Purpose: Lung diseases are the third leading cause of death worldwide. Stethoscope-based auscultation is the most commonly used, non-invasive, inexpensive, and primary diagnostic approach for assessing lung conditions. However, the manual auscultation-based diagnosis procedure is prone to error, and its accuracy is dependent on the physician’s experience and hearing capacity. Moreover, the stethoscope recording is vulnerable to different noises that can mask the important features of lung sounds which may lead to misdiagnosis. In this paper, a method for the acquisition of lung sound signals and classification of the top 7 lung diseases has been proposed for improving the efficacy of auscultation diagnosis of pulmonary disease. Methods: An electronic stethoscope has been constructed for signal acquisition. Lung sound signals were then collected from people with COPD, upper respiratory tract infections (URTI), lower respiratory tract infections (LRTI), pneumonia, bronchiectasis, bronchiolitis, asthma, and healthy people. Lung sounds were analyzed using a wavelet multiresolution analysis. To choose the most relevant features, feature selection using one-way ANOVA was performed. The classification accuracy of various machine learning classifiers was compared, and the Fine Gaussian SVM was chosen for final classification due to its superior performance. Model optimization was accomplished through the application of Bayesian optimization techniques. Results: A test classification accuracy of 99%, specificity of 99.2%, and sensitivity of 99.04%, have been achieved for the 7 lung diseases using the optimized Fine Gaussian SVM classifier. Conclusion: Our experimental results demonstrate that the proposed method has the potential to be used as a decision support system for the classification of lung diseases, especially in those areas where the expertise and the means are limited.

Improper cycling posture is linked to a variety of spinal musculoskeletal diseases, including structural malformation of the spine and back discomfort. This paper presents a novel smart shirt integrated tri-axial gyroscope and accelerometer that can detect postural variation in terms of spinal curvature changes. To provide accurate feedback to the wearer and improve the wearer’s correct movement, the garment is able to recognize trunk body posture. The gyroscope/accelerometer was placed around the upper and mid trunk of the user to record tri-axial angular velocity data. The device can also be used to help determine the trunk bending angle and monitor body postures in order to improve optimal orientation and position. The garment enables continuous measurement in the field at high sample rates (50 Hz), and the sensor has a large measurement range (16 g, 2000°/s). As electronic components are non-washable, instead of encapsulating them, a detachable module was created. In this, magnets are embedded in the jersey, and allow the positioning and removal of the sensor. The test results show that the average trunk-bending angle was 21.5°, and 99 percent of the observed angle fell within the standard (ranging from 8° to 35°). The findings demonstrate the feasibility of employing the smart shirt sensor to estimate trunk motions in the field on a regular basis.

Purpose: In a clinical setting, blood oxygen saturation is one of the most important vital sign indicators. A pulse oximeter is a device that measures the blood oxygen saturation and pulse rate of patients with various disorders. However, due to ethical concerns, commercially available pulse oximeters are limited in terms of calibration on critically sick patients, resulting in a significant error rate for measurement in the critical oxygen saturation range. The device’s accessibility in developing countries’ healthcare settings is also limited due to portability, cost implications, and a lack of recognized need. The purpose of this study was to develop a reliable, low-cost, and portable pulse oximeter device with improved accuracy in the critical oxygen saturation range. Methods: The proposed device measures oxygen saturation and heart rate using the reflectance approach. The rechargeable battery and power supply from the smartphone were taken into account, and the calibration in critical oxygen saturation values was performed using Prosim 8 vital sign simulator, and by comparing with a standard pulse oximeter device over fifteen iterations. Results: The device’s prototype was successfully developed and tested. Oxygen saturation and heart rate readings were both accurate to 97.74% and 97.37%, respectively, compared with the simulator, and an accuracy of 98.54% for the measurement of blood oxygen saturation was obtained compared with the standard device. Conclusion: The accuracy of oxygen measurement attained in this study is significant for measuring oxygen saturation for patients in critical care, anesthesia, pre-operative and post-operative surgery, and COVID-19 patients. The advancements made in this research have the potential to increase the accessibility of pulse oximeter in resource limited areas.

Background: Primary postpartum hemorrhage (PPH) is an obstetric emergency caused by excessive blood loss that occurs most commonly after the placenta is delivered. PPH can lead to volume depletion, hypovolemic shock, anemia, and it is the leading cause of maternal mortality worldwide. With 470 deaths per 100,000 live births, the maternal mortality ratio in Ethiopia is one of the highest in the world. It is estimated that 94% of births occur at home in Ethiopia and that 10% of maternal deaths are attributed to PPH. Currently, physicians use visual estimation to calculate blood loss and provide fluid during delivery. This traditional method is subjective and generally inaccurate.Method: In this project, after delivery blood loss measurement system integrated with fluid delivery and vital sign monitoring method is proposed. The collection and measurement system collects blood loss after delivery and measures the amount of blood loss. The management system continuously monitors the mother’s heart rate and blood pressure. These vital sign values are integrated with the measured blood loss to estimate the amount of IV fluid required to be delivered for the mother. The rate of IV fluid delivery is regulated by a flow rate sensor and solenoid valve.Results: The prototype was built and undergone through different tests and iterations. The proposed device was tested for accuracy, cost effectiveness and ease to use. 91.28% accuracy has been achieved and the prototype was built with less than 210 USD.Conclusion: The proposed design allows physicians, especially those in low resource setting, to estimate blood loss and deliver fluid accurately. This helps to reduce maternal mortality rate that may occur due to postpartum hemorrhage.

Recent developments in flexible printed heaters (FPHs) for wearable thermal applications, driven by the advancement of printed electronics, show great promise in revolutionizing patient care through the development of wearable flexible heaters for medical applications. Wearable heaters with high thermal stability, heat uniformity, safety, flexibility, comfort, biocompatibility, biodegradability, recyclability, and power efficiency are desirable for standalone medical thermotherapy applications. This paper reviews recent advancements in the design of FPHs for wearable thermal applications. Materials used in the FPHs, fabrication methods, design considerations, temperature control mechanisms, medical applications, and performance analysis of specific FPHs are all thoroughly discussed. Materials used in FPHs, such as conductive and substrate materials, receive special attention along with the heater design parameters. Additionally, the paper addresses the challenges and future directions for the advancement of FPHs in wearable medical applications.