Noninvasive respiratory monitoring system based on the piezoceramic transducer's pyroelectric effect

Indirect Calorimetry in Spontaneously Breathing, Mechanically Ventilated and Extracorporeally Oxygenated Patients: An Engineering Review

Indirect calorimetry (IC) is considered the gold standard for measuring resting energy expenditure (REE). This review presents an overview of the different techniques to assess REE with special regard to the use of IC in critically ill patients on extracorporeal membrane oxygenation (ECMO), as well as to the sensors used in commercially available indirect calorimeters. The theoretical and technical aspects of IC in spontaneously breathing subjects and critically ill patients on mechanical ventilation and/or ECMO are covered and a critical review and comparison of the different techniques and sensors is provided. This review also aims to accurately present the physical quantities and mathematical concepts regarding IC to reduce errors and promote consistency in further research. By studying IC on ECMO from an engineering point of view rather than a medical point of view, new problem definitions come into play to further advance these techniques.

Non-Contact Spirometry Using a Mobile Thermal Camera and AI Regression

Non-contact physiological measurements have been under investigation for many years, and among these measurements is non-contact spirometry, which could provide acute and chronic pulmonary disease monitoring and diagnosis. This work presents a feasibility study for non-contact spirometry measurements using a mobile thermal imaging system. Thermal images were acquired from 19 subjects for measuring the respiration rate and the volume of inhaled and exhaled air. A mobile application was built to measure the respiration rate and export the respiration signal to a personal computer. The mobile application acquired thermal video images at a rate of nine frames/second and the OpenCV library was used for localization of the area of interest (nose and mouth). Artificial intelligence regressors were used to predict the inhalation and exhalation air volume. Several regressors were tested and four of them showed excellent performance: random forest, adaptive boosting, gradient boosting, and decision trees. The latter showed the best regression results, with an R-square value of 0.9998 and a mean square error of 0.0023. The results of this study showed that non-contact spirometry based on a thermal imaging system is feasible and provides all the basic measurements that the conventional spirometers support.

Human Vital Signs Detection Methods and Potential Using Radars: A Review

Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject's body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.

Contact-Based Methods for Measuring Respiratory Rate

There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject's body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.

Noncontact spirometry with a webcam

We present an imaging-based method for noncontact spirometry. The method tracks the subtle respiratory-induced shoulder movement of a subject, builds a calibration curve, and determines the flow-volume spirometry curve and vital respiratory parameters, including forced expiratory volume in the first second, forced vital capacity, and peak expiratory flow rate. We validate the accuracy of the method by comparing the data with those simultaneously recorded with a gold standard reference method and examine the reliability of the noncontact spirometry with a pilot study including 16 subjects. This work demonstrates that the noncontact method can provide accurate and reliable spirometry tests with a webcam. Compared to the traditional spirometers, the present noncontact spirometry does not require using a spirometer, breathing into a mouthpiece, or wearing a nose clip, thus making spirometry test more easily accessible for the growing population of asthma and chronic obstructive pulmonary diseases.

Respiration detection chip with integrated temperature-insensitive MEMS sensors and CMOS signal processing circuits

An airflow sensing chip, which integrates MEMS sensors with their CMOS signal processing circuits into a single chip, is proposed for respiration detection. Three micro-cantilever-based airflow sensors were designed and fabricated using a 0.35 μm CMOS/MEMS 2P4M mixed-signal polycide process. Two main differences were present among these three designs: they were either metal-covered or metal-free structures, and had either bridge-type or fixed-type reference resistors. The performances of these sensors were measured and compared, including temperature sensitivity and airflow sensitivity. Based on the measured results, the metal-free structure with fixed-type reference resistors is recommended for use, because it has the highest airflow sensitivity and also can effectively reduce the output voltage drift caused by temperature change.

Mobile monitoring and embedded control system for factory environment

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.

Negative mood and alcohol problems are related to respiratory dynamics in young adults

This study examined the relationship of negative affect and alcohol use behaviors to baseline respiration and respiratory response to emotional challenge in young adults (N = 138, 48 % women). Thoracic-to-abdominal ratio, respiratory frequency and variability, and minute volume ventilation were measured during a low-demand baseline task, and emotional challenge (viewing emotionally-valenced, emotionally-neutral, and alcohol-related pictures). Negative mood and alcohol problems principal components were generated from self-report measures of negative affect and mood, alcohol use, and use-related problems. The negative mood component was positively related to a thoracic bias when measured throughout the study (including baseline and picture exposure). There was generally greater respiratory activity in response to the picture cues, although not specifically in response to the content (emotional or alcohol-related) of the picture cues. The alcohol problems component was positively associated with respiratory reactivity to picture cues, when baseline breathing patterns were controlled. Self-report arousal data indicated that higher levels of negative mood, but not alcohol problems, were associated with greater arousal ratings overall. However, those with alcohol problems reported greater arousal to alcohol cues, compared to emotionally neutral cues. These results are consistent with theories relating negative affect and mood to breathing patterns as well as the relationship between alcohol problems and negative emotions, suggesting that the use of respiratory interventions may hold promise for treating problems involving negative affect and mood, as well as drinking problems.

Development of an integrated sensor module for a non-invasive respiratory monitoring system

A respiratory monitoring system has been developed for analyzing the carbon dioxide (CO2) and oxygen (O2) concentrations in the expired air using gas sensors. The data can be used to estimate some medical conditions, including diffusion capability of the lung membrane, oxygen uptake, and carbon dioxide output. For this purpose, a 3-way valve derived from a servomotor was developed, which operates synchronously with human respiratory signals. In particular, the breath analysis system includes an integrated sensor module for valve control, data acquisition through the O2 and CO2 sensors, and respiratory rate monitoring, as well as software dedicated to analysis of respiratory gasses. In addition, an approximation technique for experimental data based on Haar-wavelet-based decomposition is explored to remove noise as well as to reduce the file size of data for long-term monitoring.