration in children with heart failure.

Cheyne-Stokes respiration (CSA-CSR) is a form of central sleep apnea characterized by alternating periods of hyperventilation and central apneas or hypopneas. CSA-CSR develops following a cardiac insult resulting in a compensatory increase in sympathetic activity, which in susceptible patients causes hyperventilation and destabilizes respiratory control. The physiological changes that occur in CSA-CSR include hyperventilation, a reduced blood gas buffering capacity, and circulatory delay. In adults, 25% to 50% of patients with heart failure are reported to have CSA-CSR. The development of CSA-CSR in this group of patients is considered a poor prognostic sign. The prevalence, progression, and treatment outcomes of CSA-CSR in children remain unclear with only 11 children being described in the literature. The lack of data is possibly not due to the paucity of children with severe heart failure and CSA-CSR but because they may be under-recognized, compounded by the absence of routine polysomnographic assessment of children with moderate to severe heart failure. Building on much broader experience in the diagnosis and management of CSA-CSR in adult sleep medicine and our limited experience in a pediatric quaternary center, this paper will discuss the prevalence of CSA-CSR, its' treatment options, outcomes in children, and the potential future direction for research in this understudied area of pediatric sleep medicine.

The association of breathing pattern with exercise tolerance and perceived fatigue in women with systemic lupus erythematosus: an exploratory case-control study.

The aims of the study were to (1) to characterize the breathing pattern and work of breathing during peak exercise in patients with SLE; (2) to examine the extent to which the breathing pattern and work of breathing impact the exercise capacity and fatigue. Forty-one women participated in the study (SLE: n = 23, median = 35, range = 21-57 years, control: n = 18, median = 38, range = 22-45 years). Each subject performed a treadmill cardiopulmonary exercise test (a modified Bruce treadmill protocol) ending with volitional exhaustion. Breathing mechanic was characterized by measures of expired minute volume (VE), tidal volume (Vt), respiratory rate (f), work of breathing, and cardiorespiratory fitness was quantified by measures of peak oxygen consumption (VO2) and time to exhaustion. Data presented as median and interquartile range (IQR). Women with SLE had lower Vt {1221 [488.8] mL/min vs. 1716 [453.1] mL; p = .006}, VE {58.9 [18.9] L/min vs 70 [28.1] L/min, p = 0.04} and increased breathing frequency {51.5 [10.8] vs 43.6 [37.8] bpm, p = 0.01} compared to the control group. The time to exhaustion and peak VO2 during the CPET were significantly reduced in those with SLE compared to controls {13.3 [10.2] vs 16.1 [2.2] min; p = 0.004}, {20 [6.1] mL/kg/min vs 26.6 [7] mL/kg/min p < 0.001}, respectively. Differences remained when the analyses were controlled for the observed differences in peak VO2. When the regression model adjusted for the peak VO2, it had been shown that Vt, WOB and f were explained variances in the fatigue severity by 64% [p < 0.001]. The decline in VE and Vt coupled with a decreased peak VO2, and work of breathing may have contributed to low cardiorespiratory fitness and fatigue in patients with systemic lupus erythematosus.

Monitoring Respiratory Motion during VMAT Treatment Delivery Using Ultra-Wideband Radar.

The goal of this paper is to evaluate the potential of a low-cost, ultra-wideband radar system for detecting and monitoring respiratory motion during radiation therapy treatment delivery. Radar signals from breathing motion patterns simulated using a respiratory motion phantom were captured during volumetric modulated arc therapy (VMAT) delivery. Gantry motion causes strong interference affecting the quality of the extracted respiration motion signal. We developed an artificial neural network (ANN) model for recovering the breathing motion patterns. Next, automated classification into four classes of breathing amplitudes is performed, including no breathing, breath hold, free breathing and deep inspiration. Breathing motion patterns extracted from the radar signal are in excellent agreement with the reference data recorded by the respiratory motion phantom. The classification accuracy of simulated deep inspiration breath hold breathing was 94% under the worst case interference from gantry motion and linac operation. Ultra-wideband radar systems can achieve accurate breathing rate estimation in real-time during dynamic radiation delivery. This technology serves as a viable alternative to motion detection and respiratory gating systems based on surface detection, and is well-suited to dynamic radiation treatment techniques. Novelties of this work include detection of the breathing signal using radar during strong interference from simultaneous gantry motion, and using ANN to perform adaptive signal processing to recover breathing signal from large interference signals in real time.

Tidal volume expandability affected by flow, dynamic hyperinflation, and quasi-fixed inspiratory time in patients with COPD and healthy individuals.

Exertional dyspnea (ED) and impaired exercise performance (EP) are mainly caused by dynamic hyperinflation (DH) in chronic obstructive pulmonary disease (COPD) patients by constraining tidal volume expansion at peak exercise (VTpeak). As VTpeak is the product of inspiratory time (TIpeak) and flow (VT/TIpeak), it was hypothesized that VTpeak and VTpeak/total lung capacity (VTpeak/TLC) may be affected by TIpeak and VT/TIpeak. Hence, the study investigated the (1) effect of TIpeak and VT/TIpeak on VTpeak expansion, (2) factors associated with TIpeak, expiratory time (TEpeak), VT/TIpeak, and VTpeak/TLC, and (3) relationships between VT/TIpeak and VTpeak/TLC with ED and EP in COPD patients and controls. The study enrolled 126 male stable COPD patients and 33 sex-matched controls. At peak exercise, TIpeak was similar in all subjects (COPD versus controls, mean ± SD: 0.78 ± 0.17 s versus 0.81 ± 0.20 s, p = NS), whereas the COPD group had lower VT/TIpeak (1.71 ± 0.49 L/s versus 2.58 ± 0.69 L/s, p < .0001) and thus the COPD group had smaller VTpeak (1.31 ± 0.34 L versus 2.01 ± 0.45 L,p < .0001) and VTpeak/TLC (0.22 ± 0.06 vs 0.33 ± 0.05, p < .0001). TIpeak, TEpeak, and VT/TIpeak were mainly affected by exercise effort, whereas VTpeak/TLC was not. TEpeak, VT/TIpeak, and VTpeak/TLC were inversely changed by impaired lung function. TIpeak was not affected by lung function. Dynamic hyperinflation did not occur in the controls, however, VTpeak/TLC was strongly inversely related to DH (r = -0.79) and moderately to strongly related to lung function, ED, and EP in the COPD group. There was a slightly stronger correlation between VTpeak/TLC with ED and EP than VT/TIpeak in the COPD group (|r| = 0.55-0.56 vs 0.38-0.43). In summary, TIpeak was similar in both groups and the key to understanding how flow affects lung expansion. However, the DH volume effect was more important than the flow effect on ED and EP in the COPD group.

The central nervous system during lung injury and mechanical ventilation: a narrative review.

Mechanical ventilation induces a number of systemic responses for which the brain plays an essential role. During the last decade, substantial evidence has emerged showing that the brain modifies pulmonary responses to physical and biological stimuli by various mechanisms, including the modulation of neuroinflammatory reflexes and the onset of abnormal breathing patterns. Afferent signals and circulating factors from injured peripheral tissues, including the lung, can induce neuronal reprogramming, potentially contributing to neurocognitive dysfunction and psychological alterations seen in critically ill patients. These impairments are ubiquitous in the presence of positive pressure ventilation. This narrative review summarises current evidence of lung-brain crosstalk in patients receiving mechanical ventilation and describes the clinical implications of this crosstalk. Further, it proposes directions for future research ranging from identifying mechanisms of multiorgan failure to mitigating long-term sequelae after critical illness.

Is our breathing optimal? Solving a piecewise linear model with constraints.

This paper is motivated by a question related to the control of amplitude and frequency of breathing. We present a simplified mathematical model, consisting of two piecewise linear ordinary differential equations, that could represent gas exchange in the lungs. We then define and solve an optimal control problem with unknown durations of inhalation and exhalation, subject to several constraints. The durations are divided such that one of the state variables is strictly increasing during the first phase and decreasing during the second phase. The optimal control problem can be solved analytically. One analytical solution is found when the forcing is a given sinusoidal function with unknown period and amplitude. Other analytical solutions are found when the forcing function, the period and the duration of the first phase are unknown but the amplitude is given. Our results show that different cost functions can produce different optimal forcing functions. We also show that the shape of these functions does not affect the average levels of oxygen in the lungs-the average level of oxygen is only dependent on the amplitude and period of breathing in the model we present.

Ventilatory responses at submaximal exercise intensities in healthy children and adolescents during the growth spurt period: a semi-longitudinal study.

PURPOSE: To identify the changes of ventilation ([Formula: see text]E), tidal volume (VT) and respiratory frequency (fr) at different incremental step test intensities during maturation of children and adolescents. METHODS: A semi-longitudinal study was conducted on 68 healthy untrained boys and girls aged 11-17 years. The subjects were separated into three distinct age groups. [Formula: see text]E, VT and fr parameters were evaluated annually during 3 years by modifying incremental step test intensities according to ventilatory threshold (VTh) level (30, 60 and 90% of [Formula: see text]O2max). Absolute and relative values of ventilatory responses were analyzed and compared according to age and developmental phase. RESULTS: (1) Height, weight, lean body mass and vital capacity increased significantly from 11 to 17 years of age. (2) [Formula: see text]O2max, [Formula: see text]E, and VT increased during maturation even when exercise intensity changed, especially from 11 to 15 years of age. On the other hand, fr showed a decreasing trend. CONCLUSION: Increases of VT are the main reason for [Formula: see text]E increases during maturation of children. fr decreased independently of total body mass during maturation. [Formula: see text]E.kg-1 was stable despite intensity variations. VT.kg-1 increased significantly from 11 to 15 years then stabilized at 17 years. Lean body mass seems to explain the evolution of VT.kg-1 during maturation.

A novel technique for prediction of preterm birth: fetal nasal flow Doppler.

OBJECTIVES: Absence of fetal breathing movements (FBM) has been found to be a good predictor of preterm delivery in symptomatic patients. However, analysis of FBM patterns and Doppler measurement of them for preterm birth prediction have not been performed before. In this study, we aimed to investigate and analyze FBM patterns in symptomatic preterm labor patients by fetal ultrasonography and nasal Doppler. METHODS: This was a multicenter, prospective cohort study. Singleton pregnant patients between 24 and 37 gestational weeks diagnosed with preterm labor were included in the study. Patients were evaluated in three groups: no FBM (Group 1), regular FBM (Group 2), irregular FBM (Group3). RESULTS: Seventy-three patients were available for the final analysis after exclusion. Preterm delivery rate in 24 h in groups were 91.7, 32.7 and 100%, respectively. The absence of FBM (Group 1) was statistically significant for preterm delivery in for both 24 (91.7 vs. 42.6%, p=0.002) and 48 h (91.7 vs. 49.2%, p=0.006) when compared with fetal breathing positive Group 2 and 3. In fetal nasal Doppler analyses in Group 2, the inspiration/expiration number rate was significantly lower in the patients who delivered in 24 h (0.98±0.2 vs. 1.25±0.57, p=0.015). By using fetal nasal Doppler, combination of absence of FBM or irregular FBM or regular FBM with inspiration number/expiration number (I/E) <1.25 detects 94.6% of patients who will eventually deliver in the first 24 h after admission. CONCLUSIONS: Examining FBM patterns and using nasal Doppler may help the clinician to differentiate those who will deliver preterm and may be an invaluable tool for managing preterm labor patients.

RF Sensing Based Breathing Patterns Detection Leveraging USRP Devices.

Non-contact detection of the breathing patterns in a remote and unobtrusive manner has significant value to healthcare applications and disease diagnosis, such as in COVID-19 infection prediction. During the epidemic prevention and control period of COVID-19, non-contact approaches have great significance because they minimize the physical burden on the patient and have the least requirement of active cooperation of the infected individual. During the pandemic, these non-contact approaches also reduce environmental constraints and remove the need for extra preparations. According to the latest medical research, the breathing pattern of a person infected with COVID-19 is unlike the breathing associated with flu and the common cold. One noteworthy symptom that occurs in COVID-19 is an abnormal breathing rate; individuals infected with COVID-19 have more rapid breathing. This requires continuous real-time detection of breathing patterns, which can be helpful in the prediction, diagnosis, and screening for people infected with COVID-19. In this research work, software-defined radio (SDR)-based radio frequency (RF) sensing techniques and machine learning (ML) algorithms are exploited to develop a platform for the detection and classification of different abnormal breathing patterns. ML algorithms are used for classification purposes, and their performance is evaluated on the basis of accuracy, prediction speed, and training time. The results show that this platform can detect and classify breathing patterns with a maximum accuracy of 99.4% through a complex tree algorithm. This research has a significant clinical impact because this platform can also be deployed for practical use in pandemic and non-pandemic situations.

Enhanced Breathing Pattern Detection during Running Using Wearable Sensors.

Breathing pattern (BP) is related to key psychophysiological and performance variables during exercise. Modern wearable sensors and data analysis techniques facilitate BP analysis during running but are lacking crucial validation steps in their deployment. Thus, we sought to evaluate a wearable garment with respiratory inductance plethysmography (RIP) sensors in combination with a custom-built algorithm versus a reference spirometry system to determine its concurrent validity in detecting flow reversals (FR) and BP. Twelve runners completed an incremental running protocol to exhaustion with synchronized spirometry and RIP sensors. An algorithm was developed to filter, segment, and enrich the RIP data for FR and BP estimation. The algorithm successfully identified over 99% of FR with an average time lag of 0.018 s (-0.067,0.104) after the reference system. Breathing rate (BR) estimation had low mean absolute percent error (MAPE = 2.74 [0.00,5.99]), but other BP components had variable accuracy. The proposed system is valid and practically useful for applications of BP assessment in the field, especially when measuring abrupt changes in BR. More studies are needed to improve BP timing estimation and utilize abdominal RIP during running.

[Quantitative analysis of breathing patterns based on wearable systems].

Breathing pattern parameters refer to the characteristic pattern parameters of respiratory movements, including the breathing amplitude and cycle, chest and abdomen contribution, coordination, etc. It is of great importance to analyze the breathing pattern parameters quantificationally when exploring the pathophysiological variations of breathing and providing instructions on pulmonary rehabilitation training. Our study provided detailed method to quantify breathing pattern parameters including respiratory rate, inspiratory time, expiratory time, inspiratory time proportion, tidal volume, chest respiratory contribution ratio, thoracoabdominal phase difference and peak inspiratory flow. We also brought in "respiratory signal quality index" to deal with the quality evaluation and quantification analysis of long-term thoracic-abdominal respiratory movement signal recorded, and proposed the way of analyzing the variance of breathing pattern parameters. On this basis, we collected chest and abdomen respiratory movement signals in 23 chronic obstructive pulmonary disease (COPD) patients and 22 normal pulmonary function subjects under spontaneous state in a 15 minute-interval using portable cardio-pulmonary monitoring system. We then quantified subjects' breathing pattern parameters and variability. The results showed great difference between the COPD patients and the controls in terms of respiratory rate, inspiratory time, expiratory time, thoracoabdominal phase difference and peak inspiratory flow. COPD patients also showed greater variance of breathing pattern parameters than the controls, and unsynchronized thoracic-abdominal movements were even observed among several patients. Therefore, the quantification and analyzing method of breathing pattern parameters based on the portable cardiopulmonary parameters monitoring system might assist the diagnosis and assessment of respiratory system diseases and hopefully provide new parameters and indexes for monitoring the physical status of patients with cardiopulmonary disease.

Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning.

Rapid assessment of breathing patterns is important for several emergency medical situations. In this research, we developed a non-invasive breathing analysis system that automatically detects different types of breathing patterns of clinical significance. Accelerometer and gyroscopic data were collected from light-weight wireless sensors placed on the chest and abdomen of 100 normal volunteers who simulated various breathing events (central sleep apnea, coughing, obstructive sleep apnea, sighing, and yawning). We then constructed synthetic datasets by injecting annotated examples of the various patterns into segments of normal breathing. A one-dimensional convolutional neural network was implemented to detect the location of each event in each synthetic dataset and to classify it as belonging to one of the above event types. We achieved a mean F1 score of 92% for normal breathing, 87% for central sleep apnea, 72% for coughing, 51% for obstructive sleep apnea, 57% for sighing, and 63% for yawning. These results demonstrate that using deep learning to analyze chest and abdomen movement data from wearable sensors provides an unobtrusive means of monitoring the breathing pattern. This could have application in a number of critical medical situations such as detecting apneas during sleep at home and monitoring breathing events in mechanically ventilated patients in the intensive care unit.