ABSTRACT
The continuous monitoring of respiratory rate (RR) and oxygen saturation (SpO2) is crucial for patients with cardiac, pulmonary, and surgical conditions. RR and SpO2 are used to assess the effectiveness of lung medications and ventilator support. In recent studies, the use of a photoplethysmogram (PPG) has been recommended for evaluating RR and SpO2. This research presents a novel method of estimating RR and SpO2 using machine learning models that incorporate PPG signal features. A number of established methods are used to extract meaningful features from PPG. A feature selection approach was used to reduce the computational complexity and the possibility of overfitting. There were 19 models trained for both RR and SpO2 separately, from which the most appropriate regression model was selected. The Gaussian process regression model outperformed all the other models for both RR and SpO2 estimation. The mean absolute error (MAE) for RR was 0.89, while the root-mean-squared error (RMSE) was 1.41. For SpO2, the model had an RMSE of 0.98 and an MAE of 0.57. The proposed system is a state-of-the-art approach for estimating RR and SpO2 reliably from PPG. If RR and SpO2 can be consistently and effectively derived from the PPG signal, patients can monitor their RR and SpO2 at a cheaper cost and with less hassle.
ABSTRACT
Although the Berlin definition of acute respiratory distress syndrome (ARDS), 2012 has been widely used in clinical practice, issues have occasionally been raised regarding various criteria since it was proposed. High-flow nasal oxygen (HFNO) is widely used for effective respiratory support in acute respiratory failure. As patients who do not require ventilation but meet the Berlin criteria have similar characteristics to those with ARDS, the definition of ARDS may be broadened to include patients receiving HFNO. As the PaO2/FiO2 under-recognizes the diagnosis of ARDS, a SpO2/FiO2 value of ≤315 may be considered instead of a PaO2/FiO2 value of ≤300 for diagnosing the condition in resource-constrained settings. In this context, patients with severe COVID-19 always meet other criteria for ARDS except for 7-day acute onset. Therefore, the timeframe for the onset of ARDS may be extended to up to 14 days. An expanded definition of ARDS may allow early identification of patients with less severe diseases and facilitate testing and application of new therapies in patients with a high risk of poor outcomes. Here, we discuss the major controversies regarding the extension of the ARDS definition with a view to improving clinical implementation and patient outcomes.
ABSTRACT
Background: The bulk of oxygen in blood is normally transported as oxyhemoglobin. The amount of oxyhemoglobin is often expressed as percentage saturation (Spo2). Objective(s): Oxygen saturation is one of the vitals monitored in clinical practice and also the most important vital monitored in COVID-19patients since it's the oxygen saturation which gets depleted in these patients. COVID pandemic has taken heavy toll on health and life of the people and since different people respond to COVID-19 differently so the response is multifactorial. The exposure to lower oxygen levels may have important clinical consequences, particularly in physiologic processes like respiratory drive, which are dependent on PO2 in the blood. Hence our aim is to study the effect of BMI and Hb on oxygen saturation (SPO2). Method(s): A descriptive cross-sectional study was conducted in Department of Physiology, SKIMS-Medical College. Data was collected by using self-administered questionnaire followed by anthropometric measurement. Body Mass Index (BMI) by Quetelet's index and Haemoglobin (Hb) concentrations by Sahli's method were assessed. Pulse oximetry was done to know the oxygen saturation. Result(s): The students with high BMI show negative correlation with oxygen saturation while as Hb with oxygen saturation shows positive correlation. These results have important clinical implications while treating patients with high BMI or low Hb. Copyright © 2023, Institute of Medico-legal Publication. All rights reserved.
ABSTRACT
The Covid-19 pandemic outbreak is still not over. Even today, there are many cases of people without symptoms (OTG = Orang Tanpa Gejala/People Without Symptoms). The sufferer does not feel the symptoms of fever, cough and runny nose. Patients can still do activities as usual, but suddenly experience shortness of breath and decreased consciousness due to lack of oxygen. This phenomenon of reducing the amount of oxygen in the body without causing symptoms is known as happy hypoxia. This study aims to design a prototype measurement of blood oxygen saturation (SpO2) as an early detection of happy hypoxia in Covid-19 patients using a pulse oximeter sensor and non-invasive methods (without surgery). The sensor is placed on the patient's fingertip and will measure the intensity of light that penetrates the bloodstream at the fingertip. The measurement data is compared with an oximeter and this tool has the highest error of 0.02% and the lowest 0.01%. © 2022 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
"Pulse oxymeter" A medical device is quiet popular and used widely throughout during the COVID19 pandemic.Almost every household has one pulse Oxymeter and ubiquotiosly used nowadays to monitor the body oxygen saturation on room air. Portable pulse oximetry can be used by patients of any age.The present paper throws light on the working Principle of Pulse oxymeter and its applications in medical and other than hospital settings which is an application of physics(photo plethysmography).