IEEE Reviews in Biomedical Engineering

Body compression through a garment or inflatable pneumatic mechanism has various applications in aesthetic, athletic, robotics, haptics, astronautics, and especially medical fields for treatment of various disorders such as varicose veins, lymphedema, deep vein thrombosis, and orthostatic intolerance. Traditionally, compression has been done through under-sized (e.g. elastic) or size-adjustable (e.g. inflatable) compression garments. Such systems are designed to apply substantially uniform pressure on the body...

The tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerably, with emphasis on the handling of time-varying conditions and confounding factors. Time-frequency analysis holds since long an important position in HRV analysis, however, this technique cannot alone handle a mean heart rate or a respiratory frequency which vary over time. Overlapping frequency bands represents another critical condition which needs to be dealt with to produce accurate spectral measurements...

Confronted with the COVID-19 health crisis, the year 2020 represented a turning point for the entire world. It paved the way for health-care systems to reaffirm their foundations by using different technologies such as sensors, wearables, mobile applications, drones, robots, Artificial Intelligence (AI), Machine Learning (ML) and the Internet of Things (IoT). A lot of domains have been renovated such as diagnosis, treatment, and monitoring, as well as previously unprecedented domains such as contact tracing...

Neuron-on-chip (NoC) systems-microfluidic devices in which neurons are cultured-have become a promising alternative to replace or minimize the use of animal models and have greatly facilitated in vitro research. Here, we review and discuss current developments in neuron-on-chip platforms, with a particular emphasis on existing biological models, culturing techniques, biomaterials, and topologies. We also discuss how the architecture, flow, and gradients affect neuronal growth, differentiation, and development...

At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or surveillance. However, AI tools have not yet been widely successful. One of the key reason is the COVID-19 pandemic has demanded faster real-time development of AI-driven clinical and health support tools, including rapid data collection, algorithm development, validation, and deployment. However, there was not enough time for proper data quality control...

Cardiovascular disease (CVD) is the leading cause of mortality worldwide and its incidence is rising due to an aging population. The development and progression of CVD is directly linked to adverse vascular hemodynamics and biomechanics, whose in-vivo measurement remains challenging but can be simulated numerically and experimentally. The ability to evaluate these parameters in patient-specific CVD cases is crucial to better predict future disease progression, risk of adverse events, and treatment efficacy...

Non-contact vital sign monitoring has been an important research topic recently due to the ability to monitor patients for an extended period especially during sleep without requiring uncomfortable attachments. Radar is a popular sensor for vital sign monitoring research. Various algorithms have been proposed for estimating respiration rate and heart rate from the radar data. But many algorithms rely on Fast Fourier Transform (FFT) to convert time domain signal to the frequency domain and estimate vital signs, despite FFT having limitation of frequency resolution being inverse of the time interval of data sample...

This century has introduced very deadly, dangerous, and infectious diseases to humankind such as the influenza virus, Ebola virus, Zika virus, and the most infectious SARS-CoV-2 commonly known as COVID-19 and have caused epidemics and pandemics across the globe. For some of these diseases, proper medications, and vaccinations are missing and the early detection of these viruses will be critical to saving the patients. And even the vaccines are available for COVID-19, the new variants of COVID-19 such as Delta, and Omicron are spreading at large...

Ulcers and chronic wounds are a large and expensive problem, costing billions of pounds a year and affecting millions of people. Electrical stimulation has been known to have a positive effect on wound healing since the 1960 s and this has been confirmed in numerous studies, reducing the time to heal, and the incidence of adverse events such as infections. However, because each study used different parameters for the treatment, inclusion criteria and metrics for quantifying the success, it is currently hard to combine them statistically and gain a true picture of its efficacy...

Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural language processing (NLP) plays a key role in smart healthcare due to its capability of analysing and understanding human language. In this work, we review existing studies that concern NLP for smart healthcare from the perspectives of technique and application. We first elaborate on different NLP approaches and the NLP pipeline for smart healthcare from the technical point of view...

Soft robotics has opened a unique path to flexibility and environmental adaptability, learning from nature and reproducing biological behaviors. Nature implies answers for how to apply robots to real life. To find out how we learn from creatures to design and apply soft robots, in this Review, we propose a classification method to summarize soft robots based on different functions of biological systems: self-growing, self-healing, self-responsive, and self-circulatory. The bio-function based classification logic is presented to explain why we learn from creatures...

Movement sonification is emerging as a useful tool for rehabilitation, with increasing evidence in support of its use. To create such a system requires component considerations outside of typical sonification design choices, such as the dimension of movement to sonify, section of anatomy to track, and methodology of motion capture. This review takes this emerging and highly diverse area of literature and keyword-code existing real-time movement sonification systems, to analyze and highlight current trends in these design choices, as such providing an overview of existing systems...

Target 3.4 of the third Sustainable Development Goal (SDG) of the United Nations (UN) General Assembly proposes to reduce premature mortality from non-communicable diseases (NCDs) by one-third. Epidemiological data presented by the World Health Organization (WHO) in 2016 show that out of a total of 57 million deaths worldwide, approximately 41 million deaths occurred due to NCDs, with 78% of such deaths occurring in low-and-middle-income countries (LMICs). The majority of investigations on NCDs agree that the leading risk factor for mortality worldwide is hypertension...

Despite the myriad peer-reviewed papers demonstrating novel Artificial Intelligence (AI)-based solutions to COVID-19 challenges during the pandemic, few have made a significant clinical impact, especially in diagnosis and disease precision staging. One major cause for such low impact is the lack of model transparency, significantly limiting the AI adoption in real clinical practice. To solve this problem, AI models need to be explained to users. Thus, we have conducted a comprehensive study of Explainable Artificial Intelligence (XAI) using PRISMA technology...

Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain disease and monitor treatment as non-invasive imaging technology. MRI produces three-dimensional images that help neurologists to identify anomalies from brain images precisely. However, this is a time-consuming and labor-intensive process. The improvement in machine learning and efficient computation provides a computer-aid solution to analyze MRI images and identify the abnormality quickly and accurately. Image segmentation has become a hot and research-oriented area in the medical image analysis community...

Surgery is a high-risk procedure of therapy and is associated to post trauma complications of longer hospital stay, estimated blood loss and long duration of surgeries. Reports have suggested that over 2.5% patients die during and post operation. This paper is aimed at systematic review of previous research on artificial intelligence (AI) in surgery, analyzing their results with suitable software to validate their research by obtaining same or contrary results. Six published research articles have been reviewed across three continents...

Breast cancer is a leading cause of mortality among women. The patient's survival rate is uncertain due to the limitations in the accuracy of diagnosis and effective monitoring during cancer treatment. The key to efficaciously controlling cancer on a larger scale is effective diagnosis at an early stage of cancer by distinguishing the vital signatures of the diseased from the normal breast tissue. The breast tissue is a heterogeneous turbid media that exhibits multifaceted bulk tissue properties. Various sensing modalities can yield distinct tissue behavior for cancer and adjacent normal tissues, serving as a basis for cancer diagnosis...

Modifying neural activity is a substantial goal in neuroscience that facilitates the understanding of brain functions and the development of medical therapies. Neurobiological models play an essential role, contributing to the understanding of the underlying brain dynamics. In this context, control systems represent a fundamental tool to provide a correct articulation between model stimulus (system inputs) and outcomes (system outputs). However, throughout the literature there is a lack of discussions on neurobiological models, from the formal control perspective...

Radiofrequency ablation (RFA) combined with saline infusion into tissue is a promising technique to ablate larger tumours. Nevertheless, the application of saline-infused RFA remains at clinical trials due to the contradictory findings as a result of the inconsistencies in experimental procedures. These inconsistencies not only magnify the number of factors to consider during the treatment, but also obscure the understanding of the role of saline in enlarging the coagulation zone. Consequently, this can result in major complications, which includes unwanted thermal damages to adjacent tissues and also incomplete ablation of the tumour...

Fetal phonocardiography (fPCG) is receiving attention as it is a promising method for continuous fetal monitoring due to its non-invasive and passive nature. However, it suffers from the interference from various sources, overlapping the desired signal in the time and frequency domains. This paper introduces the state-of-the-art methods used for fPCG signal extraction and processing, as well as means of detection and classification of various features defining fetal health state. It also provides an extensive summary of remaining challenges, along with the practical insights and suggestions for the future research directions...