Facial Video-based Remote Physiological Measurement via Self-supervised Learning

Facial video-based remote physiological measurement aims to estimate remote photoplethysmography (rPPG) signals from human face videos and then measure multiple vital signs (e.g. heart rate, respiration frequency) from rPPG signals. Recent approaches achieve it by training deep neural networks, which normally require abundant facial videos and synchronously recorded photoplethysmography (PPG) signals for supervision. However, the collection of these annotated corpora is not easy in practice. In this paper, we introduce a novel frequency-inspired self-supervised framework that learns to estimate rPPG signals from facial videos without the need of ground truth PPG signals. Given a video sample, we first augment it into multiple positive/negative samples which contain similar/dissimilar signal frequencies to the original one. Specifically, positive samples are generated using spatial augmentation. Negative samples are generated via a learnable frequency augmentation module, which performs non-linear signal frequency transformation on the input without excessively changing its visual appearance. Next, we introduce a local rPPG expert aggregation module to estimate rPPG signals from augmented samples. It encodes complementary pulsation information from different face regions and aggregate them into one rPPG prediction. Finally, we propose a series of frequency-inspired losses, i.e. frequency contrastive loss, frequency ratio consistency loss, and cross-video frequency agreement loss, for the optimization of estimated rPPG signals from multiple augmented video samples and across temporally neighboring video samples. We conduct rPPG-based heart rate, heart rate variability and respiration frequency estimation on four standard benchmarks. The experimental results demonstrate that our method improves the state of the art by a large margin.Comment: IEEE Transactions on Pattern Analysis and Machine Intelligenc

Tightness of exponential metrics for log-correlated Gaussian fields in arbitrary dimension

We prove the tightness of a natural approximation scheme for an analog of the Liouville quantum gravity metric on $\mathbb R^d$ for arbitrary $d\geq 2$. More precisely, let $\{h_n\}_{n\geq 1}$ be a suitable sequence of Gaussian random functions which approximates a log-correlated Gaussian field on $\mathbb R^d$. Consider the family of random metrics on $\mathbb R^d$ obtained by weighting the lengths of paths by $e^{\xi h_n}$, where $\xi > 0$ is a parameter. We prove that if $\xi$ belongs to the subcritical phase (which is defined by the condition that the distance exponent $Q(\xi)$ is greater than $\sqrt{2d}$), then after appropriate re-scaling, these metrics are tight and that every subsequential limit is a metric on $\mathbb R^d$ which induces the Euclidean topology. We include a substantial list of open problems.Comment: 68 pages, 8 figures; version 2 has updated reference

Enhancing Space-time Video Super-resolution via Spatial-temporal Feature Interaction

The target of space-time video super-resolution (STVSR) is to increase both the frame rate (also referred to as the temporal resolution) and the spatial resolution of a given video. Recent approaches solve STVSR with end-to-end deep neural networks. A popular solution is to first increase the frame rate of the video; then perform feature refinement among different frame features; and last increase the spatial resolutions of these features. The temporal correlation among features of different frames is carefully exploited in this process. The spatial correlation among features of different (spatial) resolutions, despite being also very important, is however not emphasized. In this paper, we propose a spatial-temporal feature interaction network to enhance STVSR by exploiting both spatial and temporal correlations among features of different frames and spatial resolutions. Specifically, the spatial-temporal frame interpolation module is introduced to interpolate low- and high-resolution intermediate frame features simultaneously and interactively. The spatial-temporal local and global refinement modules are respectively deployed afterwards to exploit the spatial-temporal correlation among different features for their refinement. Finally, a novel motion consistency loss is employed to enhance the motion continuity among reconstructed frames. We conduct experiments on three standard benchmarks, Vid4, Vimeo-90K and Adobe240, and the results demonstrate that our method improves the state of the art methods by a considerable margin. Our codes will be available at https://github.com/yuezijie/STINet-Space-time-Video-Super-resolution

Role of cystatin C in urogenital malignancy

Urogenital malignancy accounts for one of the major causes of cancer-related deaths globally. Numerous studies have investigated novel molecular markers in the blood circulation, tumor tissue, or urine in order to assist in the clinical identification of tumors at early stages, predict the response of therapeutic strategies, and give accurate prognosis assessment. As an endogenous inhibitor of lysosomal cysteine proteinases, cystatin C plays an integral role in diverse processes. A substantial number of studies have indicated that it may be such a potential promising biomarker. Therefore, this review was intended to provide a detailed overview of the role of cystatin C in urogenital malignancy

Efficient Secure Multiparty Computation for Multidimensional Arithmetics and Its Application in Privacy-Preserving Biometric Identification

Over years of the development of secure multi-party computation (MPC), many sophisticated functionalities have been made pratical and multi-dimensional operations occur more and more frequently in MPC protocols, especially in protocols involving datasets of vector elements, such as privacy-preserving biometric identification and privacy-preserving machine learning. In this paper, we introduce a new kind of correlation, called tensor triples, which is designed to make multi-dimensional MPC protocols more efficient. We will discuss the generation process, the usage, as well as the applications of tensor triples and show that it can accelerate privacy-preserving biometric identification protocols, such as FingerCode, Eigenfaces and FaceNet, by more than 1000 times

Reverse atrial remodeling in heart failure with recovered ejection fraction

Background Heart failure with recovered ejection fraction (HFrecEF) has been a newly recognized entity since 2020. However, the concept has primarily focused on left ventricular ejection fraction improvement, with less focus on the recovery of the left atrium. In this study, we investigated changes in left atrial (LA) echocardiographic indices in HFrecEF. Methods and Results An inpatient cohort with heart failure with reduced ejection fraction (HFrEF) was identified retrospectively and followed up prospectively in a single tertiary hospital. The enrolled patients were classified into HFrecEF and persistent HFrEF groups. Alternations in LA parameters by echocardiography were calculated. The primary outcome was a composite of cardiovascular death or heart failure rehospitalization. A total of 699 patients were included (HFrecEF: n=228; persistent HFrEF: n=471). Compared with persistent HFrEF, the HFrecEF group had greater reductions in LA diameter, LA transverse diameter, LA superior–inferior diameter, LA volume, and LA volume index but not in LA sphericity index. Cox regression analysis showed that the HFrecEF group experienced lower risks of prespecified end points than the persistent HFrEF group after adjusting for confounders. Additionally, 136 (59.6%) and 62 (13.0%) patients showed LA reverse remodeling (LARR) for the HFrecEF and persistent HFrEF groups, respectively. Among the HFrecEF subgroup, patients with LARR had better prognosis compared with those without LARR. Multivariate logistic analysis demonstrated that age and coronary heart disease were 2 independent negative predictors for LARR. Conclusions In HFrecEF, both left ventricular systolic function and LA structure remodeling were improved. Patients with HFrecEF with LARR had improved clinical outcomes, indicating that the evaluation of LA size provides a useful biomarker for risk stratification of heart failure

Efficacy of guideline-directed medical treatment in heart failure with mildly reduced ejection fraction.

Heart failure with mildly reduced ejection fraction (HFmrEF) has received increasing attention following the publication of the latest ESC guidelines in 2021. However, it remains unclear whether patients with HFmrEF could benefit from guideline-directed medical treatment (GDMT), referring the combination of ACEI/ARB/ARNI, β-blockers, and MRAs, which are recommended for those with reduced ejection fraction. This study explored the efficacy of GDMT in HFmrEF patients. This was a retrospective cohort study of HFmrEF patients admitted to The First Affiliated Hospital of Dalian Medical University between 1 September 2015 and 30 November 2019. Propensity score matching (1:2) between patients receiving triple-drug therapy (TT) and non-triple therapy (NTT) based on age and sex was performed. The primary outcome was all cause death, cardiac death, rehospitalization from any cause, and rehospitalization due to worsening heart failure. Of the 906 patients enrolled in the matched cohort (TT group, n = 302; NTT group, N = 604), 653 (72.08%) were male, and mean age was 61.1 ± 11.92. Survival analysis suggested that TT group experienced a significantly lower incidence of prespecified primary endpoints than NTT group. Multivariable Cox regression showed that TT group had a lower risk of all-cause mortality (HR 0.656, 95% CI 0.447-0.961, P = 0.030), cardiac death (HR 0.599, 95% CI 0.380-0.946, P = 0.028), any-cause rehospitalization (HR 0.687, 95% CI 0.541-0.872, P = 0.002), and heart failure rehospitalization (HR 0.732, 95% CI 0.565-0.948, P = 0.018). In patients with HFmrEF, combined use of neurohormonal antagonists produces remarkable effects in reducing the occurrence of the primary outcome of rehospitalization and death. Thus, the treatment of HFmrEF should be categorized as HFrEF due to the similar benefit of neurohormonal blocking therapy in HFrEF and HFmrEF. [Abstract copyright: © 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.

Prognostic implications of left ventricular ejection fraction trajectory changes in heart failure

AimsThe latest guidelines recommended to assess the trajectory of left ventricular ejection fraction (LVEF) in patients with heart failure (HF). However, there is limited data on the trajectory of LVEF in real-world settings. In this study, we investigated the frequency and prognostic implications of changes in LVEF trajectory.MethodsPatients were divided into intensified LVEF, static LVEF, and worsening LVEF groups based on the transitions of HF types from baseline to follow-up. The intensified and worsening LVEF groups were further subdivided into mild (≤10% absolute changes of LVEF) and significant (>10% absolute changes of LVEF) increase or decrease groups according to the magnitude of change. The incidences and associations of changes in LVEF with patient outcomes were analyzed.ResultsAmong the 2,429 patients in the study cohort, 38.3% of HF with reduced ejection fraction (HFrEF) and 37.6% of HF with mildly reduced ejection fraction (HFmrEF) showed an improvement in their LVEF. In contrast, a decline in LVEF was observed in 19.3% of HF patients with preserved ejection fraction (HFpEF) and 34.9% of those with HFmrEF. Cox regression analysis showed that the intensified LVEF group was associated with a lower risk of composite endpoints, while the worsening LVEF group yielded opposite findings. Subgroup analysis revealed that compared to those with mild changes in LVEF, baseline HFrEF patients with significant increase showed a lower risk of composite outcome, while baseline HFpEF patients were the opposite.ConclusionsThe trajectories of LVEF changes are strongly correlated with outcomes in patients with HF who had prior history of HF admission. The most significant prognostic implications observed in patients with significant LVEF changes. Trajectory LVEF and type of HF changes are useful tools recommended for prognostication

Effects of rhythm control on left atrial structure remodeling in atrial fibrillation and heart failure with preserved ejection fraction

BackgroundThe benefits of rhythm control for atrial fibrillation (AF) in heart failure with preserved ejection fraction (HFpEF) have not been conclusively determined. We assessed the effects of rhythm control on left atrial (LA) structure remodeling and prognosis in patients with AF and HFpEF.MethodsThis was a retrospective, real-world, observational study involving patients diagnosed with AF and HFpEF. The cohort was divided into rhythm-control and rate-control groups depending on their treatment strategies. The primary outcomes were all-cause mortality, rehospitalization for any cause, HF-related rehospitalization, and stroke. Differences in follow-up LA structure parameters were also analyzed.ResultsCompared to the rate-control group, patients in the rhythm-control group had a lower risk of HF-related rehospitalization even after adjusting for potential confounders (adjusted HR 0.605, 95% CI 0.413–0.887, p = 0.010). Moreover, rhythm-control therapy led to marked reductions in LA echocardiographic indicators and a higher proportion of LA reverse remodeling (LARR).ConclusionsRhythm-control therapy reverses LA structure remodeling and is associated with improved clinical outcomes; therefore, it is an optimal treatment approach for AF in HFpEF patients

Reverse atrial remodeling in heart failure with recovered ejection fraction

Background Heart failure with recovered ejection fraction (HFrecEF) has been a newly recognized entity since 2020. However, the concept has primarily focused on left ventricular ejection fraction improvement, with less focus on the recovery of the left atrium. In this study, we investigated changes in left atrial (LA) echocardiographic indices in HFrecEF. Methods and Results An inpatient cohort with heart failure with reduced ejection fraction (HFrEF) was identified retrospectively and followed up prospectively in a single tertiary hospital. The enrolled patients were classified into HFrecEF and persistent HFrEF groups. Alternations in LA parameters by echocardiography were calculated. The primary outcome was a composite of cardiovascular death or heart failure rehospitalization. A total of 699 patients were included (HFrecEF: n=228; persistent HFrEF: n=471). Compared with persistent HFrEF, the HFrecEF group had greater reductions in LA diameter, LA transverse diameter, LA superior–inferior diameter, LA volume, and LA volume index but not in LA sphericity index. Cox regression analysis showed that the HFrecEF group experienced lower risks of prespecified end points than the persistent HFrEF group after adjusting for confounders. Additionally, 136 (59.6%) and 62 (13.0%) patients showed LA reverse remodeling (LARR) for the HFrecEF and persistent HFrEF groups, respectively. Among the HFrecEF subgroup, patients with LARR had better prognosis compared with those without LARR. Multivariate logistic analysis demonstrated that age and coronary heart disease were 2 independent negative predictors for LARR. Conclusions In HFrecEF, both left ventricular systolic function and LA structure remodeling were improved. Patients with HFrecEF with LARR had improved clinical outcomes, indicating that the evaluation of LA size provides a useful biomarker for risk stratification of heart failure