Dingchang Zheng

• Professor of Healthcare Technology
• Professor at Coventry University

There is a well-accepted need for a new more accurate solution to automatic blood pressure measurement, in spite of clinical convenience continuing to encourage the adoption of oscillometric devices with their known poor accuracy throughout healthcare. Our solution avoids estimates, mathematical modelling, oscillometric algorithms, and inadequate c...

With the advancement of the Internet of Things (IoT), WiFi Channel State Information (CSI)-based Human Activity Recognition (HAR) has garnered increasing attention from both academic and industrial communities. However, the scarcity of labeled data remains a prominent challenge in CSI-based HAR, primarily due to privacy concerns and the incomprehen...

Contactless vital signs detection has the potential to advance healthcare by offering precise and convenient patient monitoring. This groundbreaking approach not only streamlines the monitoring process, but also allows continuous, real-time assessment of vital signs, allowing early detection of anomalies and prompt intervention. This paper presents...

Photoplethysmography (PPG) technology enables the measurement of multiple physiological and psychological parameters with low‐cost wearable sensors and is reshaping modern healthcare. Advanced materials play a vital role in improving reliability and accuracy of PPG sensors. Recently, various advanced materials have been explored to optimize PPG sen...

Objective: Aortic pressure waveform (APW) can provide vital indices for the diagnosis of cardiovascular diseases. Although various APW estimation methods have been reported to avoid the risks of direct invasive measurement, more accurate and practical estimation models still need to be developed to promote the application of APW in routine monitori...

Background: Coronary artery disease (CAD) is the leading cause of death worldwide. The registration of the coronary artery at different phases can help radiologists explore the motion patterns of the coronary artery and assist in the diagnosis of CAD. However, there is no automatic and easy-to-execute method to solve the missing data problem that...

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to...

Background: Pulse transit time (PTT) is a key parameter in cuffless blood pressure measurement based on photoplethysmography (PPG) signals. In wearable PPG sensors, raw PPG signals are filtered, which can change the timing of PPG waveform feature points, leading to inaccurate PTT estimation. There is a lack of comprehensive investigation of filteri...

div>WiFi-based human activity recognition (HAR) has been extensively studied due to its far-reaching applications in health domains, including elderly monitoring, exercise supervision, rehabilitation monitoring, etc. Although existing supervised deep learning techniques have achieved remarkable performances for these tasks, they are however data-hu...

Recently, with the advancement of the Internet of Things (IoT), WiFi CSI-based HAR has gained increasing attention from academic and industry communities. By integrating the deep learning technology with CSI-based HAR, researchers achieve state-of-the-art performance without the need of expert knowledge. However, the scarcity of labeled CSI data re...

Objective: The decline in vascular elasticity with aging can be manifested in the shape of pulse wave. The study investigated the pulse wave features that are sensitive to age and the pattern of these features change with increasing age were examined. Methods: Five features were proposed and extracted from the photoplethysmography (PPG)-based pu...

Purpose Coronary microvascular dysfunction (CMD) is emerging as an important cause of myocardial ischemia, but there is a lack of a non-invasive method for reliable early detection of CMD. Aim To develop an electrocardiogram (ECG)-based machine learning algorithm for CMD detection that will lay the groundwork for patient-specific non-invasive earl...

Photoplethysmography (PPG) signals have been widely used in evaluating cardiovascular biomarkers, however, there is a lack of in-depth understanding of the remote usage of this technology and its viability for underdeveloped countries. This study aims to quantitatively evaluate the performance of a low-cost wireless PPG device in detecting ultra-sh...

Background: Intracranial photoplethysmography (PPG) signals can be measured from extracranial sites using wearable sensors and may enable long-term non-invasive monitoring of intracranial pressure (ICP). However, it is still unknown if ICP changes can lead to waveform changes in intracranial PPG signals. Aim: To investigate the effect of ICP change...

Objective：The oscillometric blood pressure (BP) measurement technique estimates BPs from analyzing the oscillometric cuff pressure waveform (oscillogram) envelope. The oscillogram envelope maximum is associated with physiological changes and influences BP measurement accuracy. We aim to quantitatively investigate the effect of BP and aging on the c...

WiFi-based human activity recognition (HAR) has been extensively studied due to its far-reaching applications in health domains, including elderly monitoring, exercise supervision and rehabilitation monitoring, etc. Although existing supervised deep learning techniques have achieved remarkable performances for these tasks, they are however data-hun...

Background: The severe and critical cases of COVID-19 had high mortality rates. Clinical features, laboratory data, and radiological features provided important references for the assessment of COVID-19 severity. The machine learning analysis of clinico-radiological features, especially the quantitative computed tomography (CT) image analysis resu...

Objective: Accurate and reliable blood pressure (BP) measurement is important for the prevention and treatment of hypertension. The oscillometric-based automatic office blood pressure measurement (AOBPM) is widely used in hospitals and clinics, but measurement errors are common in BP measurements. There is a lack of systematic review of the source...

Tumor-treating Fields (TTFields) is a promising cancer therapy technique in clinical application. Computational simulation of TTFields has been used to predict the electric field (EF) distribution in the human body and to optimize the treatment parameters. However, there are only a few studies to validate the accuracy of the simulation model. Here...

Imagined speech based brain-computer interface (BCI) is of great interest due to its efficiency and user-friendliness for patients with speech impairment. The aim of this work was to study whether different rhythms of imagined syllables could elicit corresponding frequency components on EEG amplitude spectra. Seventeen participants were recruited t...

Swallowing recognition is the leading step in the evaluation of dysphagia which seriously affects people's life. Current medical swallowing monitoring methods require an in-hospital environment and overly rely on professional knowledge of the medical staff. In this study, we developed a wearable swallowing recognition system that consists of an on-...

Electrical motor cortex stimulation (EMCS) has been used for Parkinson's Disease (PD) treatment. Some studies found that distinct cell types might lead to selective effects. As the largest subgroup of interneurons, Parvalbumin (PV) neurons have been reported to be involved in the mechanisms of therapeutic efficacy for PD treatment. However, little...

Background and objective: The uterine electrohysterogram (EHG) contains important information about electrical signal propagation which may be useful to monitor and predict the progress of pregnancy towards parturition. Directed information processing has the potential to be of use in studying EHG recordings. However, so far, there is no directed...

Background Invasively measured fractional flow reserve (FFR) and index of microcirculatory resistance (IMR) are gold standards for the diagnosis of coronary artery disease (CAD) and coronary microcirculatory dysfunction (CMD). However, the interaction between CAD and CMD has not been comprehensively investigated. We aim to non-invasively investigat...

Purpose To evaluate the safety and effectiveness of photobiomodulation (PBM) in the treatment of diabetic macular edema (DME). Methods It was a single-center, self-controlled prospective study. The clinical records of 12 diabetic retinopathy patients (5 males and 7 females, 20 eyes in total) who were treated with PBM for DME at the Second Affiliat...

Ballistocardiography (BCG) is considered a good alternative to HRV analysis with its non-contact and unobtrusive acquisition characteristics. However, consensus about its validity has not yet been established. In this study, 50 healthy subjects (26.2 ± 5.5 years old, 22 females, 28 males) were invited. Comprehensive statistical analysis, including...

div>WiFi-based human activity recognition (HAR) has been extensively studied due to its far-reaching applications in health domains, including elderly monitoring, exercise supervision, rehabilitation monitoring, etc. Although existing supervised deep learning techniques have achieved remarkable performances for these tasks, they are however data-hu...

div>WiFi-based human activity recognition (HAR) has been extensively studied due to its far-reaching applications in health domains, including elderly monitoring, exercise supervision, rehabilitation monitoring, etc. Although existing supervised deep learning techniques have achieved remarkable performances for these tasks, they are however data-hu...

div>WiFi-based human activity recognition (HAR) has been extensively studied due to its far-reaching applications in health domains, including elderly monitoring, exercise supervision, rehabilitation monitoring, etc. Although existing supervised deep learning techniques have achieved remarkable performances for these tasks, they are however data-hu...

The dysfunction of coronary microcirculation is an important cause of coronary artery disease (CAD). The index of microcirculatory resistance (IMR) is a quantitative evaluation of coronary microcirculatory function, which provides a significant reference for the prediction, diagnosis, treatment, and prognosis of CAD. IMR also plays a key role in in...

Arterial stiffness (AS) and endothelial function (EF) are two features of the arterial system essential for assessing its function. Routine measurements of AS and EF are powerful tools aiding the diagnosis and prognosis of cardiovascular disease. Photoplethysmography (PPG) lends itself well to the assessment of AS and EF due to its low-cost and eas...

Personalized cardiac modeling is widely used for studying the mechanisms of cardiac arrythmias. Due to the high demanding of computational resource of modeling, the arrhythmias induced in the models are usually simulated for just a few seconds. In clinic, it is common that arrhythmias last for more than several minutes and the morphologies of reent...

[This corrects the article DOI: 10.3389/fphys.2021.718540.].

Background: The three-dimensional (3D) geometry of coronary atherosclerotic plaques is associated with plaque growth and the occurrence of coronary artery disease. However, there is a lack of studies on the 3D geometric properties of coronary plaques. We aim to investigate if coronary plaques of different sizes are consistent in geometric propertie...

This study aimed to analyse the temporal change of diabetes and any associated risk and protective factors for diabetes in Chinese adults between Wave 0 (2003) and Wave 1 (2009) of the World Health Organization (WHO) Study on global AGEing and adult health (SAGE). Data from China of the SAGE were analysed. Diabetes (outcome variable) was assessed b...

Background Newtonian fluid model has been commonly applied in simulating cerebral blood flow in intracranial atherosclerotic stenosis (ICAS) cases using computational fluid dynamics (CFD) modeling, while blood is a shear-thinning non-Newtonian fluid. We aimed to investigate the differences of cerebral hemodynamic metrics quantified in CFD models bu...

Objective: The contours of the pulse wave vary greatly, which affect the accuracy of pulse wave peak detection and the reliability of subsequent peak-based cardiovascular health analyses. We proposed an algorithm to reliably detect the peak of forward pulse wave (forward peak) and proposed to use it for improving the accuracy in cardiovascular hea...

Manual auscultatory is the gold standard for clinical non-invasive blood pressure (BP) measurement, but its usage is decreasing as it requires substantial professional skills and training, and its environmental concerns related to mercury toxicity. As an alternative, automatic oscillometric technique has been used as one of the most common methods...

The black-box nature of machine learning models hinders the deployment of some high-accuracy models in medical diagnosis. It is risky to put one's life in the hands of models that medical researchers do not fully understand. However, through model interpretation, black-box models can promptly reveal significant biomarkers that medical practitioners...

Background: The oscillometric blood pressure (BP) measurement technique estimates BPs from analyzing the envelop of oscillometric cuff pressure waveform. The oscillometric waveform envelope shape is associated with physiological changes and influences BP measurement accuracy. The aim of this study was to comprehensively quantify BP- and age-relate...

Objective: Filtering can change the timing of pulse feature points on photoplethysmography (PPG) signals. We aim to quantitatively investigate the effect of measurement site and type of pulse feature on the filtering-induced time shift (TS). Approach: 60-second PPG signals were measured from six body sites [finger, wrist under (volar), wrist upp...

The respiration rate (RR) is a vital sign in physiological measurement and clinical diagnosis. RR can be measured using stretchable and wearable strain gauge sensors which detect the respiratory movements in the abdomen or thorax areas caused by volumetric changes. In different body locations, the accuracy of RR detection might differ due to differ...

Objective: A proof-of-concept study to assess the potential of a Deep Learning (DL) based photoplethysmography PPG ('DLPPG') classification method to detect peripheral arterial disease (PAD) using toe PPG signals. Approach: PPG spectrogram images derived from our previously published multi-site PPG datasets (214 participants; 31.3% legs with PAD...

Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the m...

Uterine contraction (UC) is an essential clinical indicator in the progress of labour and delivery. Electrohysterogram (EHG) signals recorded on the abdomen of pregnant women reflect the uterine electrical activity. This study proposes a novel algorithm for automatic recognition of UCs with EHG signals to improve the accuracy of detecting UCs. EHG...

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a progressive disease that causes long-term breathing problems. The reliable monitoring of respiratory rate (RR) is very important for the treatment and management of COPD. Based on inkjet printing technology, we have developed a stretchable and wearable sensor that can accurately measur...

The present work assessed Mandarin sentence understanding when the electric and acoustic portions are not temporally aligned in simulated combined electric-and-acoustic stimulation (EAS). A relative time shift was added between the electric and acoustic portions, simulating the temporal misalignment effect in EAS processing. The processed stimuli w...

Objective: Despite the vast number of photoplethysmography (PPG) research publications and growing demands for such sensing in Digital and Wearable Health platforms, there appears little published on signal quality expectations for morphological pulse analysis. Aim: to determine a consensus regarding the minimum number of undistorted i.e., diagnost...

Objective: The aim of this study was to evaluate the performance of using a deep learning-based method for measuring SBPs and DBPs and the effects of cuff inflation and deflation rates on the deep learning-based blood pressure (BP) measurement (in comparison with the manual auscultatory method). Methods: Forty healthy subjects were recruited. SB...

This paper aimed to evaluate the effect of various electrode configurations on applying a convolutional neural network (CNN) to recognize uterine contraction (UC) with Electrohysterogram (EHG) signals. Seven 8‐electrode configurations and thirteen 4‐electrode configurations were selected from the 4 × 4 electrode grid in the Icelandic 16‐electrode E...

Black-box nature hinders the deployment of many high-accuracy models in medical diagnosis. Putting one's life in the hands of models that medical researchers do not trust it's irresponsible. However, to understand the mechanism of a new virus, such as COVID-19, machine learning models may catch important symptoms that medical practitioners do not n...

The relatively limited understanding of the physiology of uterine activation prevents us from achieving optimal clinical outcomes for managing serious pregnancy disorders such as preterm birth or uterine dystocia. There is increasing awareness that multi-scale computational modeling of the uterus is a promising approach for providing a qualitative...

Objective: Based on different physiological mechanisms, respiratory modulations of photoplethysmography (PPG) signal differ in strength and resultant accuracy of respiratory frequency (RF) estimation. We aimed to investigate the strength of different respiratory modulations and the accuracy of resultant RF estimation in different body sites and tw...

Introduction Respiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelero...

Background: Various computational models of the circle of Willis (CoW) have been developed to non-invasively estimate the blood flow and hemodynamic parameters in intracranial arteries for the assessment of clinical risks such as aneurysms, ischemia, and atherosclerotic plaque growth. This review aims to categorize the latest computational models o...

Instantaneous wave-free ratio (iFR) has been proposed as a hemodynamic parameter that can reliably reflect the blood flow in stenosed coronary arteries. Currently, there are few investigations on the quantitative analysis of iFR in the patients with the variation of microcirculatory resistance (MR). The data aim to provide geometric (cross-section...

The potential of using the information of uterine contractions (UCs) derived from electrohysterogram (EHG) has been recognized in early detection of preterm delivery. A better understanding of the conduction property of EHG is clinically useful for developing advanced methods to achieve a reliable prediction of preterm delivery. In this paper, a me...

Auditory stream segregation is an important function of the auditory system, and the extent to which this function works has a major impact on listener's ability to recognize auditory objects in complex listening environments. However, cochlear implant (CI) listeners are poorly equipped for this challenge, mainly owing to the impoverished sensory i...

Reverberation reduces speech quality, and therefore causes inconveniency to listeners, especially those using assistive hearing devices. To enhance the quality of reverberant speech, a significant step is speech quality assessment, most of which are based on subjective judgements. Subjective evaluations vary with listeners' perception, emotional an...

Background and Objective The instantaneous wave-free ratio (iFR) has been proposed to estimate the hemodynamic severity of atherosclerotic stenosis in coronary arteries. The atherosclerotic stenosis in a proximal coronary artery could change its distal microcirculatory resistance (MR). However, there is a lack of investigation about the effect of M...

Elevated blood pressure (BP) is a major cause of death, yet hypertension commonly goes undetected. Owing to its nature, it is typically asymptomatic until later in its progression when the vessel or organ structure has already been compromised. Therefore, noninvasive and continuous BP measurement methods are needed to ensure appropriate diagnosis a...

Background: As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention. Microaneurysms appear as the earliest symptom of DR. Accurate and reliable detection of microaneurysms in color fundus images has great importance for DR screening. M...

Traditional cuff-based blood pressure (BP) monitoring procedure causes inconvenience and discomfort to the users. To overcome these limitations, cuffless BP estimation based on pulse transit time (PTT) and single-channel photoplethysmography (PPG) has been proposed. However, existing studies based on PTT and PPG for BP estimation did not achieve AA...

Background: Tandem stenoses were widely observed in acute stroke cases. High pressure drop and low fractional flow (FF) indicate the risk of ischemia caused by intracranial atherosclerotic stenosis. Low wall shear stress (WSS) and high low-density lipoprotein (LDL) filtration rate indicate the risk of atherosclerotic plaque growth. High WSS is rela...

One in three adults worldwide has hypertension, which is associated with significant morbidity and mortality. Consequently, there is a global demand for continuous and non-invasive blood pressure (BP) measurements that are convenient, easy to use, and more accurate than the currently available methods for detecting hypertension. This could easily b...

Background: As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention. Microaneurysms appear as the earliest symptom of DR. Accurate and reliable detection of microaneurysms in color fundus images has great importance for DR screening. Met...

Background: As a major complication of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention. Microaneurysm appears as the earliest symptom of DR. Accurate and reliable detection of microaneurysms in color fundus images has great importance for DR screening. Methods: A mi...

Respiratory rate (RR) is a vital sign with continuous, convenient, and accurate measurement which is difficult and still under investigation. The present study investigates and evaluates a stretchable and wearable inkjet-printed strain gauge sensor (IJP) to estimate the RR continuously by detecting the respiratory volume change in the chest area. A...

Developing a computational method for recognizing preterm delivery is important for timely diagnosis and treatment of preterm delivery. The main aim of this study was to evaluate electrohysterogram (EHG) signals recorded at different gestational weeks for recognizing the preterm delivery using random forest (RF). EHG signals from 300 pregnant women...

Objectives: It is clinically important to evaluate the performance of a newly developed blood pressure (BP) measurement method under different measurement conditions. This study aims to evaluate the performance of using deep learning based method to measure BPs and BP change under non-resting conditions. Materials and Methods: 40 healthy subjects w...

Hypertension is one of the most prevalent diseases and is often called the “silent killer” because there are usually no early symptoms. Hypertension is also associated with multiple morbidities, including chronic kidney disease and cardiovascular disease. Early detection and intervention are therefore important. The current routine method for diagn...

Background: Uterine contraction (UC) is the tightening and shortening of the uterine muscles which can indicate the progress of pregnancy towards delivery. Electrohysterogram (EHG), which reflects uterine electrical activities, has recently been studied for UC monitoring. In this paper, we aimed to evaluate different EHG segments for recognizing U...

The respiration rate (RR) is a key vital sign that links to adverse clinical outcomes and has various important uses. However, RR signals have been neglected in many clinical practices for several reasons and it is still difficult to develop low-cost RR sensors for accurate, automated, and continuous measurement. This study aims to fabricate, devel...