About
The Delfihealth Telemed telemedicine system is an innovative project of the research and production company Delfihealth LLC (https://delfihealth.by), a resident of the China–Belarus Industrial Park “Great Stone” (https://industrialpark.by).
Well-known digital health platforms collect documented data on patients’ condition, analyse it automatically (more and more often with artificial intelligence) and then put patients in touch with specialists. The Delfihealth Telemed portal has its own specialised functions, built around original self-monitoring devices and cloud technologies for storing and processing medical data.
Wearable devices and mobile apps on the user’s smartphone stream biosignals directly to the patient’s personal account, and the treating doctor, a portal expert or even a relative can watch these signals remotely by connecting to the web server. The server software processes the biosignals in real time, which makes the expert’s work much easier and faster. This technology solves the problem of assessing a patient’s condition urgently and, when needed, allows continuous (round-the-clock) monitoring of their health.
Delfihealth Telemed is designed for wide use of home self-monitoring devices that record the ECG, breathing, body temperature, body position and physical activity. A complete technology chain has been built for online interaction between clients and the portal’s consultants. The devices come as a range of models, each suited to particular circumstances and tasks. The mobile apps do the primary processing of biosignals and, already at this stage, tell the user when it is important to see a doctor. The cloud platform contains a structured database for biosignals, medical documents and service information (lists of registered clients and experts, devices used in the system, their calibration data and more). It also hosts personal accounts for metrologists who periodically verify the devices, and for portal operators who monitor the communication channels, active services, client requests, the work of experts and so on.
Portal clients can record biosignals any number of times, keep a diary of other self-monitoring parameters, manage their document archive and arrange services with the operator in advance. The server software lets clients view their biosignals and the results of automatic processing themselves, see trends of diagnostically important indicators and, on that basis, follow how their health is changing. But if they feel worse or are unsure about their own conclusions, they can consult a doctor at once or order longer expert monitoring of their current condition (for example, overnight monitoring, monitoring during work, or after a training session).
This means the portal’s services are useful not only to people with chronic conditions, but to anyone who wants to stay healthy. The system can be used to monitor the condition of transport drivers, operators in high-stress industries, athletes and fitness centre visitors.
No one today disputes the role of physical activity in strengthening health and building up the body’s reserves. Yet overtraining, and even sudden cardiac death among athletes, are not rare. Checking how the body responds to load and detecting hidden heart failure is considered essential not only in clinics, but also in sports medicine and in the physical education of students and schoolchildren. That is why the project gives portal clients an accessible exercise test built into the devices, along with analysis of changes in physical fitness and a search for links between health indicators and lifestyle.
Among the project’s achievements are hardware and software solutions for rapid ECG recording and analysis: on the device itself and its display; on the smartphone, without a connection to the server; and in the personal account when Wi-Fi or mobile internet is available. Without a connection, signals are recorded in the smartphone’s memory and sent to the account later, automatically or when the user chooses. During multi-day monitoring, people can tell the experts about their activities and how they feel through voice or text messages, which makes the signals easier to interpret and helps anticipate unwanted states, overfatigue and growing health risks.
The project team believes that putting its results into practice will reduce illness in the population and the loss of working capacity, and will raise the standard of occupational safety, physical education of students and social care for older people. As real-world data accumulates on the portal and machine learning is applied, the developers plan to build services that respond instantly to client requests and provide diagnostic conclusions and recommendations, including programs for biofeedback-guided physical training.