The use of information technology and technological medical devices has contributed significantly to the transformation of healthcare. Despite that, many problems have arisen in diagnosing or predicting diseases, either as a result of human errors or lack of accuracy of measurements. Therefore, this paper aims to provide an integrated health monitoring system to measure vital parameters and diagnose or predict disease. Through this work, the percentage of various gases in the blood through breathing is determined, vital parameters are measured and their effect on feelings is analyzed. A supervised learning model is configured to predict and diagnose based on biometric measurements. All results were compared with the results of the Omron device as a reference device. The results proved that the proposed design overcame many problems as it contributed to expanding the database of vital parameters and providing analysis on the effect of emotions on vital indicators. The accuracy of the measurements also reached 98.8% and the accuracy of diagnosing COVID-19 was 64%. The work also presents a user interface model for clinicians as well as for smartphones using the Internet of things.

<p class="Abstract">Monitoring patient’s condition represents one of the crucial tasks in any biomedical center to ensure the stability of the patient state. Healthcare sector quality demands are exponentially rising. These demands are concerned with designing expert systems for medical diagnosis. Also, the use of fuzzy sets theory in the medical field is to solve some medical problems.  </p><p class="Abstract">This paper proposes a simple strategy of bio measurements and its behavior through fuzzy logic model. The proposed design is constructed using three different types of data transfer based sensors and microcontroller.</p><p class="Abstract">The fuzzy logic model is designed and practically tested. The generated results are compared to those of the (Omron RS3 - HEM-6130-E Omron mc-246-e) device from OMRON company. Four hundred people aged between 3 and 72 years old were examined by the proposed system. All results are compared using fuzzy logic model in MATLB. Using statistical analysis, the average data measurements for each sensor in the designed device were recorded; the output results were found to be of close enough (less than 1% error) to the reference readings.</p><p class="Abstract">The system can be used at home due to its low cost, easy to use, and high accuracy.</p>

<span lang="EN-US">Military personnel in the training or operational phases always need constant medical examination, but the presence of efficient medical care is difficult to implement in real-time for such cases. A wireless system for thermal tracking of soldiers was proposed, as well as tracking their vital signs in real time. Thermal cameras are used with an optical system designed to increase the accuracy of the thermal images captured as the change in the electro-cardiogram, heart rate, and temperature measurements are measured using a specially designed circuit. The results from both the thermal system and the biometric system are combined and sent to a computer for analysis using a model prepared with neural network technology. The proposed system was tested, and a database was created for 127 males and 110 females during training and rest times. The neural network model achieved a response time of 85 seconds until the release of the final analysis, and the accuracy of the proposed tracking system is 96%. The main contribution of this paper is the design of an integrated portable system for rapid, in-field, real-time military medical diagnostics.</span>

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<span lang="EN-US">Recently, some problems have appeared among medical workers during the diagnosis of some diseases due to human errors or the lack of sufficient information for the diagnosis. In medical diagnosis, doctors always resort to separating human emotions and their impact on vital parameters. In this paper, a methodology is presented to measure vital parameters more accurately while studying the effect of different human emotions on vital signs. Two designs were implemented based on the microcontroller and National Instruments (NI) myRIO. Measurements of four different vital parameters are measured and recorded in real time. At the same time, the effects of different emotions on those vital parameters are recorded and stored for use in analysis and early diagnosis. The results proved that the proposed methodology can contribute to the prediction and diagnosis of the initial symptoms of some diseases such as the seventh nerve and Parkinson’s disease. The two proposed designs are compared with the reference device (beurer) results. The design using NI myRIO achieved more accurate results and a response time of 1.4 seconds for real-time measurements compared to its counterpart based on microcontrollers, which qualifies it to work in intensive care units.</span>