Detection of cardiovascular risk from a photoplethysmographic signal using a matching pursuit algorithm

Comparison of pulse rate variability from post-auricula and heart rate variability during different body states for healthy subjects

Heart rate variability (HRV) extracted from the electrocardiogram (ECG) is an essential indicator for assessing the autonomic nervous system in clinical. Some scholars have studied the feasibility of pulse rate variability (PRV) instead of HRV. However, there is little qualitative research in different body states. In this paper, the photoplethysmography (PPG) of postauricular and finger and the ECG of fifteen subjects were synchronously collected for comparative analysis. The eleven experiments were designed according to the daily living state, including the stationary state, limb movement state, and facial movement state. The substitutability of nine variables was investigated in the time, frequency, and nonlinearity domain by Passing Bablok regression and Bland Altman analysis. The results showed that the PPG of the finger was destroyed in the limb movement state. There were six variables of postauricular PRV, which showed a positive linear relationship and good agreement (p > 0.05, ratio ≤0.2) with HRV in all experiments. Our study suggests that the postauricular PPG could retain the necessary information of the pulse signal under the limb movement state and facial movement state. Therefore, postauricular PPG could be a better substitute for HRV, daily PPG detection, and mobile health than finger PPG.

Cluster analysis of clinical phenotypic heterogeneity in obstructive sleep apnea assessed using photoplethysmography

BACKGROUND

We evaluated heterogeneity in clinical phenotypes among patients with obstructive sleep apnea syndrome (OSAHS) using photoplethysmography (PPG) in cluster analysis.

METHODS

All enrolled patients underwent polysomnography (PSG) monitoring while wearing a PPG device. Pulse wave signals were recorded with a modified pulse oximetry probe in the PPG device. The pulse wave-derived cardiac risk composite parameter (CRI) and eight derived signal parameters were used to assess OSAHS phenotype. We defined a high cardiovascular risk OSAHS group (CRI ≥0.5) and low cardiovascular risk OSAHS group (CRI <0.5). K-means clustering was performed for analysis of clinical phenotype heterogeneity in OSAHS by combining the CRI and its derived signals.

RESULTS

The OSAHS group had high cardiovascular risk for sex, age, body mass index, systolic and diastolic blood pressure, apnea hypopnea index, and obstructive arousal index and higher risk of developing hypertension, diabetes, and cerebrovascular comorbidities. The low cardiovascular risk OSAHS group had higher blood oxygen levels. Three clinical phenotypes were identified in CRI clustering: 1) typical OSAHS with high risk of hypertension (characterized by middle age, obesity, hypertension with severe OSAHS); 2) older women and mild OSAHS; 3) older men and mild OSAHS. Three subtypes were obtained based on the eight cardiac risk-derived parameters: 1) hypoxia combined with decreased pulse wave amplitude variation; 2) decreased vascular pulse wave amplitude combined with decreased pulse frequency; 3) arrhythmia combined with hypoxia.

CONCLUSIONS

Establishing OSAHS clinical phenotypes with the CRI and derived parameters using PPG may help in establishing multi-dimensional assessment of cardiovascular risk in OSAHS.

Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review

STUDY OBJECTIVES

Polysomnograms (PSGs) collect a plethora of physiologic signals across the night. However, few of these PSG data are incorporated into standard reports, and hence, ultimately, under-utilized in clinical decision making. Recently, there has been substantial interest regarding novel alternative PSG metrics that may help to predict obstructive sleep apnea (OSA)-related outcomes better than standard PSG metrics such as the apnea-hypopnea index. We systematically review the recent literature for studies that examined the use of alternative PSG metrics in the context of OSA and their association with health outcomes.

METHODS

We systematically searched EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews for studies published between 2000 and 2022 for those that reported alternative metrics derived from PSG in adults and related them to OSA-related outcomes.

RESULTS

Of the 186 initial studies identified by the original search, data from 31 studies were ultimately included in the final analysis. Numerous metrics were identified that were significantly related to a broad range of outcomes. We categorized the outcomes into 2 main subgroups: (1) cardiovascular/metabolic outcomes and mortality and (2) cognitive function- and vigilance-related outcomes. Four general categories of alternative metrics were identified based on signals analyzed: autonomic/hemodynamic metrics, electroencephalographic metrics, oximetric metrics, and respiratory event-related metrics.

CONCLUSIONS

We have summarized the current landscape of literature for alternative PSG metrics relating to risk prediction in OSA. Although promising, further prospective observational studies are needed to verify findings from other cohorts, and to assess the clinical utility of these metrics.

CITATION

Hajipour M, Baumann B, Azarbarzin A, et al. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med. 2023;19(2):225-242.

Home Sleep Testing of Sleep Apnea

Measurement methods with graded complexity for use in the lab as well as for home sleep testing (HST) are available for the diagnosis of sleep apnea, and there are different classification systems in existence. Simplified HST measurements, which record fewer parameters than traditional four- to six-channel devices, can indicate sleep apnea and can be used as screening tool in high-prevalence patient groups. Peripheral arterial tonometry (PAT) is a technique which can be suitable for the diagnosis of sleep apnea in certain cases. Different measurement methods are used, which has an influence on the significance of the results. New minimal-contact and non-contact technologies of recording and analysis of surrogate parameters are under development. If they are validated by clinical studies, it will be possible to detect sleep apnea in need of treatment more effectively. In addition, this could become a solution to monitor the effectiveness of such treatment.

New Trends and New Technologies in Sleep Medicine: Expanding Accessibility

New trends in sleep medicine make use of the increased computational power of digital transformation. A current trend toward fewer sensors on the body of the sleeper and to more data processing from derived signals is observed. Telemedicine technologies are used for data transmission and for better patient management in terms of diagnosis and in terms of treatment of chronic conditions.

Beyond the AHI-pulse wave analysis during sleep for recognition of cardiovascular risk in sleep apnea patients

Recent evidence supports the use of pulse wave analysis during sleep for assessing functional aspects of the cardiovascular system. The current study compared the influence of pulse wave and sleep study-derived parameters on cardiovascular risk assessment. In a multi-centric study design, 358 sleep apnea patients (age 55 ± 13 years, 64% male, body mass index 30 ± 6 kg m^-2 , apnea-hypopnea index 13 [5-26] events per hr) underwent a standard overnight sleep recording. A novel cardiac risk index was computed based on pulse wave signals derived from pulse oximetry, reflecting vascular stiffness, cardiac variability, vascular autonomic tone and nocturnal hypoxia. Cardiovascular risk was determined using the ESC/ESH cardiovascular risk matrix, and categorized to high/low added cardiovascular risk. Comparisons between cardiac risk index and sleep parameters were performed for cardiovascular risk prediction. Apnea-hypopnea index, oxygen desaturation index and cardiac risk index were associated with high cardiovascular risk after adjustment for confounders (p = .002, .001, < .001, respectively). In a nested reference model consisting of age, gender and body mass index, adding cardiac risk index but not apnea-hypopnea index or oxygen desaturation index significantly increased the area under the receiver operating characteristic curve (p = .012, .22 and .16, respectively). In a direct comparison of oxygen desaturation index and cardiac risk index, only the novel risk index had an independent effect on cardiovascular risk prediction (p_CRI  < .001, p_ODI  = .71). These results emphasize the association between nocturnal pulse wave and overall cardiovascular risk determined by an established risk matrix. Thus, pulse wave analysis during sleep provides a powerful approach for cardiovascular risk assessment in addition to conventional sleep study parameters.

Pulse wave amplitude drops during sleep: clinical significance and characteristics in a general population sample

Study Objectives

To explore the clinical significance of pulse wave amplitude (PWA)-drops during sleep as a biomarker for cardiometabolic disorders and describe their main characteristics in a general population sample.

Methods

Cross-sectional study of HypnoLaus cohort, in which 2162 individuals underwent clinical assessment and in-home full polysomnography. PWA-drops were derived from photoplethysmography and processed using a validated automated algorithm. Associations between PWA-drop features (index, mean duration, and mean area under the curve [AUC]) with hypertension, diabetes, and previous cardiovascular (CV) event were analyzed using multivariable-adjusted logistic regression.

Results

Two thousand one hundred forty-nine participants (59 ± 11 years, 51% women, 9.9% diabetes, 41.3% hypertension, 4.4% CV event) were included. Mean ± standard deviation (SD) of PWA-drop index, duration, and AUC during sleep were 51.0 ± 20.3 events/hour, 14.0 ± 2.7 seconds, and 527±115 %seconds, respectively. PWA-drop index was lower in women and decreased with age, while its mean duration and AUC increased in men and elderly. Overall, lower PWA-drop index, longer duration and greater AUC were associated with increased odds of hypertension, diabetes, or CV event after adjustment for confounders. Participants in the lowest quartile of mean duration-normalized PWA-drop index had a significantly higher odds ratio (OR) of hypertension (OR = 1.60 [1.19–2.16]), CV event (OR = 3.26 [1.33–8.03]), and diabetes (OR = 1.71 [1.06–2.76]) compared to those in the highest quartile. Similar results were observed for mean AUC-normalized PWA-drop index regarding hypertension (OR = 1.59 [1.19–2.13]), CV event (OR = 2.45 [1.14–5.26]) and diabetes (OR = 1.76 [1.10–2.83]).

Conclusions

PWA-drop features during sleep seem to be an interesting biomarker independently associated with cardiometabolic outcomes in the general population.

The novel three-dimensional pulse images analyzed by dynamic L-cube polynomial model

A dynamic L-cube polynomial is proposed to analyze dynamic three-dimensional pulse images (d3DPIs), as an extension of the previous static L-cube polynomial. In this paper, a weighted least squares (WLS) method is proposed to fit the amplitude C(t) of d3DPI at four physiological key points in addition to the best fit of L-cube polynomials to the measured normal and cold-pressor-test (CPT)-induced taut 3DPIs. Compared with other two fitting functions, C(t) of a dynamic L-cube polynomial can be well matched by the proposed WLS method with the least relative error at four physiological key points in one beat with statistical significance, in addition to the best fit of the measured 3DPIs. Therefore, a dynamic L-cube polynomial can reflect dynamic time characteristics of normal and CPT-induced hypertensive taut 3DPIs, which can be used as an evidence of hypertension diagnosis.

External temperature sensor assisted a new low power photoplethysmography readout system for accurate measurement of the bio-signs

This study presents an external temperature sensor assisted a new low power, time-interleave, wide dynamic range, and low DC drift photoplethysmography (PPG) signal acquisition system to obtain the accurate measurement of various bio signs in real-time. The designed chip incorporates a 2-bit control programmable transimpedance amplifier (TIA), a high order filter, a 3:8 programmable gain amplifier (PGA) and 2 × 2 organic light-emitting diode (OLED) driver. Temperature sensor is used herein to compensate the adverse effect of low-skin-temperature on the PPG signal quality. The analog front-end circuit is implemented in the integrated chip with chip area of 2008 μm × 1377 μm and fabricated via TSMC T18 process. With the standard 1.8 V, the experimental result shows that the measured current sensing range is 20 nA-100 uA. The measured dynamic range of the designed readout circuit is 80 dB. The estimated signal to noise ratio is 60 dB@1 uA, and the measured input referred noise is 60.2 pA/Hz^½. The total power consumption of the designed chip is 31.32 µW (readout) + 1.62 mW (OLED driver@100% duty cycle). The non-invasive PPG sensor is applied to the wrist artery of the 40 healthy subjects for sensing the pulsation of the blood vessel. The experimental results show that for every 1 °C decrease in mean ambient temperature tends to 0.06 beats/min, 0.125 mmHg and 0.063 mmHg increase in hear rate (HR), systolic (SBP) and diastolic (DBP), respectively. Similarly, for every 1 °C increase in mean ambient temperature tends to 0.13 beats/min, 0.601 mmHg and 0.121 mmHg increase in HR, SBP and DBP, respectively. The measured accuracy and standard error for the HR estimation are 96%, and - 0.022 ± 2.589 beats/minute, respectively. The oxygen stauration (S_pO₂) measurement results shows that the mean absolute percentage error is less than 5%. The resultant errors for the SBP and DBP measurement are - 0.318 ± 5.19 mmHg and - 0.5 ± 1.91 mmHg, respectively.

Overnight pulse wave analysis to assess autonomic changes during sleep in insomnia patients and healthy sleepers

Insomnia has been associated with increased cardiovascular (CV) risk, which may be linked to sympathetic activation. Non-invasive overnight pulse wave analysis may be a useful tool to detect early signs of autonomic changes during sleep in insomniacs. Fifty-two participants (26 men, 37±13 years, BMI: 24±5 kg/m², 26 insomniacs/ 26 controls) underwent overnight polysomnography with pulse oximetry and pulse wave analysis including pulse rate, vascular stiffness (pulse propagation time, PPT), and a composite cardiac risk index based on autonomic function and overnight hypoxia. We identified two subgroups of insomniacs, with and without objectively disturbed sleep (sleep efficiency SE≤80%, n = 14 vs. SE>80%, n = 12), and observed increased pulse rate and vascular stiffness in insomnia cases when diagnosis was based on both, subjective and objective criteria. Both insomnia groups were associated with higher overnight pulse rate than controls (median/ IQR: low-SE (low sleep efficiency): 67/ 58-70bpm; high-SE: 66/ 63-69bpm; controls: 58/ 52-63bpm; p = 0.01). Vascular stiffness was higher (reduction of PPT) in low-SE insomniacs compared with high-SE insomniacs and controls (169/ 147-232ms; 237/ 215-254ms; 244/ 180-284ms; p = 0.01). The cardiac risk index was increased in low-SE insomniacs (0.2/ 0.0–0.7; 0.0/ 0.0–0.4; 0.0/ 0.0–0.3; p = 0.05). Our results suggest a hyperarousal state in young and otherwise healthy insomniacs during sleep. The increased pulse rate and vascular stiffness in insomniacs with low SE suggest early signs of rigid vessels and potentially, an elevated CV risk. Overnight pulse wave analysis may be feasible for CV risk assessment in insomniacs and may provide a useful tool for phenotyping insomnia in order to provide individualized therapy.

Continuous non-invasive determination of nocturnal blood pressure variation using photoplethysmographic pulse wave signals: comparison of pulse propagation time, pulse transit time and RR-interval

OBJECTIVE

Cardiovascular diseases are the leading cause of death, whereas nocturnal ambulatory blood pressure (BP) is the most potent predictor for cardiovascular risk. The volume clamp and pulse transit time (PTT) are common methods for continuous non-invasive BP measurement, but have drawbacks during unsupervised ambulatory use and undisturbed sleep. The pulse propagation time (PPT), defined as the time between pulse wave systolic peak and diastolic peak, provides valid information about the pressure pulse waveform. However, the use of PPT for nocturnal BP variation determination and whether such variation is affected by BP or heart rate (i.e. RR-interval or RRI) has not been investigated.

APPROACH

To assess whether the PPT method is suitable for ubiquitous nocturnal BP monitoring, we compared systolic blood pressure (SBP) estimates derived from PPT, PTT, and RRI signals with parallel recorded BP measurements. The RRI-derived SBP signals were used as a baseline for testing a potential heart rate dependency. This work provides an overview of BP measurements, presents the developed real-time signal analysis, and describes the performance assessment. The signal analysis was validated with data records from 42 subjects acquired from an ergometry and sleep laboratory in equal parts.

MAIN RESULTS

The algorithms applied to the ergometry laboratory database achieved a correlation coefficient between reference SBP and estimated SBP_PPT of 0.89 (p  <  0.001) with bias 0.1 mmHg and limits of agreement (LoA)  -29.8 to 30.0 mmHg, SBP_PTT of 0.97 (p  <  0.001) with bias 0.0 mmHg and LoA  -15.2 to 15.3 mmHg, and SBP_RRI of 0.96 (p  <  0.001) with bias 0.0 mmHg and LoA  -19.5 to 19.5 mmHg. For the sleep laboratory database, the correlation coefficient was 0.95 (p  <  0.001) with bias 0.2 mmHg and LoA  -18.3 to 18.8 mmHg for SBP_PPT, 0.88 (p  <  0.001) with bias 0.0 mmHg and LoA  -25.0 to 24.9 mmHg for SBP_PTT, and 0.88 (p  <  0.001) with bias of 0.1 mmHg and LoA  -23.6 to 23.7 mmHg for SBP_RRI. A heart rate dependency of PPT or PTT could not be found. The analysis of variance shows no significant differences between the reference SBP values and the estimated values for either the ergometry (F(3, 627)  =  2.27, p  =  0.08) or the sleep laboratory (F(3, 327)  =  2.28, p  =  0.08).

SIGNIFICANCE

In conclusion, the PPT method seems to be an interesting alternative for continuous determination of SBP during simplified cardiovascular monitoring and sleep screening compared to more expensive devices based on volume clamp or PTT methods.

Nasal high flow, but not supplemental O2, reduces peripheral vascular sympathetic activity during sleep in COPD patients

Introduction

Patients with COPD have increased respiratory loads and altered blood gases, both of which affect vascular function and sympathetic activity. Sleep, particularly rapid eye movement (REM) sleep, is known to exacerbate hypoxia and respiratory loads. Therefore, we hypothesize that nasal high flow (NHF), which lowers ventilatory loads, reduces sympathetic activity during sleep and that this effect depends on COPD severity.

Methods

We performed full polysomnography in COPD patients (n=17; FEV₁, 1.6±0.6 L) and in matched controls (n=8). Participants received room air (RA) at baseline and single night treatment with O₂ (2 L/min) and NHF (20 L/min) in a random order. Finger pulse wave amplitude (PWA), a measure of vascular sympathetic tone, was assessed by photoplethysmography. Autonomic activation (AA) events were defined as PWA attenuation ≥30% and indexed per hour for sleep stages (AA index [AAI]) at RA, NHF, and O₂).

Results

In COPD, sleep apnea improved following O₂ (REM-apnea hypopnea index [AHI] with RA, O₂, and NHF: 18.6±20.9, 12.7±18.1, and 14.4±19.8, respectively; P=0.04 for O₂ and P=0.06 for NHF). REM-AAI was reduced only following NHF in COPD patients (AAI-RA, 21.5±18.4 n/h and AAI-NHF, 9.9±6.8 n/h, P=0.02) without changes following O₂ (NHF-O₂ difference, P=0.01). REM-AAI reduction was associated with lung function expressed as FEV₁ and FVC (FEV₁: r=−0.59, P=0.001; FEV₁/FVC: r=−0.52 and P=0.007).

Conclusion

NHF but not elevated oxygenation reduces peripheral vascular sympathetic activity in COPD patients during REM sleep. Sympathetic off-loading by NHF, possibly related to improved breathing mechanics, showed a strong association with COPD severity.

Advances in Photopletysmography Signal Analysis for Biomedical Applications

Heart Rate Variability (HRV) is an important tool for the analysis of a patient’s physiological conditions, as well a method aiding the diagnosis of cardiopathies. Photoplethysmography (PPG) is an optical technique applied in the monitoring of the HRV and its adoption has been growing significantly, compared to the most commonly used method in medicine, Electrocardiography (ECG). In this survey, definitions of these technique are presented, the different types of sensors used are explained, and the methods for the study and analysis of the PPG signal (linear and nonlinear methods) are described. Moreover, the progress, and the clinical and practical applicability of the PPG technique in the diagnosis of cardiovascular diseases are evaluated. In addition, the latest technologies utilized in the development of new tools for medical diagnosis are presented, such as Internet of Things, Internet of Health Things, genetic algorithms, artificial intelligence and biosensors which result in personalized advances in e-health and health care. After the study of these technologies, it can be noted that PPG associated with them is an important tool for the diagnosis of some diseases, due to its simplicity, its cost⁻benefit ratio, the easiness of signals acquisition, and especially because it is a non-invasive technique.

REM Sleep Imposes a Vascular Load in COPD Patients Independent of Sleep Apnea

Arterial stiffness, a marker for cardiovascular risk, is increased in patients with Chronic Obstructive Pulmonary Disease (COPD) and Obstructive Sleep Apnea (OSA). The specific influence of both on arterial stiffness during sleep is unknown. Nocturnal arterial stiffness (Pulse Propagation Time (PPT) of the finger pulse wave) was calculated in 142 individuals evaluated for sleep apnea: 27 COPD patients (64.7 ± 11y, 31.2 ± 8 kg/m²), 72 patients with cardiovascular disease (CVD group, 58.7 ± 13y, 33.6 ± 6 kg/m²) and 43 healthy controls (HC group 49.3 ± 12y, 27.6 ± 3 kg/m²). Sleep stage related PPT changes were assessed in a subsample of COPD patients and matched controls (n = 12/12). Arterial stiffness during sleep was increased in COPD patients (i.e. shortened PPT) compared to healthy controls (158.2 ± 31 vs. 173.2 ± 38 ms, p = 0.075) and to patients with CVD (161.4 ± 41 ms). Arterial stiffening was particular strong during REM sleep (145.9 ± 28 vs. 172.4 ± 43 ms, COPD vs. HC, p = 0.003). In COPD, time SaO₂ < 90% was associated with reduced arterial stiffness (Beta +1.7 ms (1.1-2.3)/10 min, p < 0.001). Sleep apnea did not affect PPT. In COPD, but not in matched controls, arterial stiffness increased from wakefulness to REM-sleep (ΔPPT-8.9 ± 10% in COPD and 3.7 ± 12% in matched controls, p = 0.021). Moreover, REM-sleep related arterial stiffening was correlated with elevated daytime blood pressure (r = -0.92, p < 0.001) and increased myocardial oxygen consumption (r = -0.88, p < 0.01). Hypoxia and REM sleep modulate arterial stiffness. In contrast to healthy controls, REM sleep imposes a vascular load in COPD patients independent of sleep apnea indices, intermittent and sustained hypoxia. The link between REM-sleep, vascular stiffness and daytime cardiovascular function suggests that REM-sleep plays a role for increased cardiovascular morbidity of COPD patients.