Rihui Li

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Verified

Rihui verified their affiliation via an institutional email.

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• Doctor of Philosophy
• Assistant Professor at University of Macau

For the needs of bladder urinary volume noninvasive monitoring in clinical, we present a noninvasive bladder urinary volume monitoring system based on bio-impedance. The system uses a four-electrode structure, which is composed of a pair of excitation electrodes and a pair of measurement electrodes. The Direct Digital Frequency Synthesis (DDS) is a...

Continuous wave-diffuse optical tomography (CW-DOT) has emerged as a promising non-invasive neuroimaging technique for assessing brain function. Its ability to provide brain mapping with high spatial resolution over traditional functional near-infrared spectroscopy (fNIRS) has garnered significant interest in clinical and cognitive neuroscience. In...

The performance of modern U-shaped neural networks for medical image segmentation has been significantly enhanced by incorporating Transformer layers. Although Transformer architectures are powerful at extracting global information, its ability to capture local information is limited due to their high complexity. To address this challenge, we propo...

Significance Functional near-infrared spectroscopy (fNIRS) has been widely used to assess brain functional networks due to its superior ecological validity. Generally, fNIRS signals are sensitive to motion artifacts (MA), which can be removed by various MA correction algorithms. Yet, fNIRS signals may also undergo varying degrees of distortion due...

Background: Klinefelter syndrome (KS), also referred to as XXY syndrome, is a significant but inadequately studied risk factor for neuropsychiatric disability. Whether alterations in functional brain connectivity or pubertal delays are associated with aberrant cognitive-behavioral outcomes in individuals with KS is largely unknown. In this observat...

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presen...

This study aims to identify dynamic patterns within the spatiotemporal feature space that are specific to nonpsychotic major depression (NPMD), psychotic major depression (PMD), and schizophrenia (SCZ). The study also evaluates the effectiveness of machine learning algorithms based on these network manifestations in differentiating individuals with...

Perceiving and modulating emotions is vital for cognitive function and is often impaired in neuropsychiatric conditions. Current tools for evaluating emotional dysregulation suffer from subjectivity and lack of precision, especially when it comes to understanding emotion from a regulatory or control-based perspective. To address these limitations,...

Transformers using self-attention mechanisms have recently advanced medical imaging by modeling long-range semantic dependencies, though they lack the ability of convolutional neural networks (CNNs) to capture local spatial details. This study introduced a novel segmentation (SEG) network derived from a mixed CNN-Transformer (MixFormer) feature ext...

Background Electroencephalogram (EEG) has emerged as a non‐invasive tool to detect the aberrant neuronal activity related to different stages of Alzheimer’s disease (AD). However, the effectiveness of EEG in the precise diagnosis and prediction of AD and its preclinical stage, mild cognitive impairment (MCI), has yet to be fully elucidated. In this...

Autism spectrum disorder (ASD) is characterized by etiological and phenotypic heterogeneity. Despite efforts to categorize ASD into subtypes, research on specific functional connectivity changes within ASD subgroups based on clinical presentations is limited. This study proposed a symptom-based clustering approach to identify subgroups of ASD based...

Background: Generative adversarial networks (GANs) have demonstrated superior data generation capabilities compared to other methods, making them popular for use in medical image applications. These features have intrigued researchers in the medical imaging field, resulting in a swift implementation of these techniques in various conventional and n...

This study aims to identify dynamic patterns within the spatiotemporal feature space that are specific to non-psychotic major depression (NPMD), psychotic major depression (PMD), and schizophrenia (SCZ). It also evaluates the effectiveness of machine learning algorithms based on these network manifestations in differentiating individuals with NPMD,...

Protocols have been proposed to optimize neuromodulation targets and parameters to increase treatment efficacies for different neuropsychiatric diseases. However, no study has investigated the temporal effects of optimal neuromodulation targets and parameters simultaneously via exploring the test–retest reliability of the optimal neuromodulation pr...

Children with fragile X syndrome (FXS) often avoid eye contact, a behavior that is potentially related to hyperarousal. Prior studies, however, have focused on between-person associations rather than coupling of within-person changes in gaze behaviors and arousal. In addition, there is debate about whether prompts to maintain eye contact are benefi...

Background: Fragile X syndrome (FXS) is an X chromosome-linked, genetic disorder characterized by increased risk for behavioral, social, and neurocognitive deficits. Due to a more severe phenotype relative to females, research has focused largely on identifying neural abnormalities in all-male or mixed-sex participants with FXS. Therefore, very li...

Background Electroencephalogram (EEG) has emerged as a non-invasive tool to detect the aberrant neuronal activity related to different stages of Alzheimer’s disease (AD). However, the effectiveness of EEG in the precise diagnosis and assessment of AD and its preclinical stage, amnestic mild cognitive impairment (MCI), has yet to be fully elucidated...

Functional near-infrared spectroscopy (fNIRS) is an optical imaging technique for assessing human brain activity by noninvasively measuring the fluctuation of cerebral oxygenated- and deoxygenated-hemoglobin concentrations associated with neuronal activity. Owing to its superior mobility, low cost, and good tolerance for motion, the past few decade...

A growing number of social interactions are taking place virtually on videoconferencing platforms. Here, we explore potential effects of virtual interactions on observed behavior, subjective experience, and neural “single-brain” and “interbrain” activity via functional near-infrared spectroscopy neuroimaging. We scanned a total of 36 human dyads (7...

Background Identifying neural activation patterns that predict youths' treatment response may aid in the development of imaging-based assessment of emotion dysregulation following trauma and foster tailored intervention. Changes in cortical hemodynamic activity measured with functional near-infrared spectroscopy (fNIRS) may provide a time and cost-...

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor tempor...

Motor control deficits are very common in stroke survivors and often lead to disability. Current clinical measures for profiling motor control impairments are largely subjective and lack precise interpretation in a “control” perspective. This study aims to provide an accurate interpretation and assessment of the underlying “motor control” deficits...

A growing number of social interactions are taking place virtually on video conferencing platforms. Here, we explore potential effects of virtual interactions on observed behavior, subjective experience, and neural “single-brain “ and “inter-brain “ activity via functional near-infrared spectroscopy (fNIRS) neuroimaging. We scanned a total of 36 hu...

Background Identifying neural activation patterns that predict youths’ treatment response may aid in the development of imaging-based assessment of emotion dysregulation following trauma and foster tailored intervention. Changes in cortical hemodynamic activity measured with functional near-infrared spectroscopy (fNIRS) may provide a time and cost-...

Girls with fragile X syndrome (FXS) often manifest significant symptoms of avoidance, anxiety, and arousal, particularly in the context of social interaction. However, little is currently known about the associations among neurobiological, biobehavioral such as eye gaze pattern, and social-cognitive dysfunction in real-world settings. In this study...

Recognizing the emotional states of humans through EEG signals are of great significance to the progress of human-computer interaction. The present study aimed to perform automatic recognition of music-evoked emotions through region-specific information and dynamic functional connectivity of EEG signals and a deep learning neural network. EEG signa...

INTRODUCTION Cervical cancer is a high incidence of cancer in women and cervical precancerous screening plays an important role in reducing the mortality rate. METHOD - In this study, we proposed a multichannel feature extraction method based on the probability distribution features of the acetowhite (AW) region to identify cervical precancerous l...

Muscle coordination and motor function of stroke patients are weakened by stroke-related motor impairments. Our earlier studies have determined alterations in inter-muscular coordination patterns (muscle synergies). However, the functional connectivity of these synergistically paired or unpaired muscles is still unclear in stroke patients. The goal...

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technique with the potential to enable the assessment of posttraumatic stress disorder (PTSD) brain biomarkers in an affordable and portable manner. Consistent with biological models of PTSD, functional magnetic resonance imaging (fMRI) and fNIRS studies of adults with tra...

Background: Children and adolescents with fragile X syndrome (FXS) manifest significant symptoms of anxiety, particularly in response to face-to-face social interaction. In this study we used functional near-infrared spectroscopy (fNIRS) to reveal a specific pattern of brain activation and habituation in response to face stimuli in young girls wit...

How two brains communicate with each other during social interaction is highly dynamic and complex. Multi-person (i.e., hyperscanning) studies to date have focused on analyzing the entire time series of brain signals to reveal an overall pattern of inter-brain synchrony (IBS). However, this approach does not account for the dynamic nature of social...

Electroencephalography (EEG)-based driving fatigue detection has gained increasing attention recently due to the non-invasive, low-cost, and potable nature of the EEG technology, but it is still challenging to extract informative features from noisy EEG signals for driving fatigue detection. Radial basis function (RBF) neural network has drawn lots...

Background Persistent motor deficits are very common in poststroke survivors and often lead to disability. Current clinical measures for profiling motor impairment and assessing poststroke recovery are largely subjective and lack precision. Objective A multimodal neuroimaging approach was developed based on concurrent functional near-infrared spec...

Both labeled and unlabeled data have been widely used in electroencephalographic (EEG)-based brain-computer interface (BCI). However, labeled EEG samples are generally scarce and expensive to collect, while unlabeled samples are considered to be abundant in real applications. Although the semi-supervised learning (SSL) allows us to utilize both lab...

Muscle networks represent a series of interactions among muscles in the central nervous system’s effort to reduce the redundancy of the musculoskeletal system in motor-control. How this occurs has only been investigated recently in healthy subjects with a novel technique exploring the functional connectivity between muscles through intermuscular co...

Driving fatigue accounts for a large number of traffic accidents in modern life nowadays. It is therefore of great importance to reduce this risky factor by detecting the driver’s drowsiness condition. This study aimed to detect drivers’ drowsiness using an advanced electroencephalography (EEG)-based classification technique. We first collected EEG...

Neurovascular coupling represents the relationship between changes in neuronal activity and cerebral hemodynamics. Concurrent Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recording and integration analysis has emerged as a promising multi-modal neuroimaging approach to study the neurovascular coupling as it provide...

Background: Alzheimer's disease (AD) is projected to become one of the most expensive diseases in modern history, and yet diagnostic uncertainties exist that can only be confirmed by postmortem brain examination. Machine Learning (ML) algorithms have been proposed as a feasible alternative to the diagnosis of several neurological diseases and diso...

Amnestic mild cognitive impairment (aMCI) is conceptualized as a cognitive disorder characterized by memory deficits. Patients with aMCI are treated as prodromal stage of Alzheimer's disease (AD) and have an increased likelihood of developing into AD. The investigation of aMCI is therefore fundamental to the early detection and intervention of AD....

The rapid development of the automotive industry has brought great convenience to our life, which also leads to a dramatic increase in the amount of traffic accidents. A large proportion of traffic accidents were caused by driving fatigue. EEG is considered as a direct, effective, and promising modality to detect driving fatigue. In this study, we...

Objective Physical and mental status of neurosurgeons may vary with emergency status and hours of operation, which may impact the outcome of patients undergoing surgery. This study aims to clarify the influence of these parameters on outcome after surgery in glioma patients. Patients and methods A total of 477 nonemergency surgery (NES) and 30 eme...

Purpose The aim of this study was to document more appropriate electrode location of a four-electrode-based electrical impedance technology in the monitoring of bladder filling, and to characterize the relationship between bladder filling duration and the measured electrical impedances. Methods A simulation study, based on a 2-dimension computatio...

Repetitive transcranial magnetic stimulation (rTMS) at sub-threshold intensity is a viable clinical strategy to enhance the sensory and motor functions of extremities by increasing or decreasing motor cortical excitability. Despite this, it remains unclear how sub-threshold rTMS modulates brain cortical excitability and connectivity. In this study,...

Emerging evidence indicates that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain network. Exploring alterations in the AD brain network is therefore of great importance for understanding and treating the disease. This study employs an integrative functional near-infrared spectroscopy (fNIRS) – electroencephal...

Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, wherein patients have an increased likelihood of developing Alzheimer’s disease (AD). The classification of MCI and different AD stages is therefore fundamental for understanding and treating the disease. This study aimed to comprehensively investigate the h...

Electrical properties of human tissues are usually linked with structure of thin insulating membranes and thereby reflect physiological function of the tissues or organs. It is clinically important to characterize electrical properties of tissues in vivo. Electrical impedance tomography (EIT) is a recently developed medical imaging technique which...

The coupling strength between electroencephalogram (EEG) and electromyography (EMG) signals during motion control reflects the interaction between the cerebral motor cortex and muscles. Therefore, neuromuscular coupling characterization is instructive in assessing motor function. In this study, to overcome the limitation of losing the characteristi...

Brain-Computer Interface (BCI) techniques hold a great promise for neuroprosthetic applications. A desirable BCI system should be portable, minimally invasive, and feature high classification accuracy and efficiency. As two commonly used non-invasive brain imaging modalities, Electroencephalography (EEG) and functional near-infrared spectroscopy (f...

Effects of high frequency repetitive transcranial magnetic stimulation (rTMS) with a subthreshold intensity on hemodynamic response in brain cortices (both motor and prefrontal cortices) was investigated using the functional near infrared spectroscopy (fNIRS) technique. FNIRS signals of the motor and prefrontal cortices were acquired in healthy vol...

Aiming to assist stroke patients who suffer from motor dysfunction after stroke and reduce the stress of physiotherapists, a 3-degree-of-freedom (3DOF) lower limb rehabilitation robot (LLRR) has been developed for the motion recovery in this paper. At first, a simple and flexible structure of LLRR is designed, which involves hip, knee and ankle joi...

A non-invasive method based on electrical impedance tomography (EIT) is presented for continuously assessment of human bladder urinary volume. An EIT system developed for bladder urinary volume imaging is first introduced. To validate the system and to examine the feasibility of estimating bladder fullness with EIT, we conduct an ex vivo experiment...

Ankle rehabilitation training can help the patient better recover from ankle joint injury. This paper presents an ankle rehabilitation device (ARD), which is composed of mechanical structure and its electronic controller unit. ARD can provide ankle training in sagittal plane. The device covers three rehabilitation training modes, which are called a...