Sleep apnea severity based on estimated tidal volume and snoring features from tracheal signals.

Sleep apnea can be characterized by reductions in the respiratory tidal volume. Previous studies showed that the tidal volume can be estimated from tracheal sounds and movements called tracheal signals. Additionally, tracheal sounds include the sounds of snoring, a common symptom of obstructive sleep apnea. This study investigates the feasibility of estimating the severity of sleep apnea, as quantified by the apnea/hypopnea index (AHI), using the estimated tidal volume and snoring sounds extracted from tracheal signals. Tracheal signals were recorded simultaneously with polysomnography (PSG). The tidal volume was estimated from tracheal signals. The reductions in the tidal volume were detected as potential respiratory events. Additionally, features related to snoring sounds, which quantified variability, temporal clusters, and dominant frequency of snores, were extracted. A step-wise regression model and a greedy search algorithm were used sequentially to select the optimal set of features to estimate the apnea/hypopnea index and classify participants into healthy individuals and patients with sleep apnea. Sixty-one participants with suspected sleep apnea (age: 51 ± 16, body mass index: 29.5 ± 6.4 kg/m2 , apnea/hypopnea index: 20.2 ± 21.2 event/h) who were referred for a sleep test were recruited. The estimated apnea/hypopnea index was strongly correlated with the polysomnography-based apnea/hypopnea index (R2  = 0.76, p < 0.001). The accuracy of detecting sleep apnea for the apnea/hypopnea index cutoff of 15 events/h was 78.69% and 83.61% with and without using snore-related features. These findings suggest that acoustic estimation of airflow and snore-related features can provide a convenient and reliable method for screening of sleep apnea.

Relative tidal volume and respiratory airflow estimation using tracheal sound and movement during sleep.

Airflow is the reference signal to assess sleep respiratory disorders, such as sleep apnea. Previous studies estimated airflow using tracheal sounds in short segments with specific airflow rates, while requiring calibration or a few breaths for tuning the relationship between sound energy and airflow. Airflow-sound relationship can change by posture, sleep stage and airflow rate or tidal volume. We investigated the possibility of estimating surrogates of tidal volume without calibration in the adult sleep apnea population using tracheal sounds and movements. Two surrogates of tidal volume: thoracoabdominal range of sum movement and airflow level were estimated. Linear regression was used to estimate thoracoabdominal range of sum movement from sound energy and the range of movements. The sound energy lower envelope was found to correlate with airflow level. The agreement between reference and estimated signals was assessed by repeated-measure correlation analysis. The estimated tidal volumes were used to estimate the airflow signal. Sixty-one participants (30 females, age: 51 ± 16 years, body mass index: 29.5 ± 6.4 kg m-2 , and apnoea-hypopnea index: 20.2 ± 21.2) were included. Reference and estimated thoracoabdominal range of sum movement of whole night data were significantly correlated with the reference signal extracted from polysomnography (r = 0.5 ± 0.06). Similarly, significant correlations (r = 0.3 ± 0.05) were found for airflow level. Significant differences in estimated surrogates of tidal volume were found between normal breathing and apnea/hypopnea. Surrogate of airflow can be extracted from tracheal sounds and movements, which can be used for assessing the severity of sleep apnea and even phenotyping sleep apnea patients based on the estimated airflow shape.

Torso geometry reconstruction and body surface electrode localization using three-dimensional photography.

We conducted a prospective clinical study (n=14; 29% female) to assess the accuracy of a three-dimensional (3D) photography-based method of torso geometry reconstruction and body surface electrodes localization. The position of 74 body surface electrocardiographic (ECG) electrodes (diameter 5mm) was defined by two methods: 3D photography, and CT (marker diameter 2mm) or MRI (marker size 10×20mm) imaging. Bland-Altman analysis showed good agreement in X (bias -2.5 [95% limits of agreement (LoA) -19.5 to 14.3] mm), Y (bias -0.1 [95% LoA -14.1 to 13.9] mm), and Z coordinates (bias -0.8 [95% LoA -15.6 to 14.2] mm), as defined by the CT/MRI imaging, and 3D photography. The average Hausdorff distance between the two torso geometry reconstructions was 11.17±3.05mm. Thus, accurate torso geometry reconstruction using 3D photography is feasible. Body surface ECG electrodes coordinates as defined by the CT/MRI imaging, and 3D photography, are in good agreement.

Global Electric Heterogeneity Risk Score for Prediction of Sudden Cardiac Death in the General Population: The Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health (CHS) Studies.

BACKGROUND: Asymptomatic individuals account for the majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and noninvasive SCD risk stratification tools is necessary. METHODS AND RESULTS: Participants from the Atherosclerosis Risk in Communities study and Cardiovascular Health Study (n=20 177; age, 59.3±10.1 years; age range, 44-100 years; 56% female; 77% white) were followed up for 14.0 years (median). Five ECG markers of global electric heterogeneity (GEH; sum absolute QRST integral, spatial QRST angle, spatial ventricular gradient [SVG] magnitude, SVG elevation, and SVG azimuth) were measured on standard 12-lead ECGs. Cox proportional hazards and competing risks models evaluated associations between GEH electrocardiographic parameters and SCD. An SCD competing risks score was derived from demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1000 person-years. After multivariable adjustment, baseline GEH parameters and large increases in GEH parameters over time were independently associated with SCD. Final SCD risk scores included age, sex, race, diabetes mellitus, hypertension, coronary heart disease, stroke, and GEH parameters as continuous variables. When GEH parameters were added to clinical/demographic factors, the C statistic increased from 0.777 to 0.790 (P=0.008), the risk score classified 10-year SCD risk as high (>5%) in 7.2% of participants, 10% of SCD victims were appropriately reclassified into a high-risk category, and only 1.4% of SCD victims were inappropriately reclassified from high to intermediate risk. The net reclassification index was 18.3%. CONCLUSIONS: Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. The addition of GEH parameters to clinical characteristics improves SCD risk prediction.

Optimal configuration of adhesive ECG patches suitable for long-term monitoring of a vectorcardiogram.

The purpose of this study was to develop optimal configuration of adhesive ECG patches placement on the torso, which would provide the best agreement with the Frank orthogonal ECGs. Ten seconds of orthogonal ECG followed by 3-5min of ECGs using patches at 5 different locations simultaneously on the torso were recorded in 50 participants at rest in sitting position. Median beat was generated for each ECG and 3 patch ECGs that best correlate with orthogonal ECGs were selected for each participant. For agreement analysis, spatial QRS-T angle, spatial QRS and T vector characteristics, spatial ventricular gradient, roundness, thickness and planarity of vectorcardiographic (VCG) loops were measured. Key VCG parameters showed high agreement in Bland-Altman analysis (spatial QRS-T angle on 3-patch ECG vs. Frank ECG bias 0.3 (95% limits of agreement [-6.23;5.71 degrees]), Lin's concordance coefficient=0.996). In conclusion, newly developed orthogonal 3-patch ECG can be used for long-term VCG monitoring.

Correlation between the high-frequency content of the QRS on murine surface electrocardiogram and the sympathetic nerves density in left ventricle after myocardial infarction: Experimental study.

Denervated post-infarct scar is arrhythmogenic. Our aim was to compare QRS frequency content in denervated and innervated left ventricular (LV) scar. In-vivo single lead ECG telemetry device was implanted in 17 heterozygous PTPσ (HET) and 7 lacking PTPσ (KO) transgenic mice. Myocardial infarction (MI) with reperfusion and sham surgery was performed. HET mice developed a denervated scar, whereas KO mice developed innervated scar. The power spectral density was used to assess the QRS frequency content. Denervated as compared to innervated post-MI scar was characterized by the higher relative contribution of 300-500 Hz (14 ± 1 vs. 9 ± 1%; P = 0.001) but reduced relative contribution of 200-300 Hz (86 ± 1 vs. 91 ± 1%; P = 0.001). Norepinephrine concentration in peri-infarct zone correlated with both 1-200 Hz (r = 0.75; P = 0.03) and 200-500 Hz QRS power (r = 0.73; P = 0.04). Sympathetic fiber density within the infarct correlated with 200-300/200-500 Hz QRS power ratio (r = 0.56; P = 0.005). Intracellular sigma peptide injections in post-MI HET mice restored the QRS power.

Electrophysiologic Substrate and Risk of Mortality in Incident Hemodialysis.

The single leading cause of mortality on hemodialysis is sudden cardiac death. Whether measures of electrophysiologic substrate independently associate with mortality is unknown. We examined measures of electrophysiologic substrate in a prospective cohort of 571 patients on incident hemodialysis enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease Study. A total of 358 participants completed both baseline 5-minute and 12-lead electrocardiogram recordings on a nondialysis day. Measures of electrophysiologic substrate included ventricular late potentials by the signal-averaged electrocardiogram and spatial mean QRS-T angle measured on the averaged beat recorded within a median of 106 days (interquartile range, 78-151 days) from dialysis initiation. The cohort was 59% men, and 73% were black, with a mean±SD age of 55±13 years. Transthoracic echocardiography revealed a mean±SD ejection fraction of 65.5%±12.0% and a mean±SD left ventricular mass index of 66.6±22.3 g/m2.7 During 864.6 person-years of follow-up, 77 patients died; 35 died from cardiovascular causes, of which 15 were sudden cardiac deaths. By Cox regression analysis, QRS-T angle ≥75° significantly associated with increased risk of cardiovascular mortality (hazard ratio, 2.99; 95% confidence interval, 1.31 to 6.82) and sudden cardiac death (hazard ratio, 4.52; 95% confidence interval, 1.17 to 17.40) after multivariable adjustment for demographic, cardiovascular, and dialysis factors. Abnormal signal-averaged electrocardiogram measures did not associate with mortality. In conclusion, spatial QRS-T angle but not abnormal signal-averaged electrocardiogram significantly associates with cardiovascular mortality and sudden cardiac death independent of traditional risk factors in patients starting hemodialysis.

Atrial Fibrillation Predictors: Importance of the Electrocardiogram.

Atrial fibrillation (AF) is the most common arrhythmia in adults and is associated with significant morbidity and mortality. Substantial interest has developed in the primary prevention of AF, and thus the identification of individuals at risk for developing AF. The electrocardiogram (ECG) provides a wealth of information, which is of value in predicting incident AF. The PR interval and P wave indices (including P wave duration, P wave terminal force, P wave axis, and other measures of P wave morphology) are discussed with regard to their ability to predict and characterize AF risk in the general population. The predictive value of the QT interval, ECG criteria for left ventricular hypertrophy, and findings of atrial and ventricular ectopy are also discussed. Efforts are underway to develop models that predict AF incidence in the general population; however, at present, little information from the ECG is included in these models. The ECG provides a great deal of information on AF risk and has the potential to contribute substantially to AF risk estimation, but more research is needed.

Quantitative Assessment of Vectorcardiographic Loop Morphology.

Vectorcardiography (VCG), developed 100years ago, characterizes clinically important electrophysiological properties of the heart. In this study, VCG QRS loop roundness, planarity, thickness, rotational angle, and dihedral angle were measured in 81 healthy control subjects (39.0±14.2y; 51.8% male; 94% white), and 8 patients with infarct-cardiomyopathy and sustained monomorphic ventricular tachycardia (VT) (68.0±7.8y, 37.5% male). The angle between two consecutive QRS vectors was defined as the rotational angle, while dihedral angle quantified planar alteration over the QRS loop. In VT subjects, planarity index decreased (0.63±0.22 vs. 0.88±0.10; P=0.014), and dihedral angle was significantly more variable (variance of dihedral angle, median (IQR): 897(575-1450) vs. 542(343-773); P=0.029; rMSSD: 47.7±12.7 vs. 35.1±13.1; P=0.027). Abnormal electrophysiological substrate in VT patients is characterized by the appearance of QRS loop folding, likely due to local conduction block. The presence of fragmented QRS complexes on the 12-lead ECG had low sensitivity (31%) for detecting QRS loop folding on the VCG.

Joint symbolic dynamics for the assessment of cardiovascular and cardiorespiratory interactions.

Beat-to-beat variations in heart period provide information on cardiovascular control and are closely linked to variations in arterial pressure and respiration. Joint symbolic analysis of heart period, systolic arterial pressure and respiration allows for a simple description of their shared short-term dynamics that are governed by cardiac baroreflex control and cardiorespiratory coupling. In this review, we discuss methodology and research applications. Studies suggest that analysis of joint symbolic dynamics provides a powerful tool for identifying physiological and pathophysiological changes in cardiovascular and cardiorespiratory control.

VV' Alternans Triplets on Near-Field ICD Intracardiac Electrogram is Associated with Mortality.

BACKGROUND: In heart failure patients with implantable cardioverter defibrillator (ICD) the risk of death from causes other than tachyarrhythmia is substantial. Benefit from ICD is determined by two competing risks: appropriate ICD shock or nonarrhythmic death. The goal of the study was to test predictors of competing outcomes. METHODS: Patients with structural heart disease (N = 234, mean age 58.5 ± 15.1; 71% men, 80% whites, 61% ischemic cardiomyopathy) and primary (75%) or secondary prevention ICD underwent a 5-minute baseline near-field electrogram (NF EGM) recording. VV' alternans triplets were quantified as a percentage of three sinus VV' cycles sequences of "short-long-short" or "long-short-long" order. Appropriate ICD shock for fast ventricular tachycardia (FVT, cycle length ≤240 ms)/ventricular fibrillation (VF) and composite nonarrhythmic death (pump failure death or heart transplant) served as competing outcomes. RESULTS: Over a median follow-up of 2.4 years, 26 patients (4.6% per person-year of follow-up) developed FVT/VF with ICD shock, and 35 (6.3% per person-year of follow-up) had nonarrhythmic death. In competing risk analysis, after adjustment for demographics, left ventricular ejection fraction, New York Heart Association class, cardiomyopathy type, use of class I antiarrhythmics, and diabetes, increased percentage of VV' alternans triplets (>69%) was associated with nonarrhythmic death (subhazard ratio [SHR] 2.09; 95% confidence interval [CI] 1.03-4.23; P = 0.041), rather than with FVT/VF (SHR 1.05; 95% CI 0.45-2.46; P = 0.901). Risk of nonarrhythmic death was especially high in diabetics with VV' alternans triplets in the highest quartile (SHR 3.46; 95% CI 1.41-8.50; P = 0.007). CONCLUSION: In ICD patients with structural heart disease sinus VV' alternans triplets on NF EGM is independently associated with nonarrhythmic death, rather than with FVT/VF.

Increased thoracoabdominal asynchrony during breathing periods free of discretely scored obstructive events in children with upper airway obstruction.

OBJECTIVE: This study aims to investigate the impact of upper airway obstruction (UAO) in children by measuring thoracoabdominal asynchrony (TAA) during periods of sleep apnea/hypopnea and during scored-event-free (SEF) breathing periods. METHODS: Respiratory inductive plethysmographic signals were extracted from polysomnographic data, recorded before and after adenotonsillectomy in 40 children with UAO and 40 healthy, matched children at equivalent time points. Thoracoabdominal asynchrony was computed using a Hilbert transform-based phase difference estimation method in SEF periods during stage 2, stage 4 non-rapid eye movement (NREM), and rapid eye movement (REM) sleep and compared between the groups. RESULTS: At baseline, in the UAO group, TAA during obstructions were significantly higher than TAA during SEF periods in both stage 2 and REM sleep. Compared to controls, children with UAO had a significantly higher TAA during SEF periods in stage 2, stage 4 sleep, and REM sleep. This between-group difference was not significant post adenotonsillectomy. UAO group showed a significant decrease in TAA compared to their baseline during SEF stage 2 and 4 NREM, but not in REM. CONCLUSION: Upper airway obstruction in children is associated with increased TAA during SEF periods, indicative of continuous partial obstruction of the upper airway. Adenotonsillectomy decreased this effect significantly in non-REM sleep as evidenced by reduced asynchrony levels post-surgery. TAA assessment during sleep may therefore provide additional diagnostic information.

High atrioventricular phase index on near-field intracardiac electrogram is associated with risk of ventricular arrhythmia.

The purposes of this study were to characterize and quantify concordance between consecutive atrial and ventricular activation time points through analysis of phases and to explore its association with outcomes in patients with implantable cardioverter-defibrillator (ICD). Patients with structural heart disease and dual-chamber ICDs underwent 5min baseline right ventricular (V) near-field and atrial (A) electrogram (EGM) recording. The cross-dependencies of phase dynamics of the changes in consecutive A (AA') and V (VV') were quantified and the AV phase dependency index was determined. In Cox regression analysis, a high AV phase index (in the highest quartile, >0.259) was significantly associated with higher risk of ventricular tachyarrhythmias (HR 2.84; 95% CI 1.05-7.67; P=0.04). In conclusion, in ICD patients with structural heart disease, high sinus AV phase dependency index on EGM is associated with the risk of ventricular arrhythmia.

Construction of intracardiac vectorcardiogram from implantable cardioverter-defibrillator intracardiac electrograms.

We constructed an intracardiac vectorcardiogram from 3 configurations of intracardiac cardiovertor defibrilator (ICD) electrograms (EGMs). Six distinctive 3 lead combinations were selected out of five leads: can to right ventricular coil (RVC); RVC to superior vena cava coil (SVC); atrial lead tip (A-tip) to right ventricular (RV)-ring; can to RV-ring; RV-tip to RVC, in a patient with dual chamber ICD. Surface spatial QRS-T angle (119.8°) was similar to intracardiac spatial QRS-T angle derived from ICD EGMs combination A (101.3°), B (96.1°), C (92.8°), D (95.2), E (99.0), F (96.2) and median (101.5). Future validation of the novel method is needed.

Respiratory sinus arrhythmia during sleep in children with upper airway obstruction.

Upper airway obstruction during adulthood is associated with cardiovascular morbidity; cardiovascular consequences of childhood upper airway obstruction are less well established. This study aimed at investigating the effect of childhood upper airway obstruction on respiratory sinus arrhythmia as a measure of cardiac vagal modulation during night-time sleep. Overnight polysomnography was conducted in 40 healthy children (20 M; age: 7.5 ± 2.6 years; body mass index percentile: 60.7 ± 26.4%) and 40 children with upper airway obstruction (24 M; age: 7.5 ± 2.7 years; body mass index percentile: 65.8 ± 31.9%). We used the phase-averaging technique to compute respiratory sinus arrhythmia amplitude and phase delay. To study sleep stage effects and the effect of upper airway obstruction, respiratory sinus arrhythmia was measured during all artefact-free sleep episodes, and after exclusion of respiratory events. A significant increase in respiratory sinus arrhythmia amplitude and phase delay was observed during stage 4 sleep as compared with rapid eye movement sleep in both groups (amplitude: controls = 0.10 ± 0.03 versus 0.07 ± 0.02 s, P < 0.01, respectively, and upper airway obstruction = 0.07 ± 0.03 versus 0.05 ± 0.03 s, P < 0.05, respectively; phase delay: controls = 3.1 ± 0.1 versus 3.0 ± 0.1 rad, P < 0.05, respectively, and upper airway obstruction = 3.13 ± 0.04 versus 3.04 ± 0.08 rad, P < 0.01, respectively). A significant association between respiratory sinus arrhythmia and apnea/hypopnea index was observed during stage 2 sleep in children with upper airway obstruction. Compared with healthy controls, a significant decrease in respiratory sinus arrhythmia amplitude during stage 2 sleep was observed in children with upper airway obstruction (0.09 ± 0.03 versus 0.06 ± 0.03 s, P < 0.05). However, this difference was not apparent when respiratory events were excluded from analysis. Importantly, respiratory sinus arrhythmia showed a strong negative correlation with body mass index. In conclusion, night-time respiratory sinus arrhythmia in children is sleep stage dependent and normal during quiet sleep in children with relatively mild upper airway obstruction.

Joint symbolic analyses of heart rate, blood pressure, and respiratory dynamics.

INTRODUCTION: The dynamics of cardiovascular variables are modulated by respiration. The aim of this study was to assess baroreflex function in normal subjects based on the joint symbolic dynamics of heart rate, blood pressure and respiration. METHODS: ECG, continuous blood pressure and respiration were recorded in ten healthy subjects during rest in the supine position and upon standing. Beat-to-beat time series of heart rate, systolic blood pressure and respiratory phase were extracted and transformed into binary symbol sequences. Words of length two that were reflective of baroreflex activity were statistically analysed with respect to the respiratory phase. RESULTS: Symbolic analysis showed a significant influence of the respiratory phase on the occurrence of baroreflex patterns. Upon standing, the frequency of baroreflex words increased and the effect of respiration appeared to be reduced. CONCLUSIONS: Symbolic dynamics provide a simple representation of cardiovascular dynamics and may be useful for assessing baroreflex function.

Modeling and Reproducing Textile Sensor Noise: Implications for Textile-Compatible Signal Processing Algorithms.

Smart textiles provide an opportunity to simultaneously record various electrophysiological signals, e.g., ECG, from the human body in a non-invasive and continuous manner. Accurate processing of ECG signals recorded using textile sensors is challenging due to the very low signal-to-noise ratio (SNR). Signal processing algorithms that can extract ECG signals out of textile-based electrode recordings, despite low SNR are needed. Presently, there are no textile ECG datasets available to develop, test and validate these algorithms. In this paper we attempted to model textile ECG signals by adding the textile sensor noise to open access ECG signals. We employed the linear predictive coding method to model different features of this noise. By approximating the linear predictive coding residual signals using Kernel Density Estimation, an artificial textile ECG noise signal was generated by filtering the residual signal with the linear predictive coding coefficients. The synthetic textile sensor noise was added to the MIT-BIH Arrhythmia Database (MITDB), thus creating Textile-like ECG dataset consisting of 108 trials (30 min each). Furthermore, a Python code for generating textile-like ECG signals with variable SNR was also made available online. Finally, to provide a benchmark for the performance of R-peak detection algorithms on textile ECG, the five common R-peak detection algorithms: Pan & Tompkins, improved Pan & Tompkins (in Biosppy), Hamilton, Engelse, and Khamis, were tested on textile-like MITDB. This work provides an approach to generating noisy textile ECG signals, and facilitating the development, testing, and evaluation of signal processing algorithms for textile ECGs.

Automatic Respiratory Phase Identification Using Tracheal Sounds and Movements During Sleep.

One of the most important signals to assess respiratory function, especially in patients with sleep apnea, is airflow. A convenient method to estimate airflow is based on analyzing tracheal sounds and movements. However, this method requires accurate identification of respiratory phases. Our goal is to develop an automatic algorithm to analyze tracheal sounds and movements to identify respiratory phases during sleep. Data from adults with suspected sleep apnea who were referred for in-laboratory sleep studies were included. Simultaneously with polysomnography, tracheal sounds and movements were recorded with a small wearable device attached to the suprasternal notch. First, an adaptive detection algorithm was developed to localize the respiratory phases in tracheal sounds. Then, for each phase, a set of morphological features from sound energy and tracheal movement were extracted to classify the localized phases into inspirations or expirations. The average error and time delay of detecting respiratory phases were 7.62% and 181 ms during normal breathing, 8.95% and 194 ms during snoring, and 13.19% and 220 ms during respiratory events, respectively. The average classification accuracy was 83.7% for inspirations and 75.0% for expirations. Respiratory phases were accurately identified from tracheal sounds and movements during sleep.

Cardiorespiratory response to spontaneous cortical arousals during stage 2 and rapid eye movement sleep in healthy children.

Arousal from sleep is associated with transient and abrupt cardiorespiratory changes, and elevated arousals associated with sleep disorders may trigger adverse cardiovascular sequela. In this paper, we provide the first data in children on cardiorespiratory responses to cortical arousal. Heart rate and ventilatory responses to arousal from stage 2 and rapid eye movement (REM) sleep were investigated in 40 normal, healthy Caucasian children (age: 7.7 +/- 2.6 years; body mass index z-score: 0.30 +/- 0.8). All children underwent overnight polysomnography studies. Cortical arousals were scored according to standard criteria. Heart rate changes were assessed over 30 s, starting 15 s prior to cortical arousal onset. Breathing rates were quantified three breaths before and after arousal onset. Arousals from stage 2 as well as REM sleep resulted in an R-R interval shortening of about 15%, independent of age and gender. The R-R interval shortening initiated at least 3 s before the cortical arousal onset. The breathing interval immediately after cortical arousal onset was significantly shortened (P < 0.001). In conclusion, cortical arousals in children are associated with an increase in breathing rate and significant heart rate accelerations, which typically precede the cortical arousal onset.

Portable diagnosis of sleep apnea with the validation of individual event detection.

STUDY OBJECTIVE: To develop an algorithm for improving apnea hypopnea index (AHI) estimation which includes event by event validation and event duration estimation. The algorithm uses breathing sounds, respiratory related movements and blood oxygen saturation (SaO2). METHODS: Adults with suspected sleep apnea underwent overnight polysomnography (PSG) at Toronto Rehabilitations Institute. Simultaneously with PSG, breathing sounds and respiratory related movements were recorded over the suprasternal notch using the Patch. The Patch had a microphone and an accelerometer to record respiratory sounds and movement, respectively. First, we calculated the amount of drops in SaO2 from pulse oximeter. Subsequently, energy of breaths and accelerometer were extracted. Features were normalized, weighted, summed and passed through a threshold to estimate PatchAHI. PatchAHI was compared to the AHI obtained from PSG (PSGAHI). Furthermore, performance of event detection was evaluated using F1-score. Moreover, event duration difference between estimated and PSG-based events was compared. RESULTS: Data from 69 subjects were investigated. PatchAHI had high correlation with PSGAHI (r2 = 0.88). Considering a diagnostic AHI cut-off of ≥15, sensitivity and specificity were 91.42 ± 11.92% and 89.29 ± 7.62%, respectively. F1-score for individual event detection increased from 0.22 ± 0.10 for AHI≤5 to 0.72 ± 0.09 for AHI >30. Moreover, event duration difference between estimated events and PSG-based events was 5.33 ± 8.17 sec. CONCLUSION: Our proposed algorithm had high accuracy in estimating individual respiratory events during sleep. The algorithm can increase reliability of acoustic methods for diagnosis of sleep apnea at home.