Piezoelectric rubber sheet sensor: a promising tool for home sleep apnea testing.

PURPOSE: This study aimed to develop an unobtrusive method for home sleep apnea testing (HSAT) utilizing micromotion signals obtained by a piezoelectric rubber sheet sensor. METHODS: Algorithms were designated to extract respiratory and ballistocardiogram components from micromotion signals and to detect respiratory events as the characteristic separation of the fast envelope of the respiration component from the slow envelope. In 78 adults with diagnosed or suspected sleep apnea, micromotion signal was recorded with a piezoelectric rubber sheet sensor placed beneath the bedsheet during polysomnography. In a half of the subjects, the algorithms were optimized to calculate respiratory event index (REI), estimating apnea-hypopnea index (AHI). In the other half of subjects, the performance of REI in classifying sleep apnea severity was evaluated. Additionally, the predictive value of the frequency of cyclic variation in heart rate (Fcv) obtained from the ballistocardiogram was assessed. RESULTS: In the training group, the optimized REI showed a strong correlation with the AHI (r = 0.93). Using the optimal cutoff of REI ≥ 14/h, subjects with an AHI ≥ 15 were identified with 77.8% sensitivity and 90.5% specificity. When applying this REI to the test group, it correlated closely with the AHI (r = 0.92) and identified subjects with an AHI ≥ 15 with 87.5% sensitivity and 91.3% specificity. While Fcv showed a modest correlation with AHI (r = 0.46 and 0.66 in the training and test groups), it lacked independent predictive power for AHI. CONCLUSION: The analysis of respiratory component of micromotion using piezoelectric rubber sheet sensors presents a promising approach for HSAT, providing a practical and effective means of estimating sleep apnea severity.

Enhanced detection of abnormalities in heart rate variability and dynamics by 7-day continuous ECG monitoring.

BACKGROUND: The analysis of heart rate variability (HRV) and heart rate (HR) dynamics by Holter ECG has been standardized to 24 hs, but longer-term continuous ECG monitoring has become available in clinical practice. We investigated the effects of long-term ECG on the assessment of HRV and HR dynamics. METHODS: Intraweek variations in HRV and HR dynamics were analyzed in 107 outpatients with sinus rhythm. ECG was recorded continuously for 7 days with a flexible, codeless, waterproof sensor attached on the upper chest wall. Data were divided into seven 24-h segments, and standard time- and frequency-domain HRV and nonlinear HR dynamics indices were computed for each segment. RESULTS: The intraweek coefficients of variance of HRV and HR dynamics indices ranged from 2.9% to 26.0% and were smaller for frequency-domain than for time-domain indices, and for indices reflecting slower HR fluctuations than faster fluctuations. The indices with large variance often showed transient abnormalities from day to day over 7 days, reducing the positive predictive accuracy of the 24-h ECG for detecting persistent abnormalities over 7 days. Conversely, 7-day ECG provided 2.3- to 6.5-fold increase in sensitivity to detect persistent plus transient abnormalities compared with 24-h ECG. It detected an average of 1.74 to 2.91 times as many abnormal indices as 24-h ECG. CONCLUSIONS: Long-term ECG monitoring increases the accuracy and sensitivity of detecting persistent and transient abnormalities in HRV and HR dynamics and allows discrimination between the two types of abnormalities. Whether this discrimination improves risk stratification deserves further studies.

Night-to-night variability of sleep apnea detected by cyclic variation of heart rate during long-term continuous ECG monitoring.

BACKGROUND: Sleep apnea is common in patients with cardiovascular disease and is a factor that worsens prognosis. Holter 24-h ECG screening for sleep apnea is beneficial in the care of these patients, but due to high night-to-night variability of sleep apnea, it can lead to misdiagnosis and misclassification of disease severity. METHODS: To investigate the long-term dynamic behavior of sleep apnea, seven-day ECGs recorded with a patch ECG recorder in 120 patients were analyzed for the cyclic variation of heart rate (CVHR) during sleep periods as determined by a built-in three-axis accelerometer. RESULTS: The frequency of CVHR (Fcv) showed considerable night-to-night variability (coefficient of variance, 66 ± 35%), which was consistent with the night-to-night variability in apnea-hypopnea index and oxygen desaturation index reported in earlier studies. In patients with presumed moderate-to-severe sleep apnea (Fcv > 15 cph at least one night), it was missed on 62% of nights, and on at least one night in 88% of patients. The CV of Fcv was negatively correlated with the average of Fcv, suggesting that patients with mild sleep apnea show greater night-to-night variability and would benefit from long-term assessment. The average Fcv was higher in the supine position, but the night-to-night variability was not explained by the night-to-night variability of time spent in the supine position. CONCLUSIONS: CVHR analysis of long-term ambulatory ECG recordings is useful for improving the reliability of screening for sleep apnea without placing an extra burden on patients with cardiovascular disease and their care.

Redundancy among risk predictors derived from heart rate variability and dynamics: ALLSTAR big data analysis.

BACKGROUND: Many indices of heart rate variability (HRV) and heart rate dynamics have been proposed as cardiovascular mortality risk predictors, but the redundancy between their predictive powers is unknown. METHODS: From the Allostatic State Mapping by Ambulatory ECG Repository project database, 24-hr ECG data showing continuous sinus rhythm were extracted and SD of normal-to-normal R-R interval (SDNN), very-low-frequency power (VLF), scaling exponent α1 , deceleration capacity (DC), and non-Gaussianity λ25s were calculated. The values were dichotomized into high-risk and low-risk values using the cutoffs reported in previous studies to predict mortality after acute myocardial infarction. The rate of multiple high-risk predictors accumulating in the same person was examined and was compared with the rate expected under the assumption that these predictors are independent of each other. RESULTS: Among 265,291 ECG data from the ALLSTAR database, the rates of subjects with high-risk SDNN, DC, VLF, α1 , and λ25s values were 2.95, 2.75, 5.89, 15.75, and 18.82%, respectively. The observed rate of subjects without any high-risk value was 66.68%, which was 1.10 times the expected rate (60.74%). The ratios of observed rate to the expected rate at which one, two, three, four, and five high-risk values accumulate in the same person were 0.73 times (24.10 and 32.82%), 1.10 times (6.56 and 5.99%), 4.26 times (1.87 and 0.44%), 47.66 times (0.63 and 0.013%), and 1,140.66 times (0.16 and 0.00014%), respectively. CONCLUSIONS: High-risk predictors of HRV and heart rate dynamics tend to cluster in the same person, indicating a high degree of redundancy between them.

Risk stratification after acute myocardial infarction by amplitude-frequency mapping of cyclic variation of heart rate.

BACKGROUND: Blunted cyclic variation of heart rate (CVHR), measured as a decrease in CVHR amplitude (Acv), predicts mortality risk after acute myocardial infarction (AMI). However, Acv also can be reduced in mild sleep apnea with mild O2 desaturation. We investigated whether Acv's predictive power for post-AMI mortality could be improved by considering the effect of sleep apnea severity. METHODS: In 24-hr ECG in 265,291 participants of the Allostatic State Mapping by Ambulatory ECG Repository project, sleep apnea severity was estimated by the frequency of CVHR (Fcv) measured by an automated algorithm for auto-correlated wave detection by adaptive threshold (ACAT). The distribution of Acv on the Acv-Fcv relation map was modeled by percentile regression, and a function converting Acv into percentile value was developed. In the retrospective cohort of the Enhancing Recovery in Coronary Heart Disease (ENRICHD) study, consisting of 673 survivors and 44 non-survivors after AMI, the mortality predictive power of percentile Acv calculated by the function was compared with that of unadjusted Acv. RESULTS: Among the ALLSTAR ECG data, low Acv values appeared more likely when Fcv was low. The logistic regression analysis for mortality in the ENRICHD cohort showed c-statistics of 0.667 (SE, 0.041), 0.817 (0.035), and 0.843 (0.030) for Fcv, unadjusted Acv, and the percentile Acv, respectively. Compared with unadjusted Acv, the percentile Acv showed a significant net reclassification improvement of 0.90 (95% CI, 0.51-1.42). CONCLUSIONS: The predictive power of Acv for post-AMI mortality is improved by considering its relation to sleep apnea severity estimated by Fcv.

Sensing of Microvascular Vasomotion Using Consumer Camera.

In this paper, we will introduce a method for observing microvascular waves (MVW) by extracting different images from the available images in the video taken with consumer cameras. Microvascular vasomotion is a dynamic phenomenon that can fluctuate over time for a variety of reasons and its sensing is used for variety of purposes. The special device, a side stream dark field camera (SDF camera) was developed in 2015 for the medical purpose to observe blood flow from above the epidermis. However, without using SDF cameras, smart signal processing can be combined with a consumer camera to analyze the global motion of microvascular vasomotion. MVW is a propagation pattern of microvascular vasomotions which reflects biological properties of vascular network. In addition, even without SDF cameras, MVW can be analyzed as a spatial and temporal pattern of microvascular vasomotion using a combination of advanced signal processing with consumer cameras. In this paper, we will demonstrate that such vascular movements and MVW can be observed using a consumer cameras. We also show a classification using it.

Optimal length of R-R interval segment window for Lorenz plot detection of paroxysmal atrial fibrillation by machine learning.

BACKGROUND: Heartbeat interval Lorenz plot (LP) imaging is a promising method for detecting atrial fibrillation (AF) in long-term monitoring, but the optimal segment window length for the LP images is unknown. We examined the performance of AF detection by LP images with different segment window lengths by machine learning with convolutional neural network (CNN). LP images with a 32 × 32-pixel resolution of non-overlapping segments with lengths between 10 and 500 beats were created from R-R intervals of 24-h ECG in 52 patients with chronic AF and 58 non-AF controls as training data and in 53 patients with paroxysmal AF and 52 non-AF controls as test data. For each segment window length, discriminant models were made by fivefold cross-validation subsets of the training data and its classification performance was examined with the test data. RESULTS: In machine learning with the training data, the averages of cross-validation scores were 0.995 and 0.999 for 10 and 20-beat LP images, respectively, and > 0.999 for 50 to 500-beat images. The classification of test data showed good performance for all segment window lengths with an accuracy from 0.970 to 0.988. Positive likelihood ratio for detecting AF segments, however, showed a convex parabolic curve linear relationship to log segment window length and peaked at 85 beats, while negative likelihood ratio showed monotonous increase with increasing segment window length. CONCLUSIONS: This study suggests that the optimal segment window length that maximizes the positive likelihood ratio for detecting paroxysmal AF with 32 × 32-pixel LP image is 85 beats.

Very low frequency component of heart rate variability as a marker for therapeutic efficacy in patients with obstructive sleep apnea: Preliminary study.

BACKGROUND: Although positive airway pressure (PAP) therapy is effective for treating obstructive sleep apnea (OSA), some patients with severe OSA are intolerable to this treatment, which may lead to an increase in the mortality and morbidity of cardiovascular diseases. We investigated the relationship between heart rate variability (HRV) and sleep parameters during natural sleep and treatment of patients with OSA. MATERIALS AND METHODS: This was the cross-sectional observation study. Patients were 17 males with severe OSA who were unable to accept continuous PAP. Standard polysomnography was performed for two consecutive nights, i.e., during natural sleep and following night with bilevel PAP (BiPAP) treatment. Time-dependent responses of the amplitudes of low frequency (LF), very low frequency (VLF), and high frequency components of HRV were assessed with the technique of complex demodulation. RESULTS: Apnea-hypopnea index, oxygen desaturation time, and percentage of stage 1 sleep were significantly reduced, whereas the percentages of rapid eye movement and stages 3 + 4 sleep were increased, by BiPAP treatment. Therapy also reduced the amplitudes of VLF and LF components of HRV. Difference in amplitudes of VLF during natural sleep and treatment with BiPAP was significantly correlated with difference in percentages of stage 1 and stages 3 + 4 sleep. CONCLUSION: Therapy-induced amelioration of OSA and sleep quality was accompanied by decrease in the amplitudes of VLF components of HRV. The VLF component may thus reflect physiological changes in both autonomic activity and sleep structure and serve as an objective marker for therapeutic efficacy in patients with severe OSA.

Prognostic Importance of Novel Oxygen Desaturation Metrics in Patients With Heart Failure and Central Sleep Apnea.

BACKGROUND: Sleep-disordered breathing, particularly central sleep apnea (CSA), is highly prevalent in heart failure (HF) and an independent prognostic marker. We assessed the hypothesis that an increased hypoxemic burden during sleep may have greater prognostic value than the frequency of apneic and hypopneic episodes. METHODS AND RESULTS: We prospectively conducted overnight cardiorespiratory polygraphy on consecutive HF patients referred to our hospital from 2008 to 2011. We studied CSA defined by an apnea-hypopnea index (AHI) of ≥5 events/h with >75% of all events being central in origin. We determined the AHI, proportion of the sleep time with SpO2 <90% (T90%), and proportion of the recording time that 4% desaturation events occurred (4%POD). We studied 112 HF patients with either systolic or diastolic dysfunction. During a follow-up period of 37 ± 25 months, 32 patients (29%) died. Nonsurvivors had a higher 4%POD compared with survivors (11 ± 6.4% vs 19 ± 13%; P = .001), but did not differ significantly from survivors regarding AHI and T90%. An adjusted logistic regression analysis revealed that the 4%POD was the best independent predictor of mortality. CONCLUSIONS: The 4%POD, a novel metric for the nocturnal hypoxemic burden, is an independent prognostic marker in HF patients affected by CSA.

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients.

AIMS: Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. METHODS AND RESULTS: CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2-3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4-2.2], P < 0.001), ESRD (1.5 [1.3-1.8], P < 0.001), and CHF (1.4 [1.1-1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, ß-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. CONCLUSION: Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients.

Examining the Crux of Autonomic Dysfunction in Posttraumatic Stress Disorder: Whether Chronic or Situational Distress Underlies Elevated Heart Rate and Attenuated Heart Rate Variability.

OBJECTIVE: Posttraumatic stress disorder (PTSD) has been linked to elevated heart rate (HR) and reduced heart rate variability (HRV) in cross-sectional research. Using ecological momentary assessment and minute-to-minute HRV/HR monitoring, we examined whether cross-sectional associations between PTSD symptom severity and HRV/HR were due to overall elevations in distress levels or to attenuated autonomic regulation during episodes of acute distress. METHODS: Two hundred nineteen young adults (18-39 years old), 99 with PTSD, underwent 1 day of Holter monitoring and concurrently reported distress levels via ecological momentary assessment. Using multilevel modeling, we examined the associations between momentary distress and the 5-minute means for low-frequency (LF) and high-frequency (HF) HRV and HR immediately following distress ratings, and whether PTSD symptom severity moderated these associations. RESULTS: Compared with the controls, participants with PTSD recorded higher ambulatory distress (mean [standard deviation] = 1.7 [0.5] versus 1.2 [0.3], p < .001) and HR (87.2 [11.8] versus 82.9 [12.6] beats/min, p = .011), and lower ambulatory LF HRV (36.9 [14.7] versus 43.7 [16.9 ms, p = .002) and HF HRV (22.6 [12.3] versus 26.4 [14.6] milliseconds, p = .043). Overall distress level was not predictive of HR or HRV (p values > .27). However, baseline PTSD symptom severity was associated with elevated HR (t(1257) = 2.76, p = .006) and attenuated LF (t(1257) = -3.86, p < .001) and HF (t(1257) = -2.62, p = .009) in response to acute momentary distress. CONCLUSIONS: Results suggest that PTSD is associated with heightened arousal after situational distress and could explain prior findings associating PTSD with HR/HRV. Implications for treatment and cardiovascular risk are discussed.

Beat-to-beat T-wave amplitude variability in the risk stratification of right ventricular outflow tract-premature ventricular complex patients.

AIMS: Premature ventricular complexes (PVCs) originating from the right ventricular outflow tract (RVOT) may occasionally trigger monomorphic ventricular tachycardia (MVT), polymorphic ventricular tachycardia (PVT), or ventricular fibrillation (VF). We examined whether an analysis of the ventricular repolarization instability could differentiate PVT/VF triggered by RVOT-PVCs from benign RVOT-PVCs or MVT. METHODS: We evaluated the ventricular repolarization instability as assessed by the beat-to-beat T-wave amplitude variability (TAV) using Holter recordings in patients with RVOT-PVCs but with no structural heart disease. We determined the prematurity index, defined as the ratio of the coupling interval of the first ventricular tachycardia (VT) beat or isolated PVC to the preceding R-R interval just before the VT or isolated PVC in the Holter recordings. The study patients were classified into RVOT-PVCs/MVT (n = 33) and PVT/VF (n = 10). RESULTS: The two groups did not differ with respect to the age, sex, and left ventricular ejection fraction. There was no significant difference in the prematurity index between the two groups (RVOT-PVCs/MVT 0.66 ± 0.16 vs. PVT/VF 0.61 ± 0.13, P = 0.60). The patients with PVT/VF had a significantly larger maximum TAV than those with RVOT-PVCs/MVT (31 ± 13 vs. 68 ± 40 µV, P < 0.001). Patients with a higher than median value of the TAV (33 µV) were at increased risk of PVT/VF vs. those with a lower than median value, after adjusting for the age and sex [9.25 (95% confidence interval: 1.27-19.2); P = 0.03]. CONCLUSIONS: The TAV analysis is a useful measure to identify the subset of usually benign RVOT-PVC/MVT patients prone to PVT/VF.

Circadian Contrasts in Heart Rate Variability Associated With Posttraumatic Stress Disorder Symptoms in a Young Adult Cohort.

Prior research has demonstrated that individuals exposed to trauma have shown impaired autonomic function. We sought to determine if heart rate variability (HRV), a marker of impaired autonomic function, differed across periods of wake, rest, and sleep as a function of the level of symptoms of posttraumatic stress disorder (PTSD). A sample of young adults (N = 209), 95 of whom met full criteria for current PTSD based on the Clinician Administered PTSD Scale (CAPS; Blake et al., 1995), were evaluated for ≈ 24 hr using actigraphy and electrocardiogram. Actigraphy data were categorized as active, rest, or sleep. Multilevel modeling analyses showed that individuals with high PTSD symptom severity had lower high-frequency HRV than individuals with low PTSD symptom severity during periods of sleep, t(1083) = 2.20, p = .028, Cohen's d = 0.12. No differences were found during periods of activity, t(1083) = 1.34, p = .499, d = 0.05, or rest, t(1083) = 1.34, p = .180, d = 0.09. Our findings extended the import of prior studies to suggest that those with elevated PTSD symptoms may have decreased parasympathetic control during sleep. Moreover, relative to periods of wake and rest, sleep may represent a state of increased vulnerability for decreased parasympathetic cardiac control. Individuals with elevated PTSD symptoms may benefit from early screening for detection of cardiovascular disease.

Autonomic nervous responses in colorectal polypectomy: Randomized controlled trial comparing air and carbon dioxide insufflation.

BACKGROUND AND AIM: Carbon dioxide (CO2) insufflation devices are commonly used for endoscopic examination and treatment. In this prospective randomized controlled trial (RCT), we compared patient acceptance, cardiovascular tolerance,and autonomic nervous responses between patients receiving air insufflation and CO2 insufflation. METHODS: We initially enrolled 170 patients and, of these, 158 patients in total were analyzed (air group, 83; CO2 group, 75). Autonomic nervous responses were evaluated by analysis of heart rate variability (HRV). Primary end point was superiority in the effects of CO2 insufflation on the autonomic nervous system by HRV analysis. RESULTS: Visual analog scale disclosed significantly less abdominal pain and abdominal fullness with CO2. Percentage heart rate change rate at 1 h and 4 h after the procedure was also significantly lower in the CO2 group than in the air group (1 h after: P < 0.01, 4 h after: P < 0.05). Comparison based on age showed that % heart rate change was significantly lower in the younger CO2 patients (just after colonoscopy and 1 h after: P < 0.01, 4 h after: P < 0.05), but this difference was not apparent in an older group of patients. CONCLUSIONS: This is the first RCT showing that colorectal polypectomy using CO2 insufflation significantly decreases abdominal pain and abdominal fullness common in such patients with lowered stress to the autonomous nervous system. The effects using CO2 insufflation on the sympathetic nervous system also seemed to be more prominent among younger patients.

Nocturnal patterns of heart rate and the risk of mortality after acute myocardial infarction.

BACKGROUND: The purposes of this study were to identify nocturnal patterns of heart rate (HR) in depressed and nondepressed patients after an acute myocardial infarction (MI) and to determine which patterns, if any, are associated with all-cause mortality or recurrent infarction. METHODS: Functional data analysis and model-based clustering methods were used to identify nocturnal HR patterns in 245 depressed and 247 nondepressed patients with a recent MI. All-cause mortality and recurrent infarctions were ascertained over a median follow-up of 24 months. RESULTS: Three HR activity patterns were identified. In the first, HR gradually declined during the nighttime and increased the next morning. The second pattern was similar, but with a higher overall HR during the recording interval. The third showed almost no decrease in HR at night (ie, "nondipping"). All-cause mortality was higher among patients with pattern 3 than pattern 1 (P = .007), and the combined end point of recurrent MI or all-cause mortality was higher in pattern 3 than pattern 2 (P = .05). Patterns 2 and 3 were more common in the depressed than in the nondepressed patients. CONCLUSIONS: The nondipping nocturnal HR independently predicts all-cause mortality and recurrent MI. Future studies should examine the underlying causes of nondipping nocturnal HR and its association with depression and investigate the effects of treatment on survival.

Blood Pressure Regulation and Hypertension in Obstructive Sleep Apnea Syndrome: A Historical Perspective.

In obstructive sleep apnea syndrome (OSAS), an underlying disease of secondary hypertension, repeated episodes of asphyxia due to obstructive sleep apnea (OSA), followed by arousal, lead to various cardiovascular consequences. Using a canine model of OSAS, it was found that a single load of OSA caused an abrupt increase in blood pressure (BP) (Apnea Surge in seconds), while multiple OSA episodes occurring nightly for 1-3 months led to a sustained elevation of BP during both nighttime and daytime. Epidemiological studies on 24-hour ambulatory BP measurements revealed that some hypertensive patients experienced elevated BP in the early morning (Morning Surge), which could be intensified by OSAS. The resonance of Apnea Surge in seconds and Morning Surge increases the risk of organ damage, triggers the cardiovascular events, and adversely affects the prognosis of hypertensive patients with OSAS.For ameliorating these risks, OSA should be treated with positive airway pressure properly.

Quantitative detection of sleep apnea in adults using inertial measurement unit embedded in wristwatch wearable devices.

Sleep apnea (SA) is associated with risk of cardiovascular disease, cognitive decline, and accidents due to sleepiness, yet the majority (over 80%) of patients remain undiagnosed. Inertial measurement units (IMUs) are built into modern wearable devices and are capable of long-term continuous measurement with low power consumption. We examined if SA can be detected by an IMU embedded in a wristwatch device. In 122 adults who underwent polysomnography (PSG) examinations, triaxial acceleration and triaxial gyro signals from the IMU were recorded during the PSG. Subjects were divided into a training group and a test groups (both n = 61). In the training group, an algorithm was developed to extract signals in the respiratory frequency band (0.13-0.70 Hz) and detect respiratory events as transient (10-90 s) decreases in amplitude. The respiratory event frequency estimated by the algorithm correlated with the apnea-hypopnea index (AHI) of the PSG with r = 0.84 in the test group. With the cutoff values determined in the training group, moderate-to-severe SA (AHI ≥ 15) was identified with 85% accuracy and severe SA (AHI ≥ 30) with 89% accuracy in the test group. SA can be quantitatively detected by the IMU embedded in wristwatch wearable devices in adults with suspected SA.

Multi-scale heart rate dynamics detected by phase-rectified signal averaging predicts mortality after acute myocardial infarction.

AIMS: Acceleration and deceleration capacity (AC and DC) for beat-to-beat short-term heart rate dynamics are powerful predictors of mortality after acute myocardial infarction (AMI). We examined if AC and DC for minute-order long-term heart rate dynamics also have independent predictive value. METHODS AND RESULTS: We studied 24-hr Holter electrcardiograms in 708 post-AMI patients who were followed up for up to 30 months thereafter. Acceleration capacity and DC was calculated with the time scales of T (window size defining heart rate) and s (wavelet scale) from 1 to 500 s and compared their prognostic values with conventional measures (AC(conv) and DC(conv)) that were calculated with (T,s) = [1,2 (beat)]. During the follow-up, 47 patients died. Both increased AC(conv) and decreased DC(conv) predicted mortality (C statistic, 0.792 and 0.797). Concordantly, sharp peaks of C statistics were observed at (T,s) = [2,7 (sec)] for both increased AC and decreased DC (0.762 and 0.768), but there were larger peaks of C statistics at around [30,60 (sec)] for both (0.783 and 0.796). The C statistic was greater for DC than AC at (30,60) (P = 0.0012). Deceleration capacity at (30,60) was a significant predictor even after adjusted for AC(conv) (P = 0.020) and DC(conv) (P = 0.028), but the predictive power of AC at (30,60) was no longer significant. CONCLUSION: A decrease in DC for minute-order long-term heart rate dynamics is a strong predictor for post-AMI mortality and the predictive power is independent of AC(conv) and DC(conv) for beat-to-beat short-term heart rate dynamics.

Accuracy of ECG-based screening for sleep-disordered breathing: a survey of all male workers in a transport company.

PURPOSE: Sleep-disordered breathing (SDB) is associated with increased risk for cardiovascular morbidity and mortality and for sleepiness-related accidents, but >75 % of the patients remain undiagnosed. We sought to determine the diagnostic accuracy of ECG-based detection of SDB when used for population-based screening. METHODS: All male workers, mostly truck drivers, of a transport company (n = 165; age, 43 ± 12 years) underwent standard attended overnight polysomnography. Cyclic variation of heart rate (CVHR), a characteristic pattern of heart rate associated with SDB, was detected from single-lead ECG signals during the polysomnography by a newly developed automated algorithm of autocorrelated wave detection with adaptive threshold (ACAT). RESULTS: Among 165 subjects, the apnea-hypopnea index (AHI) was ≥5 in 62 (38 %), ≥15 in 26 (16 %), and ≥30 in 16 (10 %). The number of CVHR per hour (CVHR index) closely correlated with AHI [r = 0.868 (95 % CI, 0.825-0.901)]. The areas under the receiver operating characteristic curves for detecting subjects with AHI ≥5, ≥15, and ≥30 were 0.796 (95 % CI, 0.727-0.855), 0.974 (0.937-0.993), and 0.997 (0.971-0.999), respectively. With a predetermined criterion of CVHR index ≥15, subjects with AHI ≥15 were identified with 88 % sensitivity and 97 % specificity (likelihood ratios for positive and negative test, 30.7 and 0.12). The classification performance was retained in subgroups of subjects with obesity, hypertension, diabetes mellitus, dyslipidemia, and decreased autonomic function. CONCLUSIONS: The CVHR obtained by the ACAT algorithm may provide a useful marker for screening for moderate-to-severe SDB among apparently healthy male workers.

Heart rate variability biofeedback improves cardiorespiratory resting function during sleep.

The present study was designed to examine the effect of heart rate variability (HRV) biofeedback on the cardiorespiratory resting function during sleep in daily life. Forty-five healthy young adults were randomly assigned to one of three groups: HRV biofeedback, Autogenic Training(AT), and no-treatment control. Participants in the HRV biofeedback were instructed to use a handheld HRV biofeedback device before their habitual bedtime, those in the AT were asked to listen to an audiotaped instruction before bedtime,and those in the control were asked to engage in their habitual activity before bedtime. Pulse wave signal during sleep at their own residences was measured continuously with a wrist watch-type transdermal photoelectric sensor for three time points. Baseline data were collected on the first night of measurements, followed by two successive nights for HRV biofeedback, AT, or control. Cardiorespiratory resting function was assessed quantitatively as the amplitude of high frequency(HF) component of pulse rate variability, a surrogate measure of respiratory sinus arrhythmia. HF component increased during sleep in the HRV biofeedback group,although it remained unchanged in the AT and control groups. These results suggest that HRV biofeedback before sleep may improve cardiorespiratory resting function during sleep.