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Nursing facility residents at high risk for pressure ulcers are turned in bed by staff at regular intervals. In an ongoing large, multi-site randomized clinical trial (RCT) the impacts of 2, 3, and 4 hour turning intervals are being studied on pressure ulcer outcomes. In the RCT, it is necessary to objectively confirm the reported times of assisted turning by certified nurse assistants using activity...
In this paper, a control model is developed to automate the process of navigation in rat-robot-a new type of bio-robot based on BCI(Brain-Computer Interface) technique. Because of the particular difficulties in rat-robot control, we design a novel control model to ‘learn’ and ‘imitate’ the control behavior of human guidance. General Regression Neural Network (GRNN) model is used to analyze the control...
The future challenges to medical and biological engineering, sometimes referred to as biomedical engineering or simply bioengineering, are many. Some of these are identifiable now and others will emerge from time to time as new technologies are introduced and harnessed. There is a fundamental issue regarding “Branding the bio/biomedical engineering degree” that requires a common understanding of what...
A tissue bath system, to be used as an alternative to complex perfusion chambers, was constructed for use in cardiac electrophysiological studies. This system consists of an acrylic chamber to hold circulating physiological medium such as DMEM, suspended in a water bath warmed by a hot plate. Temperature and pH were controlled to mimic physiological conditions. Rat and porcine cardiac tissues, were...
In this paper we discuss an efficient methodology for the characterization of Microelectrode Recordings (MER) obtained during deep brain stimulation surgery for Parkinson's disease using Support Vector Machines and present the results of a preliminary study. The methodology is based in two algorithms: (1) an algorithm extracts multiple computational features from the microelectrode neurophysiology,...
This paper reports the brain activation patterns of five subjects who were abruptly awakened from microsleeps in a simulated automotive driving experiment. By comparing the BOLD signals between behavioral microsleep (BM), abrupt awakening (AA) and post-abrupt awakening (post-AA) stages, we observed that visual area, frontal cortex, limbic lobe manifested more intense activation during the AA stage...
Automatic tracking of movement disorders in patients with Parkinson's disease (PD) is dependent on the ability of machine learning algorithms to resolve the complex and unpredictable characteristics of wearable sensor data. The challenge reflects the variety of movement disorders that fluctuate throughout the day which can be confounded by voluntary activities of daily life. Our approach is the development...
We propose a new methodology to model high-level descriptions of physical activities using multimodal sensor signals (ambulatory electrocardiogram (ECG) and accelerometer signals) obtained by a wearable wireless sensor network. We introduce a two-step strategy where the first step estimates likelihood scores over the low-level descriptions of physical activities such as walking or sitting directly...
We propose a novel approach to calculate the conduction velocity (CV) of the uterine contraction bursts in magnetomyogram (MMG) signals measured using a multichannel SQUID array. For this purpose, we partition the sensor coordinates into four different quadrants and identify the contractile bursts using a previously proposed Hilbert-wavelet transform approach. If contractile burst is identified in...
Large variations in Surface Electromyogram (SEMG) signal across different subjects make the process of automated signal classification as a generalized tool, challenging. In this paper, we propose a domain adaptation methodology that addresses this challenge. In particular we propose a hierarchical sample selection methodology, that selects samples from multiple training subjects, based on their similarity...
The analysis of isometric force may provide early detection of certain types of neuropathology such as Parkinson's disease. Our long term goal is to determine if there are detectable differences between model parameters of healthy verses unhealthy individuals. As a first step toward our long-term goal, we studied 24 healthy young adults ages 18 through 24 years, both male and female. The experiments...
Total cavopulmonary connection (TCPC) is commonly applied for the surgical treatment of congenital heart disease such as single ventricle in pediatric patients. Patients with no ventricle in pulmonary circulation are treated along with Fontan algorithm, in which the systemic venous return is diverted directly to the pulmonary artery without passing through subpulmonary ventricle. In order to promote...
Viability assessment of heart muscle after a myocardial infarction is an important step for diagnosis and therapy planning. It is important to quantify the area of edema because it can differentiate between viable and death myocardial tissues. In this paper an automatic method to quantify cardiac edema is presented. The method is based on a combination of morphological operations and statistical thresholding...
3D functional neuroimaging is used in the diagnosis and management of neurological disorders. The efficient management and analysis of these large imaging datasets has prompted research in the field of content-based image retrieval. In this context, our generalized regional disorder-sensitive-weighting (DSW) scheme gives greater weight to brain regions affected by the diseases than regions that are...
The respiratory rate is a vital sign that can provide important information about the health of a patient, especially that of the respiratory system. The aim of this study is to develop a simple method that can be applied in wearable systems to monitor the respiratory rate automatically and continuously over extended periods of time. In this paper, a novel respiratory rate estimation method is presented...
This paper presents an approach for measuring and monitoring human body joint angles using inertial measurement unit (IMU) sensors. This type of monitoring is beneficial for therapists and physicians because it facilitates remote assessment of patient activities. In our approach, two IMUs are mounted on the upper leg and the lower leg to measure the Euler angles of each segment. The Euler angles are...
Parkinson's disease (PD) is characterized by motor disabilities that can be alleviated reasonably with appropriate medication. However, there is a lack of objective methods for quantifying the efficacy of treatment in PD. We applied here an objective method for quantifying the effects of medication in PD using EMG and acceleration measurements and analysis. In the method, four signal features were...
Tracheal respiratory sound analysis is a simple, inexpensive and non-invasive way to study the pathology of the upper airways. Recently, it has attracted considerable attention for acoustical flow estimation and investigation of obstruction in the upper airways. Obstructive sleep apena (OSA) is characterized by periods of reduction or complete cessation of airflow during sleep. However, the flow-sound...
Although deep brain stimulation (DBS) therapy has been achieved, fine tuning on the operational parameters and the equipment are needed in order to make the stimulation treatment more applicable. Thus, the purpose of this study is to design and produce a deep brain stimulation device for DBS experiments for small animals (e.g. rats). Physical size, durability, cost of device and convenience of operation...
We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral...
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