Using Peripheral Venous Pressure Waveforms to Predict Key Hemodynamic Parameters

Analysis of peripheral venous pressure (PVP) waveforms is a novel method of monitoring intravascular volume. Two cohorts were used to study the hemodynamics change of the body state and its influence on the PVP using (1) dehydration setting with infants suffering from pyloric stenosis and (2) hemorrhage setting during a craniosynostosis elective surgery. The goal of this research is to develop a minimally invasive method of analyzing the PVP waveforms and find correlations with volume loss. Twenty-three pyloric stenosis patients PVP were acquired at five stages and were divided into euvolemic, normal fluid volume, and hypovolemic, significant fluid loss. Seven craniosynostosis patients were enrolled and the PVP was acquired at the intervention to explore if the isoflurane dosage influences the PVP. A multivariate analysis of variances (MANOVA) was used to test if the PVP was influenced by the volume change and the anesthetic drugs effect. Prediction algorithms based on Fast Fourier Transform were utilized at the two cohort patients analyses to classify an arbitrary PVP into its correct classification. Our research found that PVP signal is influenced by the different hemodynamics states of the body. Based on MANOVA outcomes, we built prediction systems and they were able to categorize an arbitrary PVP signal into its correct classification. The k-nearest neighbor (k-NN) model correctly predicted 77% of the data in the euvolemic and hypovolemic groups. The k-NN models of the anesthetic drugs were able to correctly predict correctly at least 85% of the preoperative and intraoperative signals of the pyloric stenosis patients and the different isoflurane dosages of the craniosynostosis patients. Analyzing the PVP signal is a promising tool for measuring the dehydration level in acute settings. Our results imply that the subsequent changes in vascular resistance due to inhaled and infused anesthetics are reflected in the peripheral veins. A technology that would accurately assess the volume status of a patient to guide triage and treatment would be a significant improvement in various care settings. This minimally invasive technology utilizes a standard peripheral intravenous line and a commercial pressure-monitoring transducer, which exist today and requires no new clinical skills

A Novel Real-Time Non-invasive Hemoglobin Level Detection Using Video Images from Smartphone Camera

Hemoglobin level detection is necessary for evaluating health condition in the human. In the laboratory setting, it is detected by shining light through a small volume of blood and using a colorimetric electronic particle counting algorithm. This invasive process requires time, blood specimens, laboratory equipment, and facilities. There are also many studies on non-invasive hemoglobin level detection. Existing solutions are expensive and require buying additional devices. In this paper, we present a smartphone-based non-invasive hemoglobin detection method. It uses the video images collected from the fingertip of a person. We hypothesized that there is a significant relation between the fingertip mini-video images and the hemoglobin level by laboratory gold standard. We also discussed other non-invasive methods and compared with our model. Finally, we described our findings and discussed future works

Focal Spot, Winter 2009/2010

https://digitalcommons.wustl.edu/focal_spot_archives/1113/thumbnail.jp

Ensemble Of Multiple Matchers For Finger Vein Recognition

Biometrics recognition system is important in identification and verification of an individual. Recently, the research on finger vein verification becomes popular due to the benefits such as hygiene and cannot be duplicated. Finger vein verification is also able to overcome community needs and health problems. Various feature extraction methods were proposed by researchers, such as repeated line tracking, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Band-Limited Phase-Only Correlation (BLPOC. These methods are considered as hand-crafted feature extraction method. Learned feature extraction has not been used in finger vein verification yet. Hence, spatial pyramid pooling method is developed as learned feature extraction for finger vein verification. BLPOC is used as hand-crafted feature extraction which the scores obtained will be then fused together with the scores obtained from spatial pyramid pooling by using Support Vector Machine (SVM). The database used is FV-USM based on 123 individuals with 4 fingers each. In the result obtained, spatial pyramid pooling shows the highest EER, 4.368%, followed by BLPOC, 2.36% and the lowest is SVM, 0.1348%. As conclusion, fusion of learned feature and hand-crafted feature shows the best performance as compared to single feature matching

Real-Time Superficial Vein Imaging System for Observing Abnormalities on Vascular Structures

Circulatory system abnormalities might be an indicator of diseases or tissue damage. Early detection of vascular abnormalities might have an important role during treatment and also raise the patient's awarenes. Current detection methods for vascular imaging are high-cost, invasive, and mostly radiation-based. In this study, a low-cost and portable microcomputer-based tool has been developed as a near-infrared (NIR) superficial vascular imaging device. The device uses NIR light-emitting diode (LED) light at 850 nm along with other electronic and optical components. It operates as a non-contact and safe infrared (IR) imaging method in real-time. Image and video analysis are carried out using OpenCV (Open-Source Computer Vision), a library of programming functions mainly used in computer vision. Various tests were carried out to optimize the imaging system and set up a suitable external environment. To test the performance of the device, the images taken from three diabetic volunteers, who are expected to have abnormalities in the vascular structure due to the possibility of deformation caused by high glucose levels in the blood, were compared with the images taken from two non-diabetic volunteers. As a result, tortuosity was observed successfully in the superficial vascular structures, where the results need to be interpreted by the medical experts in the field to understand the underlying reasons. Although this study is an engineering study and does not have an intention to diagnose any diseases, the developed system here might assist healthcare personnel in early diagnosis and treatment follow-up for vascular structures and may enable further opportunities

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book

RESULTS AND CHALLENGES OF ARTIFICIAL NEURAL NETWORKS USED FOR DECISION-MAKING AND CONTROL IN MEDICAL APPLICATIONS

The aim of this paper is to present several approaches by which technology can assist medical decision-making. This is an essential, but also a difficult activity, which implies a large number of medical and technical aspects. But, more important, it involves humans: on the one hand, the patient, who has a medical problem and who requires the best solution; on the other hand, the physician, who should be able to provide, in any circumstances, a decision or a prediction regarding the current and the future medical status of the patient. The technology, in general, and particularly the Artificial Intelligence (AI) tools could help both of them, and it is assisted by appropriate theory regarding modeling tools. One of the most powerful mechanisms that can be used in this field is the Artificial Neural Networks (ANNs). This paper presents some of the results obtained by the Process Control group of the Politehnica University Timisoara, Romania, in the field of ANNs applied to modeling, prediction and decision-making related to medical systems. An Iterative Learning Control-based approach to batch training a feedforward ANN architecture is given. The paper includes authors’ concerns in this domain and emphasizes that these intelligent models, even if they are artificial, are able to make decisions, being useful tools for prevention, early detection and personalized healthcare

Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

USSR Space Life Sciences Digest, issue 32

This is the thirty-second issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 34 journal or conference papers published in Russian and of 4 Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. The abstracts in this issue have been identified as relevant to 18 areas of space biology and medicine. These areas include: adaptation, aviation medicine, biological rhythms, biospherics, cardiovascular and respiratory systems, developmental biology, exobiology, habitability and environmental effects, human performance, hematology, mathematical models, metabolism, microbiology, musculoskeletal system, neurophysiology, operational medicine, and reproductive system