In recent decades, with the advancement of communication and information technologies, telemedicine has been increasingly considered as a new solution in providing health services. This trend reached its peak especially during the pandemic, when the need for social distancing and reducing physical contact made the provision of medical services virtually and remotely a necessity. According to the World Health Organization (WHO), the pandemic led to fundamental changes in the way health care is provided and increased use of new technologies in this field.
In this regard, the development of telemedicine platforms that can effectively manage patients' biological signals is of particular importance. This paper examines the development of a web socket-based telemedicine platform designed as a comprehensive solution for monitoring patient health. This system is capable of collecting and transmitting data related to patients' vital signs in real time using the open source eHealth V2.0 platform and WebSocket technology.
Project Objectives
The main objective of this project is to develop a remote monitoring solution for real-time biological signal management. The system includes the measurement and transmission of data related to temperature, electrocardiogram (ECG), airflow, heart rate, and blood oxygen saturation (SpO2). Using this system, healthcare professionals can easily track patients’ vital signs in real time and make timely interventions if needed. The project also seeks to improve access to medical services and reduce healthcare costs.
Relevance
Telemedicine has gained great importance as a new approach in healthcare delivery, especially in critical situations and pandemics. This method allows medical professionals to provide care and treatment services with minimal physical contact with patients. These systems can also help reduce healthcare costs and improve access to healthcare services. Given the increasing demand for telemedicine services, it is essential to develop effective and efficient platforms in this field.
Methodology
The project was implemented using agile methodologies, specifically the SCRUM approach. This approach allows the development team to respond quickly to changes in needs and requirements. The main stages of the project include analysis, design, implementation, testing, and product delivery. In this regard, the design and functional requirements were carefully specified and the system was divided into three main stages: signal acquisition, signal processing, and data visualization.
Design and Implementation
In this study, various sensors were used to measure biological signals. These sensors include temperature, heart rate, oxygen saturation, electrocardiogram, and airflow sensors. The signals are sent to the server using Arduino and Raspberry Pi. WebSocket has been identified as a suitable solution for real-time data transfer. This technology allows two-way communication between clients and servers, and thus, data is transferred quickly and in real time.
Development Stages
1. Signal Acquisition: In this stage, the system is designed to be able to collect biological signals from various sensors. These sensors are connected to a microcontroller such as Arduino and process the data digitally.
2. Signal Processing: After receiving the signals, the data needs to be processed to convert them into useful information. This processing includes noise filtering, feature extraction, and signal analysis. The use of digital signal processing techniques is very crucial in this stage.
3. Data Visualization: Finally, the processed data needs to be displayed visually. For this purpose, a graphical user interface (GUI) is designed that allows users to view the acquired data in real time. This user interface is developed using the React framework.
Performance Evaluation
The system performance has been evaluated using various criteria including latency, accuracy, data transfer rate and stability. The results show that the average latency in this system was 3 ms and the average jitter was 2 ms. Also, the accuracy of the measurements has been confirmed using standard deviation and confidence intervals. These results indicate the high efficiency of the system in data transmission and patient health monitoring.
Results
This study shows that the developed system is capable of providing accurate and timely data for patient health monitoring. Using this platform, it is possible to track patients' vital signs in real time and helps in timely interventions. Also, this system leads to reducing medical costs and improving the quality of health services.
Discussion and Conclusion
The developed telemedicine platform provides an effective solution for managing biological signals in critical situations and improving the quality of health services. This system can be used as a key tool in the future of medicine, given the increasing needs for telemedicine services and its high capabilities in integrating various technologies.
Future Outlook
Due to the rapid advances in information and communication technologies, telemedicine is expected to expand rapidly. In the future, it can be expected that telemedicine systems will improve using artificial intelligence and machine learning, providing greater capabilities in data analysis and predicting patient health status. Also, with the expansion of the Internet of Things (IoT), greater connectivity and integration of medical devices and sensors will be possible.
Challenges and Limitations
Despite significant advances in the field of telemedicine, there are still challenges and limitations that need to be addressed. One of these challenges is data security and patient privacy. Transferring sensitive data online can be risky and requires strong security protocols and protection standards. Also, the lack of access to high-speed internet in some areas can prevent the effective use of these systems.
Suggestions for future research
To improve the performance and capabilities of telemedicine systems, future research should focus on developing more advanced algorithms for data analysis, improving security protocols, and increasing internet access in underserved areas. Also, examining the social and economic impacts of these systems on society and patients can also help to better understand their efficiency and effectiveness.
Technical and technological aspects
1. WebSocket technology: One of the key aspects in this project is the use of WebSocket technology. WebSocket is a communication protocol that allows two-way communication between a client and a server, allowing data to be transferred in real time. This technology is particularly suitable for monitoring biological signals that require fast and continuous transmission.
2. Development frameworks: Various frameworks have been used to develop this system. Server-side frameworks such as Express.js have been used to create the server and manage requests, and client-side frameworks such as React.js have been used to create the user interface. These choices allow developers to create a seamless and efficient system.
3. System architecture: The system is designed to consist of several layers. The first layer includes sensors and microcontrollers to collect data. The second layer includes the server that processes the data, and the third layer includes the user interface that visually displays the data. This architecture helps increase the scalability and flexibility of the system.
Data Analysis
Data analysis is a vital part of this system. Data collected from sensors must be processed accurately to extract useful information. This processing includes the following steps:
1. Data filtering: Raw data may contain noise and distortions. The use of digital filters is essential to remove this noise and improve the quality of the signals.
2. Feature extraction: After filtering, key features are extracted from the signals. These features can include the mean, standard deviation, and signal fluctuations.
3. Trend analysis: Using analytical algorithms, trends in the data are identified. These trends can help predict the health status of patients.
Socio-economic impacts
With the expansion of telemedicine, the socio-economic impacts of these systems should also be examined. On the one hand, these systems can help improve access to health services, and on the other hand, they may increase the costs of ICT infrastructure. There is also a need to educate and raise awareness among patients and medical professionals about the use of these systems.
Conclusion
The developed telemedicine platform offers an effective solution for managing biological signals in critical situations and improving the quality of health services. This system can be used as a key tool in the future of medicine, given the increasing needs for telemedicine services and its high capabilities in integrating different technologies. Given the existing challenges and limitations, efforts to improve the security, accessibility, and efficiency of these systems should be prioritized.
Source: www.mdpi.com