Objective: Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms, measuring the maximal flow velocity is challenging. In this work, we propose a

Cardiac electrophysiology procedures present the physician with a wealth of 3D information, typically presented on fixed 2D monitors. New developments in wearable mixed reality displays offer the potential to simplify and enhance 3D visualization while providing hands-free, dynamic control of devices within the procedure room. Objective: This work aims to evaluate the performance and quality of a mixed

Background: Stroke is one of the leading causes of disability with ~80% of post-stroke survivors suffering from gait-related deficits. Conventional gait rehabilitation settings are labor-intensive and need rigorous involvement of clinicians (who use their expertise to decide the dosage of exercise intensity based on patient’s capability). This demands a technology-assisted individualized exercise platform

Novel myoelectric control strategies may yield more robust, capable prostheses which improve quality of life for those affected by upper-limb loss; however, the development and translation of such strategies from an experimental setting towards daily use by persons with limb loss is a slow and costly process. Since prosthesis functionality is highly dependent on the physical interface between the user’s

Bladder cancer is the 9th most common cancer worldwide. Diagnosing bladder cancer typically involves highly invasive cystoscopy, with followup monitored using uteroscopy. Molecular methods have been developed as an adjunct to this, but tend to be expensive or require expert operator input. Here we present a study of the use of dielectrophoresis (DEP) of voided cells from eight cancer-presenting patients

Oxygen concentration in living organisms is one of the important vital indicators in emergency care and bedside medical settings. However, the oximetry method has limitations: the measurement site is limited to the tissue containing blood and the absolute value of oxygen concentration cannot be measured. To overcome these limitations, in this work, we develop a new oxygen sensor that can directly measure

As a senile chronic, progressive and currently incurable disease, dementia has an enormous impact on society and life quality of the elderly. The development of teleoperation technology has changed the traditional way of care delivery and brought a variety of novel applications for dementia care. In this paper, a telerobotic system is presented which gives the caregivers the capability of assisting

Background: Digital radiography devices are still the gold standard for diagnosis or therapy guidance in medicine. Despite the similarities between all direct digital x-ray systems, researchers and new companies face significant challenges during the development phase of innovative x-ray devices; each component is manufactured independently, guidance towards device integration from manufacturers is

Attenuation imaging is a novel, ultrasound-based technique to objectively detect and quantify liver steatosis. In this study, we evaluated the performance and inter-observer variability of attenuation imaging and compared it to a known quantification method of liver fat, the hepatorenal index (HRI). Two observers measured attenuation coefficients (AC) in an attenuation phantom, 20 healthy volunteers

Pulse Arrival Time (PAT) derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) for cuff-less Blood Pressure (BP) measurement has been a contemporary and widely accepted technique. However, the features extracted for it are conventionally from an isolated pulse of ECG and PPG signals. As a result, the estimated BP is intermittent. Objective: This paper presents feature extraction from each

Goal: The purpose of this study was to identify clinically relevant patterns of glaucomatous vision loss through convex representation to predict glaucoma several years prior to disease onset. Methods: We developed a deep archetypal analysis to identify patterns of glaucomatous vision loss, and then projected visual fields over the identified patterns. Projections provided a representation that was

Accurate iFR calculation can provide important clinical information for intracoronary functional assessment without administration of adenosine, which needs to locate object points in the pressure waveforms: peak, the dichrotic notch and the pressure nadir at the end of diastole. We propose a DFENet that is capable of locating object points to calculate iFR accurately. We first design a SFRA into DFENet

Technology is advancing at an extraordinary rate. Continuous flows of novel data are being generated with the potential to revolutionize how we better identify, treat, manage, and prevent disease across therapeutic areas. However, lack of security of confidence in digital health technologies is hampering adoption, particularly for biometric monitoring technologies (BioMeTs) where frontline healthcare

Dementia is a severe disease threatening ageing societies, which not only causes great harm to patients both physically and psychologically but also places a heavy burden on patients’ families. Medications have been used for the treatment of dementia but with little success. However, serious games, as a new form of dementia therapy, stand out from various therapeutic methods and pave the way for dementia

Fall risk is high for older adults with dementia. Gait impairment contributes to increased fall risk, and gait changes are common in people with dementia, although the reliable assessment of gait is challenging in this population. This study aimed to develop an automated approach to performing gait assessments based on gait data that is collected frequently and unobtrusively, and analysed using computer

Background: Various voice assessment tools, such as questionnaires and aerodynamic voice characteristics, can be used to assess vocal function of individuals. However, not much is known about the best combinations of these parameters in identification of functional dysphonia in clinical settings. Methods: This study investigated six scores from clinically commonly used questionnaires and seven acoustic

Objective: The presence of right ventricular hypertrophy (RVH) accounts for approximately 5-10% in young adults. The sensitivity estimated by commonly used 12-lead electrocardiographic (ECG) criteria for identifying the presence of RVH is under 20% in the general population. The aim of this study is to develop a 12-lead ECG system with the related information of age, body height and body weight via

Objectives: Worldwide efforts to protect front line providers performing endotracheal intubation during the COVID-19 pandemic have led to innovative devices. Authors evaluated the aerosol containment effectiveness of a novel intubation aerosol containment system (IACS) compared with a recently promoted intubation box and no protective barrier. Methods: In a simulation center at the authors’ university

Background: EEG-driven research is paramount in cognitive-neuropsychological studies, as it provides a non-invasive window to the underlying neural mechanisms of cognition and behavior. A myriad collection of software and hardware frameworks has been developed to alleviate some of the technical barriers involved in EEG-driven research. Methods: we propose an integrated development environment which

Multiple studies have suggested that some associations exist between occlusal factors and postural alterations. OBJECTIVES This study aimed to evaluate the effectiveness of a vibrotactile posture trainer device, comprised a wearable device containing an accelerometer sensor to measure the angle of the neck flexion (input) and provided real-time vibrotactile biofeedback (output) for postural balance

Objective: This study investigates the estimation of three dimensional (3D) left ventricular (LV) motion using the fusion of different two dimensional (2D) cine magnetic resonance (CMR) sequences acquired during routine imaging sessions. Although standard clinical cine CMR data is inherently 2D, the actual underlying LV dynamics lies in 3D space and cannot be captured entirely using single 2D CMR image

The prevalence of physiological and pathological left ventricular hypertrophy (LVH) among young adults is about 5%. A use of electrocardiographic (ECG) voltage criteria and machine learning for the ECG parameters to identify the presence of LVH is estimated only 20-30% in the general population. The aim of this study is to develop an ECG system with anthropometric data using machine learning to increase

OBJECTIVE This study intends to develop an accurate, real-time tumor tracking algorithm for the automated radiation therapy for cancer treatment using Graphics Processing Unit (GPU) computing. Although a previous moving mesh based tumor tracking approach has been shown to be successful in delineating the tumor regions from a sequence of magnetic resonance image, the algorithm is computationally intensive

Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases, and the number of AD patients has increased year after year with the global aging trend. The onset of AD has a long preclinical stage. If doctors can make an initial diagnosis in the mild cognitive impairment (MCI) stage, it is possible to identify and screen those at a high-risk of developing full-blown AD,

A kind of wearable exoskeleton soft rehabilitation glove is proposed for the dementia in Parkinson's disease (PD) patients with loss of hand function, limited range of motion, and insufficient finger muscle strength to carry out rehabilitation exercise training in a passive or auxiliary way. A novel soft joint structure based on composite fabric material is introduced for the design of the soft glove

BACKGROUND Cardiovascular diseases (CVD) are the leading cause of death globally. Electrocardiogram (ECG) analysis can provide thoroughly assessment for different CVDs efficiently. We propose a multi-task group bidirectional long short-term memory (MTGBi-LSTM) framework to intelligent recognize multiple CVDs based on multi-lead ECG signals. METHODS This model employs a Group Bi-LSTM (GBi-LSTM) and

Objective: This work aims at providing novel endovascular instrumentation to overcome current technical limitations of in situ endograft fenestration including challenges in targeting the fenestration site under fluoroscopic control and supplying mechanical support during endograft perforation. Technology: Novel electromagnetically trackable instruments were developed to facilitate the navigation of

Heart rate variability (HRV) measurements are performed using a tilt-table (TT) to diagnose dysfunctionality in the autonomic nervous system (ANS) and the cardiovascular system. To maintain homeostasis, the ANS adapts to body position changes through alterations in sympathetic and parasympathetic responses that can be quantified by extracting time-domain and frequency-domain parameters from the heart

Introduction: The effects of ageing on bone can be mitigated with different types of physical training, such as power training. However, stimuli that combine increasing external and internal loads concomitantly may improve bone quality. The goal of this study was to assess the efficacy of a combined power and plyometric training on lumbar spine and distal tibia microstructure and function. Methods:

This paper presents an evaluation technique for higher-level instrumental activities of daily living (HL-IADLs), which are defined as relatively complicated modern daily activities to perform independently, using micro-Doppler radar (MDR) signatures of sit-to-stand-to-sit (STSTS) movements. Because HL-IADLs are useful for evaluating the degree of disability and cognitive decline in daily life, this

The clinical assessment technology such as remote monitoring of rehabilitation progress for lower limb related ailments rely on the automatic evaluation of movement performed along with an estimation of joint angle information. In this paper, we introduce a transfer-learning based Long-term Recurrent Convolution Network (LRCN) named as `MyoNet' for the classification of lower limb movements, along

OBJECTIVE This paper proposes a multiclass deep learning method for the classification of dementia using an informant-based questionnaire. METHODS A deep neural network classification model based on Keras framework is proposed in this paper. To evaluate the advantages of our proposed method, we compared the performance of our model with industry-standard machine learning approaches. We enrolled 6,701

Background: Closed-loop neuromodulation based on bladder pressure is an effective therapy for lower urinary tract dysfunction. The catheter-based cystometry normally used for bladder pressure measurement is not conducive to patient health because it will bring great mental stress to the patient and increase the risk of infection. Method: This paper designs and implements an implantable wireless and

Pelvic floor disorders are caused by weakening or damage to the tissues lining the bottom of the abdominal cavity. These disorders affect nearly 1 in every 4 women in the United States and symptoms that drastically diminish a patient's quality of life. Vaginal closure force is a good measure of pelvic health, but current vaginal dynamometers were not designed for the rigors of hospital reprocessing

A new approach is presented for localizing the Subthalamic Nucleus (STN) during Deep Brain Stimulation (DBS) surgery based on microelectrode recordings (MERs). DBS is an accepted treatment for individuals living with Parkinson's Disease (PD). This surgery involves implantation of a permanent electrode inside the STN to deliver electrical current. Since the STN is a very small region inside the brain

Background Wearable wrist-monitors offer an unobtrusive way to acquire heart rate data in an efficient manner. Previous work in this field has focused on studying healthy subjects during exercise but has yet to assess the efficacy of these devices in patients suffering from common cardiac arrhythmias such as atrial fibrillation. Objective The objective of this pilot study was to assess the accuracy

This study proposes a new assistive device for the blind that uses more than one-dimensional data to draw objects. The study aims to convert three-dimensional (3-D) spatial information into sound information using 6-axis and ultrasonic sensors, and to draw a 3-D depiction of the space ahead for the user. Fourteen participants were involved in testing, wherein 4 were visually impaired. Moreover, the

OBJECTIVE Autonomic Dysreflexia (AD) is a potentially life-threatening syndrome which occurs in individuals with higher level spinal cord injuries (SCI). AD is caused by triggers which can lead to rapid escalation of pathophysiological responses and if the trigger is not removed, AD can be fatal. There is currently no objective, non-invasive and accurate monitoring system available to automatically

Point-of-care (POC) testing has demonstrated great transformative potential in personalized medicine. In particular, patients undergoing transplantation require POC testing to ensure appropriate serum immunosuppressant levels so as to maintain adequate graft function and survival. However, no suitable POC device for monitoring immunosuppressant levels is currently available. Exploiting the latest advances

Background: Computer-aided disease detection schemes from wireless capsule endoscopy (WCE) videos have received great attention by the researchers for reducing physicians' burden due to the time-consuming and risky manual review process. While single disease classification schemes are greatly dealt by the researchers in the past, developing a unified scheme which is capable of detecting multiple gastrointestinal

Objective: investigation of the extra-low-frequency (ELF) stimulation effect on blood-cell proteins, that causes variation in its electrostatic-state. A hypothesis that this results in the conformational change in the blood-cell proteins which could enhance immune activity is explored. Since HIV-1 and host-cell engage through charge-charge interactions, an electrical-pulse may cause charge redistribution

Lung cancer is a major cause for cancer-related deaths. The detection of pulmonary cancer in the early stages can highly increase survival rate. Manual delineation of lung nodules by radiologists is a tedious task. We developed a novel computer-aided decision support system for lung nodule detection based on a 3D Deep Convolutional Neural Network (3DDCNN) for assisting the radiologists. Our decision

Cervical cancer disproportionally affects women in low- and middle-income countries, in part due to the difficulty of implementing existing cervical cancer screening and diagnostic technologies in low-resource settings. Single-board computers offer a low-cost alternative to provide computational support for automated point-of-care technologies. Here we demonstrate two new devices for cervical cancer

OBJECTIVE The Internet of Things provide solutions for many societal challenges including the use of unmanned aerial vehicles to assist in emergency situations that are out of immediate reach for traditional emergency services. Out of hospital cardiac arrest (OHCA) can result in death with less than 50% of victims receiving the necessary emergency care on time. The aim of this study is to link real

Objective: Currently available treatments for kinetic tremor can cause intolerable side effects or be highly invasive and expensive. Even though several studies have shown the positive effects of external feedback (i.e., electrical stimulation) for suppressing tremor, such approaches have not been fully integrated into wearable real-time feedback systems. Method: We have developed a wireless wearable

BACKGROUND Alzheimer's disease (AD) is a common neurodegenerative disease occurring in the elderly population. The effective and accurate classification of AD symptoms by using functional magnetic resonance imaging (fMRI) has a great significance for the clinical diagnosis and prediction of AD patients. METHODS Therefore, this paper proposes a new method for identifying AD patients from healthy subjects

OBJECTIVE This work presents a device for non-invasive wound parameters assessment, designed to overcome the drawbacks of traditional methods, which are mostly rough, inaccurate, and painful for the patient. The device estimates the morphological parameters of the wound and provides augmented reality (AR) visual feedback on the wound healing status by projecting the wound border acquired during the

Keyword search in a cluttered environment is difficult in general, and even more challenging for people with low vision. While magnification can help in reading for low vision people, it does not facilitate efficient visual search due to the constriction of the field of view. The motivating observation for this study is that, in a large number of visual search tasks, people know what are they looking

In this paper, a dual-biomarker-based neural sensing and conditioning device is proposed for closing the feedback loop in deep brain stimulation devices. The device explores both local field potentials (LFPs) and action potentials (APs) as measured biomarkers. It includes two channels, each having four main parts: (1) a pre-amplifier with built-in low-pass filter, (2) a ground shifting circuit, (3)

Sex plays an important role in the normal cardiovascular system function including resting heart rate and arterial blood pressure. In addition, it has been reported that men and women are at different levels of risk for cardiovascular diseases. The aim of this study was to evaluate and compare the temporal and morphological features of both finger and toe photoplethysmography (PPG), and anthropometric

Noncancerous breast tissue and cancerous breast tissue have different elastic properties. In particular, cancerous breast tumors are stiff when compared to the noncancerous surrounding tissue. This difference in elasticity can be used as a means for detection through the method of elastographic tomosynthesis by means of physical modulation. This paper deals with a method to visualize elasticity of

BACKGROUND Functional magnetic resonance imaging (fMRI) provides non-invasive measures of neuronal activity using an endogenous Blood Oxygenation-Level Dependent (BOLD) contrast. This article introduces a nonlinear dimensionality reduction (Locally Linear Embedding) to extract informative measures of the underlying neuronal activity from BOLD time-series. The method is validated using the Leave-On

OBJECTIVE To investigate the feasibility of improving the performance of an EEG-based multistate classifier (MSC) previously proposed by our group. RESULTS Using the random forest (RF) classifiers on the previously reported dataset of patients, but with three improvements to classification logic, the specificity of our alarm algorithm improves from 82.4% to 92.0%, and sensitivity from 87.9% to 95.2%

Norepinephrine (NE), an endogenous catecholamine, is a mainstay treatment for septic shock, which is a life-threatening manifestation of severe infection. NE counteracts the loss in blood pressure associated with septic shock. However, an NE infusion that is too low fails to counteract the blood pressure drop, and an NE infusion that is too high can cause a hypertensive crisis and heart attack. Ideally

Stroke patients are monitored hourly by physicians and nurses in an attempt to better understand their physical state. To quantify the patients' level of mobility, hourly movement (i.e. motor) assessment scores are performed, which can be taxing and time-consuming for nurses and physicians. In this paper, we attempt to find a correlation between patient motor scores and continuous accelerometer data

Excessive magnitudes of compressive stress exerted on gastrointestinal tissues can lead to pathological scar tissue or adhesion formation, bleeding, inflammation or even death from bowel perforation and sepsis. It is currently unknown however, at exactly what magnitude of compressive stress that these pathologies occur. A novel simple compressive device was engineered to provide an objective means

Burn is one of the serious public health problems. Usually, burn diagnoses are based on expert medical and clinical experience and it is necessary to have a medical or clinical expert to conduct an examination in restorative clinics or at emergency rooms in hospitals. But sometimes a patient may have a burn where there is no specialized facility available, and in such a case a computerized automatic

Parkinsonian gait is a defining feature of shaking palsy (SP) and it has one of the worse impacts on human healthy life than other SP symptoms. The objective of this work is to propose a Parkinsonian gait detection system based on an S-band perception technique to classify abnormal gait and normal walking. Due to the differences in the Gaits of Parkinson's patients compared with healthy persons, the

This paper implements logistic regression models (LRMs) and feature selection for creating a predictive model for recovery form hemorrhagic shock (HS) with resuscitation using blood in the multiple experimental rat animal protocols. A total of 61 animals were studied across multiple HS experiments, which encompassed two different HS protocols and two resuscitation protocols using blood stored for short

Glaucoma, the silent thief of vision, is mostly caused by the gradual increase of pressure in the eye which is known as intraocular pressure (IOP). An effective way to prevent the rise in eye pressure is by early detection. Prior computer vision-based work regarding IOP relies on fundus images of the optic nerves. This paper provides a novel vision-based framework to help in the initial IOP screening