Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest

The automatic detection of pulse during out-of-hospital cardiac arrest (OHCA) is necessary for the early recognition of the arrest and the detection of return of spontaneous circulation (end of the arrest). The only signal available in every single defibrillator and valid for the detection of pulse is the electrocardiogram (ECG). In this study we propose two deep neural network (DNN) architectures to detect pulse using short ECG segments (5 s), i.e., to classify the rhythm into pulseless electrical activity (PEA) or pulse-generating rhythm (PR). A total of 3914 5-s ECG segments, 2372 PR and 1542 PEA, were extracted from 279 OHCA episodes. Data were partitioned patient-wise into training (80%) and test (20%) sets. The first DNN architecture was a fully convolutional neural network, and the second architecture added a recurrent layer to learn temporal dependencies. Both DNN architectures were tuned using Bayesian optimization, and the results for the test set were compared to state-of-the art PR/PEA discrimination algorithms based on machine learning and hand crafted features. The PR/PEA classifiers were evaluated in terms of sensitivity (Se) for PR, specificity (Sp) for PEA, and the balanced accuracy (BAC), the average of Se and Sp. The Se/Sp/BAC of the DNN architectures were 94.1%/92.9%/93.5% for the first one, and 95.5%/91.6%/93.5% for the second one. Both architectures improved the performance of state of the art methods by more than 1.5 points in BAC.This work was supported by: The Spanish Ministerio de Economía y Competitividad, TEC2015-64678-R, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), UPV/EHU via GIU17/031 and the Basque Government through the grant PRE_2018_2_0260

Microwave imaging techniques for biomedical applications

Microwaves have been considered for medical applications involving the detection of organ movements and changes in tissue water content. More particularly cardiopulmonary interrogation via microwaves has resulted in various sensors monitoring ventricular volume change or movement, arterial wall motion, respiratory movements, pulmonary oedema, etc. In all these applications, microwave sensors perform local measurements and need to be displaced for obtaining an image reproducing the spatial variations of a given quantity. Recently, advances in the area of inverse scattering theory and microwave technology have made possible the development of microwave imaging and tomographic instruments. This paper provides a review of such equipment developed at Suplec and UPC Barcelona, within the frame of successive French-Spanish PICASSO cooperation programs. It reports the most significant results and gives some perspectives for future developments. Firstly, a brief historical survey is given. Then, both technological and numerical aspects are considered. The results of preliminary pre-clinical assessments and in-lab experiments allow to illustrate the capabilities of the existing equipment, as well as its difficulty in dealing with clinical situations. Finally, some remarks on the expected development of microwave imaging techniques for biomedical applications are given.Peer ReviewedPostprint (published version

Position-Free Vital Sign Monitoring: Measurements and Processing

As traditional electrodes are perturbing for patients in critical cases such as for burn victims or newborn infants, and even to detect life sign under rubble, a contactless monitoring system for the life signs is a necessity. The aim of this chapter is to present a complete process used in detecting cardiopulmonary activities. This includes a microwave Doppler radar system that detects the body wall motion and signal processing techniques in order to extract the heartbeat rate. Measurements are performed at different positions simultaneously with a PC-based electrocardiogram (ECG). For a distance of 1 m between the subject and the antennas, measurements are performed for breathing subject at four positions: front, back, left, and right. Discrete wavelet transform is used to extract the heartbeat signal from the cardiopulmonary signal. The proposed system and signal processing techniques show high accuracy in detecting the cardiopulmonary signals and extracting the heartbeat rate

Physiological Parameter Sensing with Wearable Devices and Non-Contact Dopper Radar.

M.S. Thesis. University of Hawaiʻi at Mānoa 2017

Temperature sensor technology

Human body temperature is of vital importance to the well being of the person and therefore it is routinely monitored to indicate the state of the person’s health. Despite the fact that temperature measurement in humans seems so simple, a wide variety of devices are available to record a temperature from skin, oral or rectal mucosa or the tympanic membrane. The choice of clinical thermometers for health professionals and parents has never been so complicated. This chapter makes an attempt to provide an overview of temperature sensing technologies in medicine. The introductory sections give a brief and general description of temperature and its effect on the human body. A synoptic historical review on the evolution of the thermometer including the clinical thermometer is given in section 3. Section 4 describes the main sensors/transducers used in the development of clinical thermometers, such as thermocouples, thermistors, Resistance Temperature Detectors (RTDs), semiconductor temperature sensors, liquid crystal temperature sensors, and infra-red radiation sensors. These thermometers have been designed and developed for application in various parts of the body such as the rectum, the mouth, the axilla, the esophagus, the bladder, the ear, the temporal artery, the skin, and this will be the content of section 5. It will be almost impossible for this chapter to cover every possible application and evaluation study relating to different thermometers; however an effort is made in section 6 to provide an integrative review of studies comparing selected invasive and non-invasive temperature measurement methods

Cardiovascular instrumentation for spaceflight

The observation mechanisms dealing with pressure, flow, morphology, temperature, etc. are discussed. The approach taken in the performance of this study was to (1) review ground and space-flight data on cardiovascular function, including earlier related ground-based and space-flight animal studies, Mercury, Gemini, Apollo, Skylab, and recent bed-rest studies, (2) review cardiovascular measurement parameters required to assess individual performance and physiological alternations during space flight, (3) perform an instrumentation survey including a literature search as well as personal contact with the applicable investigators, (4) assess instrumentation applicability with respect to the established criteria, and (5) recommend future research and development activity. It is concluded that, for the most part, the required instrumentation technology is available but that mission-peculiar criteria will require modifications to adapt the applicable instrumentation to a space-flight configuration