Gleb Olegovich Bondarenko

1. Relevance of the topic

The assessment of muscle tone is an important aspect of physiotherapy and rehabilitation, as well as in the field of sports medicine. It is used to assess the level of muscle activity and identify any abnormalities or imbalances in muscle tone. It is also used to monitor the progress of a patient's recovery and track changes in muscle tone over time.

A mobile system for analyzing muscle tone is particularly relevant as it allows healthcare professionals to perform assessments in a variety of settings, including in the clinic, at home, or even remotely. This can be especially helpful for patients who have mobility issues or live in remote areas, as it eliminates the need to travel to the clinic for an assessment.

In addition, using machine learning algorithms to analyze muscle tone data can improve the accuracy and consistency of estimates, as well as detect subtle changes in muscle tone that can be missed by traditional methods.

In general, a mobile system for analyzing muscle tone can provide a more efficient,a convenient and accurate way for healthcare professionals to assess and monitor their patients' muscle tone and can help improve patient outcomes.

2. Purpose and objectives of the study, planned results

Purpose - to develop a hardware-software complex for the analysis of muscle tone to improve the efficiency of decision-making in the treatment of patients with neuromuscular diseases

Main research objectives:

— Development of device hardware: design and creation of electronic circuits, selection and integration of electronic components, production of printed circuit boards and mechanical parts;

—Software development: creating a program that will process and display the captured signals, as well as provide communication with other devices (for example, with doctor's monitors);

—Implementation of signal analysis processing algorithms and software.

Research object: When developing a biotechnical system for analyzing a patient's muscle tone, the object of research will be the biotechnical system itself, including an EMG recording device, an analyzer and software for data processing and analysis.

Subject of study:

— Information support;

— Methodological support;

— Tooling;

—Software and algorithmic support;

— Metrological support.

Planned scientific results: Obtaining new knowledge about the functioning of the human nervous system and muscles, as well as methods for diagnosing and monitoring them. A new understanding of the technologies for collecting and processing EMG signals can also be obtained.

Planned practical results: The possibility of using the device in medical institutions for the diagnosis and monitoring of various diseases of the nervous system and muscles. Also, the device can be used in operations on the nervous system and muscles to continuously monitor the patient's condition.

3. The structure of the developed biotechnical systems

This BTS is diagnostic, based on physiological methods based on the registration and analysis of bioelectrical potentials of muscles and peripheral nerves. At the same time, depending on the objectives of the study, both voluntary and stimulation-induced activity of the neuromuscular apparatus is evaluated.

3.1 Block diagram and its components

Figure 1 - Structural diagram of the developed BTS

Figure 1 shows the structure of contactless monitoring, where:

– Signal recording tools (EMG, which picks up a signal using electrodes, based on the difference in electrical potential between two points);

– Means for processing medical signals and data (in this case, it is a methodology and a program);

– Medical decision support system (coordination with the medical information system is underway)

- Analysis of diagnostically significant indicators (such as H-reflex, F-wave, M-response, myotatic reflex, used in the assessment of nerve damage);

VZ - medical opinion.

[X] – patient's reaction to the test impact;

[Y] – set of biomedical signals reflecting the patient's response to the test effect [X];

[S] is a set of signals recorded by sensors and electrodes ([S] = [K][Y], where [K] is a linear operator that reflects the sensitivity of the sensors, and is also the gain of the amplifiers);

[Pts] – Indicator of the current state of the patient.

3.2 System characteristics

System control loops include setting measurement parameters, managing sensors, and displaying measurement results on the device. The system can also have the function of automatically alerting medical personnel about deviations from the norm in the patient's health parameters.

The communication channels of the system may include a wireless connection to a hospital LAN or the Internet to allow medical staff to monitor a patient's condition remotely. The function of recording and storing data can also be implemented to enable the information to be analyzed in the future.

System communication channels provide data transfer between various devices and system components. They can be implemented using various technologies, depending on the required speed, distance and transmission security.data.[2]

Some examples of information exchange channels that can be implemented in the system:

- Wireless connection: Using technologies such as Bluetooth or Wi-Fi, you can realize a wireless connection between sensors and a portable device. A wireless connection to the hospital's LAN or the Internet can also be implemented to enable remote patient monitoring.

- Wired connection: A wired connection can be made between the sensors and the handheld device using cables and adapters. This option may be suitable if you want to ensure high speed and accuracy of data transfer, as well as avoid possible interference in the system operation associated with the use of wireless technologies.

- Integration with other systems: The system can be integrated with other medical systems such as intensive care monitoring systems, infusion management systems, etc. For this, various interfaces and data exchange protocols can be used, such as HL7, DICOM, etc. Integration with other systems enables data sharing and improves treatment efficiency, as well as reducing the risk of data entry errors.[3]

Depending on the required functions and characteristics of the system, information exchange channels can be implemented as a combination of different technologies and interfaces. In the master's thesis, it is planned to develop: information, methodological, instrumental, software-algorithmic and metrological levels of support (components).[4]

3.3 Security levels

To develop this system, the following levels of support should be developed:

1. Information support:

- Database for storing information about patients, EMG signal measurements, treatment, etc.;

- Interfaces for entering, editing and displaying information;

- Database management system to ensure data security, integrity and consistency.

2. Methodological support:

- Guidelines and instructions for using the system for medical professionals and patients;

- EMG signal processing and analysis techniques;

- Knowledge base about pathologies and their treatment

3. Tooling:

- Equipment for taking the EMG signal (for example, an electrocardiograph or an electromyograph);

- Software for EMG signal processing and analysis;

- Tools for visualizing and displaying results (for example, graphs and charts).

4. Metrological assurance:

- Standards and specifications necessary to ensure measurement accuracy;

- Means of calibration and verification of equipment;

- Metrological documentation management system.

5. Software and algorithmic support:

- Operating system and required software;

- The program code that ensures the operation of the system;

- Software version control system and ensuring compatibility with various operations

The structure of the developed system provisioning level may include the following components:

1. Data collection and processing module:

- Equipment for taking EMG signal;

- Software for EMG signal processing and analysis;

- Interfaces for data input and display.

2. Information storage and processing module:

- Database for storing information about patients, EMG signal measurements, treatment, etc.;

- Database management system

3. Visualization and analysis module:

- Graphing and charting functions;

- Data analysis functions that allow you to identify trends and patterns;

- Interfaces for displaying analysis results.

4. Quality Management Module:

- A quality management system that allows you to monitor the compliance of the system with requirements and standards;

- Tools for auditing and analyzing the quality of the system.

5. Security module:

- Functions of data encryption and protection against unauthorized access;

- System security monitoring functions;

- Data backup functions.

6. Project management module:

- Software version control system;

- Task management system

- Tools for planning, controlling and tracking development progress;

- Documentation management system and regular project status reports.

These components can be developed as independent modules that can be linked and integrated into the overall system. When developing the level of support, one should take into account the needs and characteristics of medical activities, as well as the requirementsto the safety, quality and compatibility of the system.

4. Characteristics of the object of study

The object of study in this system is the work of the human nervous system and muscles, as well as the possibility of their diagnosis and monitoring using an EMG device. This object is characterized by the following characteristics[5]:

1. Dynamic nature: the work of the human nervous system and muscles changes over time, so continuous monitoring of the state is required.

2. Complexity: The human nervous system and muscles are made up of many different elements that interact with each other. This makes it difficult to understand their work and find ways to diagnose and monitor.

3. Need for Accuracy: Mistakes in diagnosis and monitoring can lead to serious health consequences for the patient.[6]

As a device is developed, the mathematical model is an important tool for analyzing and understanding how the nervous system and muscles work. It allows you to simulate the operation of these systems and explore their behavior under various conditions.

For example, in this work, one of the functions of the device is continuous monitoring of the state of the nervous system and muscles during operations, for the analysis and processing of data collected by the device, a mathematical model can be used based on the use of functions that describe the dependence of electrical signals on time . This model can help in determining the required signal level for the normal functioning of the nervous system and muscles, as well as in determining the abnormal level of this level, which may indicate a violation of the system and the need for intervention.

A typical EMG recording is shown in Figure 2.

Figure 2 - Typical Surface EMG

To estimate the spatio-temporal parameters of electrical activity, methods such as frequency, spectral-coherent and correlation analysis are widely used.

Frequency analysis allows you to decompose a complex curve of electrical activity of the brain into component frequency components, and obtain a spectrum of bioelectrical brain oscillations, highlight and quantify the frequency components of EMG.[7]

Spectral analysis determines not only the severity of various rhythmic components in a complex EMG, but also their ratio, allows you to obtain information about the total power of the EMG spectrum and its frequency components. Typically, the results of the analysis are presented in the form of graphs of power spectral density, graphs of amplitude spectra, topographic maps, as well as various quantitative indicators in tabular form.

Coherent analysis determines the statistical relationship between the fluctuations of biopotentials occurring in different parts of the brain, which reflect the degree of synchronism of EMG changes at two different points in the frequency domain (for nearby and distant brain regions within each of the hemispheres and for the same-name brain regions of the right and left hemispheres), and cross-correlation - in time.

Let's simulate the EMG signal using a mathematical model based on the use of functions that describe the dependence of electrical signals on time, for this we use the LabView software package. The result is shown in Figure 3.

Figure 3 - Results of experimental studies