Suprasternal Pressure Research Articles

Quantitative validation of the suprasternal pressure signal to assess respiratory effort during sleep

Objective. Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort. However, this type of sensor has been validated only for respiratory events in the context of obstructive sleep apnea syndrome (OSA). We aim to provide an extensive verification of the suprasternal pressure signal against RIP belts and Pes, covering both normal breathing and respiratory events. Approach. We simultaneously acquired suprasternal (207) and esophageal pressure (20) signals along with RIP belts during a clinical PSG of 207 participants. In each signal, we detected breaths with a custom algorithm, and evaluated the SSP in terms of detection quality, breathing rate estimation, and similarity of breathing patterns against RIP and Pes. Additionally, we examined how the SSP signal may diverge from RIP and Pes in presence of respiratory events scored by a sleep technician. Main results. The SSP signal proved to be a reliable substitute for both esophageal pressure (Pes) and respiratory inductance plethysmography (RIP) in terms of breath detection, with sensitivity and positive predictive value exceeding 75%, and low error in breathing rate estimation. The SSP was also consistent with Pes (correlation of 0.72, similarity 80.8%) in patterns of increasing pressure amplitude that are common in OSA. Significance. This work provides a quantitative analysis of suprasternal pressure sensors for respiratory effort measurements.

A sleep stage estimation algorithm based on cardiorespiratory signals derived from a suprasternal pressure sensor.

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages. The sensor is already used for diagnosis of sleep-disordered breathing (SDB) conditions, but besides respiratory effort it can detect cardiac vibrations transmitted through the trachea. We collected the SSP sensor signal in 100 adults (57 male) undergoing clinical polysomnography for suspected sleep disorders, including sleep apnea syndrome, insomnia, and movement disorders. Here, we separate respiratory effort and cardiac activity related signals, then input these into a neural network trained to estimate sleep stages. Using the original mixed signal the results show a moderate agreement with manual scoring, with a Cohen's kappa of 0.53 in Wake/N1-N2/N3/rapid eye movement sleep discrimination and 0.62 in Wake/Sleep. We demonstrate that decoupling the two signals and using the cardiac signal to estimate the instantaneous heart rate improves the process considerably, reaching an agreement of 0.63 and 0.71. Our proposed method achieves high accuracy, specificity, and sensitivity across different sleep staging tasks. We also compare the total sleep time calculated with our method against manual scoring, with an average error of -1.83 min but a relatively large confidence interval of ±55 min. Compact systems that employ the SSP sensor information-rich signal may enable new ways of clinical assessments, such as night-to-night variability in obstructive sleep apnea and other sleep disorders.

Extraction of cardiac-related signals from a suprasternal pressure sensor during sleep

Objective. The accurate detection of respiratory effort during polysomnography is a critical element in the diagnosis of sleep-disordered breathing conditions such as sleep apnea. Unfortunately, the sensors currently used to estimate respiratory effort are either indirect and ignore upper airway dynamics or are too obtrusive for patients. One promising alternative is the suprasternal notch pressure (SSP) sensor: a small element placed on the skin in the notch above the sternum within an airtight capsule that detects pressure swings in the trachea. Besides providing information on respiratory effort, the sensor is sensitive to small cardiac oscillations caused by pressure perturbations in the carotid arteries or the trachea. While current clinical research considers these as redundant noise, they may contain physiologically relevant information. Approach. We propose a method to separate the signal generated by cardiac activity from the one caused by breathing activity. Using only information available from the SSP sensor, we estimate the heart rate and track its variations, then use a set of tuned filters to process the original signal in the frequency domain and reconstruct the cardiac signal. We also include an overview of the technical and physiological factors that may affect the quality of heart rate estimation. The output of our method is then used as a reference to remove the cardiac signal from the original SSP pressure signal, to also optimize the assessment of respiratory activity. We provide a qualitative comparison against methods based on filters with fixed frequency cutoffs. Main results. In comparison with electrocardiography (ECG)-derived heart rate, we achieve an agreement error of 0.06 ± 5.09 bpm, with minimal bias drift across the measurement range, and only 6.36% of the estimates larger than 10 bpm. Significance. Together with qualitative improvements in the characterization of respiratory effort, this opens the development of novel portable clinical devices for the detection and assessment of sleep disordered breathing.

Diagnosis of sleep apnea without sensors on the patient's face.

Thermistors, nasal cannulas, and respiratory inductance plethysmography (RIP) are the recommended reference sensors of the American Academy of Sleep Medicine (AASM) for the detection and characterization of apneas and hypopneas; however, these sensors are not well tolerated by patients and have poor scorability. We evaluated the performance of an alternative method using a combination of tracheal sounds (TSs) and RIP signals. Consecutive recordings of 70 adult patients from the Pays de la Loire Sleep Cohort were manually scored in random order using the AASM standard signals and the combination TS and RIP signals, without respiratory sensors placed on the patient's face. The TS-RIP scoring used the TS and RIP-flow signals for detection of apneas and hypopneas, respectively, and the suprasternal pressure and RIP belt signals for the characterization of apneas. Sensitivity and specificity of the TS-RIP combination were 96.21% and 91.34% for apnea detection and 89.94% and 93.25% for detecting hypopneas, respectively, with a kappa coefficient of 0.87. For the characterization of apneas, sensitivity and specificity were 98.67% and 96.17% for obstructive apneas, 92.66% and 99.36% for mixed apneas, and 96.14% and 98.89% for central apneas, respectively, with a kappa coefficient of 0.94. The TS-RIP scoring revealed a high agreement for classifying obstructive sleep apnea into severity classes (none, mild, moderate, and severe obstructive sleep apnea) with a Cohen's kappa coefficient of 0.96. Compared with the AASM reference sensors, the TS-RIP combination allows reliable noninvasive detection and characterization of respiratory events with a high degree of sensitivity and specificity. TS-RIP combination could be used for diagnosis of obstructive sleep apnea in adults, either as an alternative to the AASM sensors or in combination with the recommended AASM sensors.

Tracheal sounds for the scoring of sleep respiratory events in children.

Oronasal thermistor and nasal cannula are recommended for the scoring of respiratory events (RE) but these sensors are poorly tolerated in children. The aim of the study was to evaluate tracheal sounds (TS) and suprasternal pressure (SSP) for the scoring of RE during sleep in children. We compared the detection and characterization of RE by AASM-recommended sensors ("AASM" scoring), with the detection and characterization of RE by the combination of TS and SSP with respiratory inductance plethysmography-sum (TS-RIP scoring), and TS and SSP only (TS scoring). The recordings of 17 patients were analyzed. The TS, SSP, and RIP flow signals were present during 95%, 95%, and 99% of the validated recording time, respectively, as compared to 79% and 86% for nasal cannula and oronasal thermistor. A total of 1,456 RE were scored with the "AASM" scoring, 1,335 with the TS-RIP scoring, and 1,311 with the TS scoring. Sensitivity for apnea and hypopnea detection was 88% and 84% for the TS-RIP scoring, and 86% and 77% for the TS scoring. For apnea characterization, the TS-RIP scoring sensitivities and specificities were 97% and 100%, 76% and 98%, and 95% and 97%, for obstructive, mixed, and central apnea, respectively. For the TS scoring, they were 95% and 100%, 95% and 97%, and 91% and 97%, respectively. TS and SSP + RIP-sum has a good sensitivity and specificity for the detection and characterization of apnea and hypopnea in children. TS and SSP alone have good sensitivity and specificity for apnea detection and characterization but lower sensitivity for hypopnea detection.

Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring

IntroductionPolysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich...

Apnea and hypopnea characterization using esophageal pressure, respiratory inductance plethysmography, and suprasternal pressure: a comparative study

To determine if recording of suprasternal pressure (SSP) can classify apneas and hypopneas as reliably as respiratory inductance plethysmography (RIP) belts and to compare the two methods to classification with esophageal pressure (Pes), the reference method for assessing respiratory effort. In addition to polysomnographic recordings that included Pes, SSP was recorded. Recordings from 32 patients (25 males, mean age 66.7 ± 15.3years, and mean BMI 30.1 ± 4.5kg/m2) were used to compare the classification of detected apneas and hypopneas by three methods of respiratory effort evaluation (Pes, RIP belts, and SSP). Signals were analyzed randomly and independently from each other. All recordings were analyzed according to AASM guidelines. Using Pes as a reference for apnea characterization, the Cohen kappa (κ) was 0.93 for SSP and 0.87 for the RIP. The sensitivity/specificity of SSP was 97.0%/96.9% for obstructive, 93.9%/98.3% for central, and 94.9%/97.9% for mixed apneas. The sensitivity/specificity of the RIP was 97.4%/91.9% for obstructive, 87.5%/97.9% for central, and 85.6%/96.6% for mixed apneas. For hypopnea characterization using the Pes as a reference, κ was 0.92 for SSP and 0.86 for the RIP. The sensitivity/specificity of SSP was 99.7%/97.6% for obstructive and 97.6%/99.7% for central. The sensitivity/specificity of the RIP was 99.8%/81.1% for obstructive and 81.1%/99.8% for central. These results confirm the excellent agreement in the detection of respiratory effort between SSP, RIP belts, and Pes signals. Thus, we conclude that apnea and hypopnea characterization in adults with SSP is a reliable method.

Characterization of Respiratory Events in Obstructive Sleep Apnea Using Suprasternal Pressure Monitoring.

In obstructive sleep apnea (OSA) esophageal pressure (Pes) is the gold standard for measurement of respiratory effort, and respiratory inductance plethysmography (RIP) is considered an accepted measurement technique. However, the use of RIP could lead to limited accuracy in certain cases and therefore suprasternal pressure (SSP) monitoring might improve the reliability of OSA diagnosis. We aimed to use SSP for the visual characterization of respiratory events in adults and compared results to those obtained by RIP from polysomnography (PSG). In patients with OSA, a 1-night SSP recording using the PneaVoX sensor (Cidelec, Sainte-Gemmes-sur-Loire, France) was done. In parallel, PSG was performed according to American Academy of Sleep Medicine criteria. A subgroup of patients agreed to have Pes measurement in addition. Characterizations of apneas as obstructive, central, and mixed as well as hypopneas as central and obstructive were done by visual evaluation of SSP, RIP, and Pes in random order by two independent scores (S1 and S2). The sensitivity and specificity of characterization by SSP compared to RIP and to Pes were calculated. Synchronous recordings of SSP and PSG were analyzed from n = 34 patients with OSA (AHI 34.1 ± 24.2 events/h); 9 of them had synchronized Pes monitoring as well. Interscorer agreement for apnea characterization as obstructive, central, and mixed based on SSP, RIP, and Pes were found, with R2 values from 0.91-0.99. The sensitivity of SSP in apnea characterization with reference to RIP (S1/S2) was 91.5%/92.3% for obstructive, 82.7%/76.2% for central, and 87.4%/79.9% for mixed. The sensitivity of SSP in apnea characterization with reference to Pes was (S1/S2) 93.1%/92.1% for obstructive, 80.8%/81.6% for central, and 91.7%/90.8% for mixed. Hypopnea was only classified for the nine patients with Pes. This study demonstrated a good agreement in the detection of respiratory effort with the SSP signal using the PneaVoX sensor compared to the RIP belts signals as well as to the Pes signal. These findings were consistently found by two independent scorers. In summary, results suggest that SSP is a reliable signal for the classification of respiratory events and could be used as an additional tool for OSA characterization in clinical practice.

Apnea characterization by means of suprasternal pressure, respiratory inductance plethysmography and oesophageal pressure: a comparative study

Apnea characterization by means of suprasternal pressure, respiratory inductance plethysmography and oesophageal pressure: a comparative study

Validation of a Suprasternal Pressure Sensor for Sleep Apnea Classification in Children.

The recognition and characterization of respiratory events is crucial when interpreting sleep studies. The aim of the study was to validate the PneaVoX sensor, which integrates the recording of respiratory effort by means of suprasternal pressure (SSP), respiratory flow, and snoring for the classification of sleep apneas in children. Sleep recordings of 20 children with a median age of 7.5 (0.5-16.5) years were analyzed. Scoring of apneas according to the American Academy of Sleep Medicine (AASM) guidelines using nasal pressure, oronasal thermal sensor and respiratory efforts by means of respiratory inductance plethysmography (RIP), was compared to a scoring using the PneaVoX sensor and nasal pressure, without the oronasal thermal sensor nor RIP, during a dual blind study. The percentage of sleep time recording without artifacts was 97%, 97%, 87%, 65%, and 98% for the respiratory flow and SSP from the PneaVoX sensor, oronasal thermal sensor, nasal pressure, and RIP, respectively. As compared to the AASM scoring with RIP, sensitivity and specificity of the SSP for the scoring of central apneas were 75% and 99% for the first reader, and 70% and 100% for the second reader, respectively. Sensitivity and specificity for the scoring of obstructive apneas were 98% and 75%, and 100% and 70%, respectively. A significant number of apneas scored as central by RIP were scored as obstructive by the SSP. The PneaVoX sensor has a high degree of scorability in children. The PneaVoX sensor is a useful adjunct for characterizing apneas.

Validation of a suprasternal pressure transducer for apnea classification during sleep.

To validate a new method of evaluation of respiratory efforts during polysomnographic recordings. NA PARTICIPANTS: 26 patients with sleep apnea syndrome, either during diagnostic assessment (n=16) or under nasal continuous positive airway pressure (n=10). This method consists of measuring suprastemal pressure by a pressure transducer placed over the trachea above the sternal notch (Pst). It was compared to the reference method (ie, esophageal pressure) during the same polysomnogram. The analysis was based on 3,261 episodes of apnea, classified as obstructive in 2,556 cases, mixed in 347 cases, and central in 358 cases according to the esophageal pressure monitor. The concordance between the two methods was very good, with a sensitivity of Pst of 99.4% for the detection of apneas with respiratory efforts and a specificity of 93.6%. Twenty-three (6.4%) of the 358 central apneas were classified by Pst as apneas with respiratory efforts and 18 of the 353 central apneas classified by Pst were actually apneas with respiratory efforts on the esophageal pressure monitor. The suprasternal pressure transducer, which presents a good sensitivity and a good specificity for identification of respiratory efforts, can be used to classify apneas during polysomnographic recordings in clinical practice.

Atrioventricular activity as reflected in suprasternal pressure curves.

Atrioventricular activity as reflected in suprasternal pressure curves.

Suprasternal pressure curves in early mitral stenosis.

Suprasternal pressure curves in early mitral stenosis.

Suprasternal Pressure Curves in Mitral Insufficiency

Suprasternal Pressure Curves in Mitral Insufficiency

Suprasternal pressure curves in atrial flutter.

Suprasternal pressure curves in atrial flutter.