This article studies the relation between electrocardiogram (ECG) and photoplethysmogram (PPG) investigates inference of ECG waveforms from PPG signals that can be obtained affordable wearable Internet-of-Things (IoT) devices for mobile health. In order to address this inverse problem, a transform is proposed map discrete cosine (DCT) coefficients each cycle those corresponding based on cardiovascular signal model. The method evaluated with different morphologies three benchmark data sets...

In the field of information forensics, many emerging problems involve a critical step that estimates and tracks weak frequency components in noisy signals. It is often challenging for prior art tracking to i) achieve high accuracy under conditions, ii) detect track multiple efficiently, or iii) strike good trade-off processing delay versus resilience tracking. To address these issues, we propose Adaptive Multi-Trace Carving (AMTC), unified approach detecting one more subtle very low...

In observational studies, confounder separation and balancing are the fundamental problems of treatment effect estimation. Most previous methods focused on addressing problem by treating all observed pre-treatment variables as confounders, ignoring separation. general, not confounders that refer to common causes outcome, some only contribute (i.e., instrumental variables) outcome adjustment variables). Balancing those non-confounders, including variables, would generate additional bias for...

In this paper, the relation between electrocardiogram (ECG) and photoplethysmogram (PPG) signals is studied, waveform of ECG inferred via PPG signals. order to address inverse problem, a transform proposed map discrete cosine (DCT) coefficients each cycle those corresponding cycle. The resulting DCT are inversely transformed obtain reconstructed waveform. method evaluated on benchmark dataset subjects with variety combinations age weight. Experimental results show that can achieve high...

An emerging research direction considers the inverse problem of inferring electrocardiogram (ECG) from photoplethysmogram (PPG) to bring about synergy between easy measurability PPG and rich clinical knowledge ECG facilitate preventive healthcare. Previous reconstruction using a universal basis has limited accuracy due lack representative power. This paper proposes cross-domain joint dictionary learning (XDJDL) framework maximize expressive power for two signals. Building on K-SVD technique,...

The electric network frequency (ENF) signal is an environmental signature that can be captured in audiovisual recordings made locations where there electrical activity. This influenced by the power grid which recording made, and recent work has shown it useful toward a number of forensics security applications. An under-studied area ENF research factors affect capture traces media recordings. Not all areas activity will carry prominent traces, strengths are vary from one to another. A...

Recent studies showed that subtle changes in human's face color due to the heartbeat can be captured by digital video recorders. Most existing work focused on still/rest cases or those with relatively small motions. In this work, we propose a heart-rate monitoring method for fitness exercise videos. We focus designing highly precise motion compensation scheme help of optical flow, and use information as cue adaptively remove ambiguous frequency components improving heart rates estimates....

This paper introduces an amplitude and frequency modulation (AM-FM) model to characterize the photoplethysmography (PPG) signal. The indicates that PPG signal spectrum contains one dominant component - heart rate (HR), which is guarded by two weaker components on both sides; distance from guard represents respiratory (RR). Based this model, efficient algorithm proposed estimate HR RR searching for components. method performed in domain RR, more robust additive noise than prior art based...

This paper presents a computational solution that enables continuous cardiac monitoring through cross-modality inference of electrocardiogram (ECG). While some smartwatches now allow users to obtain 30-second ECG test by tapping built-in bio-sensor, these short-term tests often miss intermittent and asymptomatic abnormalities functions. It is also infeasible expect persistently active user participation for long-term in order capture other types abnormalities. To alleviate the need attention...

In this paper, we study the problem of tracking multiple frequency components in a noisy signal using spectrogram-based method. Previous approaches such as image processing based or hidden Markov model methods may not be capable components, require extensive training, and time-consuming. To address these issues, propose an accurate efficient method named Adaptive Multi-Trace Carving (AMTC) for traces by iterative forward backward dynamic programming adaptive trace compensation. Experimental...

Vital signs, such as heart rate (HR), variability (HRV), respiratory (RR), are important indicators for a person's health. signs traditionally measured with contact sensors, and may be inconvenient cause discomfort during continuous monitoring. Commercial cameras promising contact-free remote photoplethysmography (rPPG) have been studied to remotely monitor from face videos. For RR measurement, most prior art was based on small periodical motions of chest regions caused by breathing cycles,...

The inverse problem of inferring electrocardiogram (ECG) from photoplethysmogram (PPG) is an emerging research direction that combines the easy measurability PPG and rich clinical knowledge ECG for long-term continuous cardiac monitoring. prior art reconstruction using a universal basis has limited fidelity uncommon waveform shapes due to lack representative power. In this paper, we design two dictionary learning frameworks, cross-domain joint (XDJDL) label-consistent XDJDL (LC-XDJDL),...

Both interpretation and accuracy are very important for a predictive model in real applications, but most of previous works, no matter interpretable models or black-box models, cannot simultaneously achieve both them, resulting tradeoff between accuracy. To break this trade-off, paper, we propose flexible framework, named IB-M, to align an Interpretable Blackbox Model optimizing Generally, think samples that well-clustered away from the true decision boundary can be easily interpreted by...

Performance improvements obtained by recent principled approaches for pulse rate (PR) estimation have typically been achieved adding or modifying certain modules within a reconfigurable system. Yet, evaluations are usually performed only at the system level. To better understand each module's contribution and facilitate future research in explainable learning artificial intelligence physiological monitoring, this paper conducts comparative study of video-based, PR tracking algorithms, with...

A wireless electrocardiogram (ECG) transmission system is developed which integrates current personal digital assistant (PDA) technology and general packet radio service (GPRS) technology. This PDA-based comprised of a designed ECG signal acquisition module, Pocket PC (Legend 5100) GPRS communication module. The specific objective this to facilitate accurate reliable monitoring patient's signal. able acquire signals, display the waveform on LCD screen PDA wirelessly transmit them an...

Infrared thermographs (IRTs, also called thermal cameras) have been used to remotely measure elevated body temperature (BT) and respiratory rate (RR) during infectious disease outbreaks, such as COVID-19. To facilitate the fast measurement of BT RR using IRTs in densely populated venues, it is desirable IRT algorithms that can automatically identify best facial locations images extract these vital signs. The IEC 80601-2-59:2017 standard suggests regions medially adjacent inner canthi eyes...

A conversion method based on the inversion of Mel frequency cepstral coefficient (MFCC) features was proposed to convert whispered speech into normal speech. First, MFCC and were extracted a matching relation between feature parameters developed through Gaussian mixture model (GMM). Then, corresponding obtained GMM and, finally, converted features. The experimental results showed that distortion (CD) by 21% less than linear predictive (LPC) features, mean opinion score (MOS) 3.56,...

Abstract This paper studies the relation between electrocardiogram (ECG) and photoplethysmogram (PPG) infers waveform of ECG via PPG signals that can be obtained from affordable wearable Internet-of-Things (IoT) devices for mobile health. In order to address this inverse problem, a transform is proposed map discrete cosine (DCT) coefficients each cycle those corresponding based on our cardiovascular signal model. The method evaluated with different morphologies three benchmark datasets...

Attribute information in fine-grained image recognition often provides more accurate and rich related to categories. How effectively combine such knowledge guide classification tasks has been one of the research hotspots computer vision recent years. We believe that using association relationship between attributes fuse attribute can obtain a representation image. In this paper, we propose novel Multi-Task Fusion Model (MTAF) which makes two major improvements traditional multi-task learning...

The existence of malicious secondary users will bring damage to the performance cooperative spectrum sensing and access in cognitive radio networks, so effectively curbing behavior become key success for mechanism.Inspired by economics repeated game theory, a trust model algorithm distributed oriented named FRTrust is proposed.In FRTrust, reputation status used describe user process.It encourages choose positive honest strategies greater long term benefits.Simultaneously, 'differentiation'...

We present a recurrent neural network (RNN) based speech bandwidth extension (BWE) method. The conventional Gaussian mixture model (GMM) BWE methods perform stably and effectively. However, GMM suffer from two fundamental competing problems: 1) inadequacy of in modeling the non-linear relationship between low frequency (LF) high (HF), 2) temporal correlations across frames are ignored, resulting spectral detail loss reconstructed by BWE. To cope these problems, RNN is employed to capture...

In order to solve the problem that urban spatial pattern causes by gradually deteriorating microclimate,directly affecting comfort of living environment and clarify influence configuration on residential microclimate, a microclimate detection system based wireless sensor network is proposed detect area,and mathematical modeling method relationship between different parameters such as: (building density, average height building, horizontal layout vertical layout), (mean radiant...