FEATURES OF USING DIGITAL SOLUTIONS FOR BIONIC PROSTHESIS CONTROL TASKS

Authors

DOI:

https://doi.org/10.18372/2310-5461.69.20954

Keywords:

digital technologies, bionic prosthesis, limbs, movement identification, servo drive, microcontroller, machine learning

Abstract

The use of digital solutions for bionic prosthesis control tasks, through the use of deep machine learning capabilities, allows us to solve the problems of identifying and formalizing the movement of individual fingers and adequately carry out the process of identifying human hand movements by reading data from a video camera and processing the received data using OpenCV software function libraries in real time. This approach allows us to reproduce the movements of the fingers of a real human hand with the bionic prosthesis while simultaneously using the MediaPipe and OpenCV platform libraries. Identification of the positions of the fingers of the human hand is carried out according to the developed program, the algorithm of which consists of the stages of recognizing the left and right fingers and their placement in two-dimensional space. The output function of this program starts the operation of the servo drives of the bionic prosthesis. Which, in turn, requires the implementation of such an approach in real hardware, which was presented in the specified work. The bionic prosthesis is controlled by transmitting output data via the UART port to the ATMega328 microcontroller, which in turn controls the servo drives of the bionic prosthesis via the SPI interface. A real printed circuit board has been designed, which allowed, using the developed programs, to simulate the movements of a human hand to work out scenarios of its movements for setting up and validating the operation of the servo drives of bionic prostheses. A structural diagram of the proposed control system for a bionic upper limb prosthesis has been developed. The specified system has been designed and a PCB board has been developed, which allowed experimental studies to work out the adequacy of its operation and validate the movements of the fingers of the bionic prosthesis with a real living object in real time.

Author Biographies

Olga Ivanets, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

Doctor of Technical Sciences, Associate Professor, Professor of the Department of Biomedical Engineering

Denys Navrotskyi, State University "Kyiv Aviation Institute", Kyiv, Ukraine

Candidate of Technical Sciences, Associate Professor of the Department of Electronics, Robotics, Monitoring Technologies and Internet of Things

Serhii Levchenko, State University "Kyiv Aviation Institute", Kyiv, Ukraine

Student of the Department of Electronics, Robotics, Monitoring Technologies and Internet of Things

Marina Arkhyrei, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

Senior Lecturer, Department of Biomedical Engineering

References

Bielov S., Zaliskyi M. Review of neural network models for 2d object detection. Science-based technologies. 2025. Vol. 68, No. 4. P. 443–452. https://doi.org/10.18372/2310-5461.68.20280.

Cheng K, Li Z, He Y, Guo Q, Lu Y, Gu S, Wu H. Potential Use of Artificial Intelligence in Infec tious Disease: Take ChatGPT as an Example. Ann Biomed Eng. 2023, Jun; 51(6). РР. 1130–1135. https://doi.org/10.1007/s10439-023-03203-3

Khanal, S. R., Paulino, D., Sampaio, J., Barroso, J., Reis, A., & Filipe, V. (2022). A Review on Com puter Vision Technology for Physical Exercise Monitoring. Algorithms, 15(12), 444. https://doi.org/ 10.3390/a15120444.  О. Б. Іванець, Д. О.Навроцький, С. В. Левченко та ін., 2026 ISSN 2075-0781 (Print), ISSN 2310-5461 (Online) Наукоємні технології № 1(69), 2026 137

Boucher, E. M., Harake, N. R., Ward, H. E., Stoeckl, S. E., Vargas, J., Minkel, J., Zilca, R. (2021). Artificially intelligent chatbots in digital mental health interventions: a review. Expert Re view of Medical Devices, 18(sup1), 37–49. https://doi.org/10.1080/17434440.2021.2013200

Масюк І. В., Богомолов І. Ф. Синергія біоме дицини та штучного інтелекту: роль чат-ботів у трансформації медичної діагностики та догляду за пацієнтами. Biomedical Engineering and Tech nology Issue 13(1) 2024. https://doi.org/10.20535/ 2617-8974.2024.13.300747.

Іванець, О., Хращевський, Р., & Свєженець, В. (2025). Особливості використання СhatGPT для завдань обробки біомедичних даних. Measuring and computing devices in technological processes, (1), 302–309.https://doi.org/10.31891/2219-9365 2025-81-37

Eremenko V. S. Burichenko M. Yu., Ivanets O. B. (2020). Method of processing the results of meas urements of medical indicators. Science-intensive technologies. 47, № 3. Р. 392–398. https://doi.org/ 10.18372/2310-5461.47.14937.

Ortiz-Catalan M. Engineering and surgical ad vancements enable more cognitively integrated bi onic arms. Sci Robot. 2021. № 6(58): eabk3123. https://doi.org/10.1126/scirobotics.abk3123.

S. Bhoyar, R. Motghare, S. Daronde. A Review on Advancing Prosthetics with Artificial Intelligence: Enhancing Control, Sensory Feedback, and Adapt ability. 2025 8th International Conference on Trends in Electronics and Informatics (ICOEI). 2025, pp. 1737–1744, https://doi.org/10.1109/ ICOEI65986.2025.11013772.

D. K. Luu et al. Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface. IEEE Transactions on Biomedi cal Engineering, vol. 69, no. 10, pp. 3051–3063. https://doi.org/10.1109/TBME.2022.3160618.

K. Bhakta, J. Camargo, L. Donovan, K. Herrin and A. Young, "Machine Learning Model Compari sons of User Independent & Dependent Intent Recognition Systems for Powered Prostheses," in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 5393–5400, Oct. 2020, https://doi.org/ 10.1109/TNSRE.2024.3365201.

https://mediapipe.org/.

Published

2026-04-27

How to Cite

Ivanets, O., Navrotskyi, D., Levchenko, S., & Arkhyrei, M. (2026). FEATURES OF USING DIGITAL SOLUTIONS FOR BIONIC PROSTHESIS CONTROL TASKS. Science-Based Technologies, 69(1), 131–138. https://doi.org/10.18372/2310-5461.69.20954

Issue

Section

Ecology, chemical technology, biotechnology, bioengineering