A reusable, low-cost and self-sufficient sensorbased neonatal pulse oximeter

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2022Pulse oximeters are non-invasive medical health devices for measuring oxygen saturation and pulse rate of humans. Pulse oximeters used for neonates have been identified to have some limitations in terms of their bulkiness in size, the need for a pulse sensor attachment to a monitoring device to obtain readings and their expensive nature. This project explores a pulse oximeter design to eliminate these limitations and create an accurate alternative for neonatal pulse oximeters. The proposed design includes a pulse sensor and a control and display circuit self-sufficiently powered by a direct current source of voltage. It employs analog signal processing, digital signal processing (DSP) with a low-power but highly efficient microprocessor to ensure accurate values are obtained. The project explores this design but however implemented part of the design (Infrared (IR) sensor) based on the materials and electrical components available. Even though the proposed design was not built as whole, various sections of the design was implemented or simulated and were feasible. The results from the IR sensor built was compared to a commercial pulse oximeter and from the statistical analysis conducted, the two systems have similar readings confirmed by the t-value of 0.917 in the paired t-test. Unfiltered data was used with the algorithm developed and the DSP and the readings for the SpO2 and pulse rate were similar to the commercial oximeter.Ashesi Universit

Investigation of Photodetector Optimization in Reducing Power Consumption by a Noninvasive Pulse Oximeter Sensor

Noninvasive pulse oximetry represents an area of potential interest to the army, because it could provide cost-effective, safe, fast and real-time physiological assessment in a combat injured soldier. Consequently, there is a need to develop a reliable, battery-powered, wearable pulse oximeter to acquire and process photoplethysmographic (PPG) signals using an optimized sensor configuration. A key requirement in the optimal design of a wearable wireless pulse oximeter is low power management without compromising signal quality. This research investigated the advantage gained by increasing the area of the photodetector and decreasing the light emitting diode (LED) driving currents to reduce the overall power requirement of a reflectance mode pulse oximeter sensor. In vitro and preliminary in vivo experiments were conducted to evaluate a multiple photodetector reflectance sensor setup to simulate a varying detection area. It was concluded that a reflection pulse oximeter sensor employing a large area photodetector is preferred over a similar transmission type sensor for extending the battery life of a wireless pulse oximeter intended for future telemedicine applications

Non-invasive sensor methods used in monitoring newborn babies after birth, a clinical perspective

Background Reducing the global new-born mortality is a paramount challenge for humanity. There are approximately 786,323 live births in the UK each year according to the office for National Statistics; around 10% of these newborn infants require assistance during this transition after birth. Each year around, globally around 2.5 million newborns die within their first month. The main causes are complications due to prematurity and during delivery. To act in a timely manner and prevent further damage, health professionals should rely on accurate monitoring of the main vital signs heart rate and respiratory rate. Aims To present a clinical perspective on innovative, non-invasive methods to monitor heart rate and respiratory rate in babies highlighting their advantages and limitations in comparison with well-established methods. Methods Using the data collected in our recently published systematic review we highlight the barriers and facilitators for the novel sensor devices in obtaining reliable heart rate measurements. Details about difficulties related to the application of sensors and interfaces, time to display, and user feedback are explored. We also provide a unique overview of using a non-invasive respiratory rate monitoring method by extracting RR from the pulse oximetry trace of newborn babies. Results Novel sensors to monitor heart rate offer the advantages of minimally obtrusive technologies but have limitations due to movement artefact, bad sensor coupling, intermittent measurement, and poor-quality recordings compared to gold standard well established methods. Respiratory rate can be derived accurately from pleth recordings in infants. Conclusion Some limitations have been identified in current methods to monitor heart rate and respiratory rate in newborn babies. Novel minimally invasive sensors have advantages that may help clinical practice. Further research studies are needed to assess whether they are sufficiently accurate, practical, and reliable to be suitable for clinical use

Development of non-invasive, optical methods for central cardiovascular and blood chemistry monitoring.

Cardiovascular disease and sepsis are leading causes of mortality, morbidity and high cost in hospitals around the world. Failure of the circulatory system during cardiogenic shock and sepsis both can significantly impair the perfusion of oxygen through organs, resulting in poor patient outcome if not detected and corrected early. Another common disorder which goes hand-in-hand with cardiovascular disease is Diabetes Mellitus. Diabetes is a metabolic disorder resulting from the inability of the body to regulate the level of glucose in the blood. The prevalence of diabetes worldwide is increasing faster than society’s ability to manage cost effectively, with an estimated 9% of the world population diagnosed with metabolic disease. The current gold standard measurements for venous oxygen saturation, arterial pulse wave velocity (PWV), and diabetes management through blood glucose concentration monitoring are all invasive. Invasive measurements increase risk of infection and com- plications, are often high cost and disposable, and have a low patient compliance to regular measurements. The aim of this thesis is to develop non-invasive methods of monitoring these important dynamic physiological variables, including, venous oxygen saturation, pulse wave velocity, and blood glucose concentration. A novel photoplethysmography-based NIR discrete wavelength spectrometer was developed using LEDs to both emit light, and detect the light reflected back through the tissue. Using LEDs to detect light simplifies sensing circuit design, lowering hardware costs, allowing adaptable sensing specific to the needs of the user. A reflectance pulse oximeter was developed to measure the oxygen saturation at both the external jugular vein, and carotid artery. Measuring the jugular venous pulse (JVP) allows estimation of the venous oxygen saturation through either the JVP, or through breathing induced variation of the JVP. In addition to oxygenation, the de- vice developed is capable of adapting the sensing layout to measure the arterial pulse waveform at multiple sites along a peripheral artery, such as the carotid or radial. The PWV local to the carotid artery, and radial artery can then be measured, providing key information of cardiovascular risk. A novel algorithm for PWV measurement over multiple pulse waveforms was also developed. Expanding the sensor to use multiple different wavelength LEDs allow discrete spectroscopy in pulsatile blood. An absorption model of components in blood at specific wavelengths was created to isolate the spectral fingerprint of glucose. The sensor successfully measured the oxygen saturation at the carotid artery, and external jugular vein across 15 subjects, giving mean oxygen saturations of 92% and 85% respectively, within the expected physiological ranges. Venous oxygen saturation calculated using breathing induced changes to JVP was 3.3% less than when calculated on the JVP alone, with a standard deviation of 5.3%, compared to 6.9%. Thus, future work on the sensor will focus on extraction of the breathing induced venous pulse, rather than measuring from the JVP itself. The PWV on the carotid and radial artery was successfully measured within the ex- pected physiological ranges, with the novel phase difference algorithm proving more robust to noise than the gold standard foot-foot method. The phase difference method returned a mean PWV at the radial artery of 4.7 ±0.6 m s−1, and a mean CoV of 20%, compared to 4.0 ±1.4 m s−1, and a moan CoV of 58% for the foot-foot method. The proof of concept PWV sensor gives promising results, but needs to be calibrated against invasive gold standards, such as aorta and femoral pressure catheters. A glucose trial involving adult and neonatal subjects provided validation of the NIR non-invasive pulse glucometer. The sensor has an R2 of 0.47, and a mean absolute relative difference (MARD) of 19% compared to gold standard reference measurements. Clarke error grid analysis returns 85% of measurements in Zone A, 11% in Zone B, and 4% in Zone C. While the sensor is not as accurate as the gold standard invasive measurements, the ability to constantly measure without any pain or discomfort will help increase measurement compliance, improving user quality of life, plus further development may improve this. Overall, this thesis provided novel contributions in non-invasive venous oxygen saturation, PWV, and glucose concentration monitoring. The adaptability of the sensor shows promise in helping reduce the pain and inconvenience of the current invasive measurements, especially in diabetes management, where the sensor has the most potential for impact

A novel approach to monitor tissue oxygen saturation with broadband near-infrared spectroscopy

Cerebral oximetry is the measurement of tissue oxygen saturation, StO2, with near-infrared spectroscopy (NIRS). The technique offers a non-invasive assessment of cerebral oxygenation and has potential to be used as a biomarker in neonatal critical care, particularly hypoxic-ischaemic-encephalopathy (HIE). HIE is a major cause of neonatal mortality and affected neonates need continuous cerebral monitoring to guide treatment and improve patient outcome. While multiple algorithms to recover StO2 have been published, issues with low measurement accuracy or extracranial tissue signal contamination remain. This thesis is focused on the exploration of recovering StO2 from continuous-wave broadband NIRS measurements with the aim to develop a novel algorithm to recover StO2 with increased dynamic range and depth resolution. The novel algorithm, broadband multidistance oximetry (BRUNO), recovers StO2 from a broadband multidistance measurement of the attenuation slope against distance. BRUNO combines and expands two other StO2 algorithms, spatially resolved spectroscopy (SRS) and broadband fitting (BF). The evaluation of algorithm performance was done in data obtained in computational simulations and phantoms. The median error of brain StO2 recovered in simulations of brain and extracerebral tissue oxygenation changes was 1.1% with BRUNO, 2.3% with BF and 3.8% with SRS. Measurements during full oxygenation-deoxygenation cycles in a homogeneous blood phantom showed differences in the dynamic range of the algorithms; BRUNO recovered StO2 over 0–100%, BF over 0–90% and SRS over 40–80%. These results show higher accuracy of BRUNO StO2, higher sensitivity to brain oxygenation and wider dynamic range. Measurements of StO2 in one neonate with HIE showed that the StO2 algorithms led to different baseline values. Including an automated data assessment step in BRUNO to evaluate the suitability of collected spectra for analysis ensured BRUNO reliability. These findings highlight the effect of StO2 algorithm selection on oxygenation recovery; applying BRUNO in the clinical care setting could reveal further insight into complex oxygenation processes occurring during neonatal brain injury

Implementation of IoT of an Electric Infant Warmer to Prevent Hypothermia in Newborns

Hypothermia is a drop in body temperature below 36.5°C in newborns. It results in an internal distribution of body heat from the nucleus to the periphery, followed by heat loss greater than metabolic production. Hypothermia is one of the factors predisposing to metabolic disorders, intracranial hemorrhage, respiratory distress, and Necrotizing enterocolitis. Hypothermia problems can be treated with infant warmers. Thus, the need for a infant warmer is considered to improve survival in newborns. This study aims to improve the accuracy of temperature monitoring, increase security, and enable remote monitoring. The temperature sensor of the device is calibrated with comparable devices such as Incubator Analyzer and Thermo hygrometer while the SpO2 sensor is calibrated with Spotlight SpO2 Functional Tester and Thermo hygrometer. Achievement and validation of temperature and oxygen saturation use a calibration comparison tool. The results of the temperature sensor measurements, including air temperature and skin sensor temperature, namely: air temperature error tolerance ≤2°C and skin sensor temperature error tolerance ± 0.5 ° C. All two indicators have the same standard deviation value of ±0.49. The SpO2 indicator reached an error tolerance value of ± 1% O2 with a standard deviation value of ± 0.6-0.9 from six trials. Then the pulse rate indicator obtained an error tolerance of ±5% with a standard deviation value of ±0.6. The smart infant warmer tool provides benefits to avoid excessive heat from the heater and minimize low temperatures that cause hypothermia through the Internet of Things technology. Furthermore, this research can be improved with machine learning technology to increase efficiency and effectiveness in patient treatment

The 2023 wearable photoplethysmography roadmap

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology