IEEE Transactions on Bio-medical Engineering

OBJECTIVE: Growing attention has been paid recently to electrocardiogram (ECG) based obstructive sleep apnea (OSA) detection, with some progresses been made on this topic. However, the lack of data, low data quality, and incomplete data labeling hinder the application of deep learning to OSA detection, which in turn affects the overall generalization capacity of the network. METHODS: To address these issues, we propose the ResT-ECGAN framework. It uses a one-dimensional generative adversarial network (ECGAN) for sample generation, and integrates it into ResTNet for OSA detection...

Background Pulse wave velocity (PWV) is a marker of arterial stiffness and local measurements could facilitate its widescale clinical use. However, confluence of incident and early reflected waves leads to biased spatiotemporal PWV estimates. Objective We introduce the Double Gaussian Propagation Model (DGPM) to measure local PWV in consideration of wave confluence (PWVDGPM ) and compare it against conventional spatiotemporal PWV (PWVST ), with Bramwell-Hill PWV (PWVBH ) and blood pressure (BP) as reference measures...

Magnetic Particle Imaging (MPI)-guided Magnetic Fluid Hyperthermia (MFH) has the potential for widespread utilization, as it allows for the prediction of magnetothermal dosage, real-time visualization of the thermal therapy process, and precise localization of the lesion area. However, the existing MPI-guided MFH (MPI-MFH) method is insensitive to concentration gradients of magnetic nanoparticles (MNPs) and is susceptible to causing damage to normal tissues with high MNP concentrations during MFH treatment, while inadequately heating tumor tissues with lower MNP concentrations...

OBJECTIVE: This study aims to explore the potential of organic electrolytic photocapacitors (OEPCs), an innovative photovoltaic device, in mediating the activation of native voltage-gated Cav1.2 channels (ICa,L) in Guinea pig ventricular cardiomyocytes. METHODS: Whole-cell patch-clamp recordings were employed to examine light-triggered OEPC mediated ICa,L activation, integrating the channel's kinetic properties into a multicompartment cell model to take intracellular ion concentrations into account...

OBJECTIVE: Sleep apnea syndrome (SAS) is a common sleep disorder, which has been shown to be an important contributor to major neurocognitive and cardiovascular sequelae. Considering current diagnostic strategies are limited with bulky medical devices and high examination expenses, a large number of cases go undiagnosed. To enable large-scale screening for SAS, wearable photoplethysmography (PPG) technologies have been used as an early detection tool. However, existing algorithms are energy-intensive and require large amounts of memory resources, which are believed to be the major drawbacks for further promotion of wearable devices for SAS detection...

OBJECTIVE: Human resting-state networks (RSNs) estimated from oxygenated (HbO) and deoxygenated hemoglobin (HbR) data exhibit strong similarities, while task-based studies show different dynamics in HbR and HbO responses. Such a discrepancy might be explained due to time-averaged estimations of RSNs. Our study investigated differences between HbO and HbR on time-resolved brain-wide coactivation patterns (CAPs). APPROACH: Diffuse optical tomography was reconstructed from resting-state whole-head functional near-infrared spectroscopy data of HbR and HbO in individual healthy participants...

UNLABELLED: Photo-mediated ultrasound therapy (PUT) is a novel antivascular therapeutic modality based on cavitation-induced bioeffects. During PUT, synergistic combinations of laser pulses and ultrasound bursts are used to remove the targeted microvessels selectively and precisely without harming nearby tissue. In the current study, an integrated system combining PUT and spectral domain optical coherence tomography (SD-OCT) was developed, where the SD-OCT system was used to guide PUT by detecting cavitation in real time in the retina of the eye...

Some classification studies of brain-computer interface (BCI) based on speech imagery show potential for improving communication skills in patients with amyotrophic lateral sclerosis (ALS). However, current research on speech imagery is limited in scope and primarily focuses on vowels or a few selected words. In this paper, we propose a complete research scheme for multi-character classification based on EEG signals derived from speech imagery. Firstly, we record 31 speech imagery contents, including 26 alphabets and 5 commonly used punctuation marks, from seven subjects using a 32-channel electroencephalogram (EEG) device...

OBJECTIVE: Finding events of interest is a common task in biomedical signal processing. The detection of epileptic seizures and signal artefacts are two key examples. Epoch-based classification is the typical machine learning framework to detect such signal events because of the straightforward application of classical machine learning techniques. Usually, post-processing is required to achieve good performance and enforce temporal dependencies. Designing the right post-processing scheme to convert these classification outputs into events is a tedious, and labor-intensive element of this framework...

OBJECTIVE: Minimally invasive ultrasound ablation transducers have been widely studied. However, conventional designs are limited by the single working frequency, restricting their conformal ablation ability (i.e. ablation size and shape controllability). METHODS: New multi-frequency ultrasonic transducer design method is proposed based on the asymmetric backing layer, which divides the transducer into non-backing-layer region (i.e. front-piezoelectric region) and backing-layer region (i...

OBJECTIVE: We explored the capabilities of power-Doppler ultrasonic (PD-US) imaging without contrast enhancement for monitoring changes in muscle perfusion over time. METHODS: Ischemic recovery was observed in healthy and type II diabetic male and female mice with and without exercise. In separate studies, perfusion was measured during and after 5-min ischemic periods and during four-week recovery periods following irreversible femoral ligation. A goal was to assess how well PD-US estimates tracked the diabetic-related changes in endothelial function that influenced perfusion...

OBJECTIVE: this study is to investigate the feasibility of our recently developed nonlinear fiberscope for label-free in situ breast tumor detection and lymph node status assessment based on second harmonic generation (SHG) imaging of fibrillar collagen matrix with histological details. The long-term goal is to improve the current biopsy-based cancer paradigm with reduced sampling errors. METHODS: in this pilot study we undertook retrospective SHG imaging study of ex vivo invasive ductal carcinoma human biopsy tissue samples, and carried out quantitative image analysis to search for collagen structural signatures that are associated with the malignance of breast cancer...

OBJECTIVE: Cortico-muscular coherence (CMC) is becoming a common technique for detection and characterization of functional coupling between the motor cortex and muscle activity. It is typically evaluated between surface electromyogram (sEMG) and electroencephalogram (EEG) signals collected synchronously during controlled movement tasks. However, the presence of noise and activities unrelated to observed motor tasks in sEMG and EEG results in low CMC levels, which often makes functional coupling difficult to detect...

Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in the brain and is widely used for brain disorder analysis. Previous studies focus on extracting fMRI representations using machine/deep learning methods, but these features typically lack biological interpretability. The human brain exhibits a remarkable modular structure in spontaneous brain functional networks, with each module comprised of functionally interconnected brain regions-of-interest (ROIs)...

OBJECTIVE: Hemodialysis patients usually receive an arteriovenous fistula (AVF) in the arm as vascular access conduit to allow dialysis 2-3 times a week. This AVF introduces the high flow necessary for dialysis, but over time the ever-present supraphysiological flow is the leading cause of complications. This study aims to develop an implantable device able to non-invasively remove the high flow outside dialysis sessions. METHODS: The developed prototype features a magnetic ring allowing external coupling and torque transmission to non-invasively control an AVF valve...

OBJECTIVE: Muscle atrophy reduces the quality of life and increases morbidity and mortality from other diseases. The development of non-invasive muscle atrophy evaluation method is of great practical value. The lack of gold standard for pathological grading usually allows only the duration of weightlessness as a criterion for the degree of atrophy. However, the adaptive reductive remodeling of muscle physiology and structure shows a trend of nonlinear changes in time. Consequently, using weightlessness time as a benchmark for the degree of atrophy is inaccurate...

Low-frequency ultrasound can permeate human thorax and can be applied in functional imaging of the respiratory system. In this study, we investigated the transmission of low-frequency ultrasound through the human thorax and propose a waveform matching method to track the changes in the transmission signal during subject's respiration. The method's effectiveness is validated through experiments involving ten human subjects. Furthermore, the experimental findings indicate that the traveltime of the first-arrival signal remains consistent throughout the respiratory cycle...

OBJECTIVE: The reconstruction of an input based on a sparse combination of signals, known as sparse coding, has found widespread use in signal processing. In this work, the combination of sparse coding with Kalman filtering is explored and its potential is shown on two use-cases. METHODS: This work extends the Iterative Shrinkage and Thresholding Algorithm with a Kalman filter in the sparse domain. The resulting method may be implemented as a deep unfolded neural network and may be applied to any signal which has a sparse representation and a known or assumed relation between consecutive measurements...

OBJECTIVE: electromyogram (EMG)-driven musculoskeletal models have been widely used to investigate human movements while existing EMG-driven models commonly neglect regional heterogeneity in anatomy and activation within a skeletal muscle. To consider neuromuscular compartment anatomy and activation, a subject- and compartment-specific EMG-driven model was developed for isometric plantarflexion moment prediction. METHODS: the model was hill-type consisting of gastrocnemius medialis, gastrocnemius lateralis, and soleus around the ankle joint, and each muscle was discretised into four compartments...

The role and importance of mechanical properties of cells and tissues in pathophysiological processes have widely been acknowledged. However, current elastography techniques most based on transverse elastic waves, diminish the translation of wave speed into elastic modulus due to its limited wave propagation direction. Here, we propose phase-domain photoacoustic mechanical imaging (PD-PAMI), leveraging the initial time and phase response characteristics of an omnidirectional photoacoustic elastic wave to quantitatively extract elastic and viscous moduli...