DOI:https://10.15407/kvt206.04.073
Cybernetics and Computer Engineering, 2021, 4(206)
VOVK М.І., PhD (Biology), Senior Researcher,
Head of Bioelectrical Control & Medical Cybernetics Department
ORCID: 0000-0003-4584-9553, e-mail: vovk@irtc.org.ua; imvovk3940@gmail.com
KUTSIAK О.А., PhD (Engineering),
Senior Researcher of the Bioelectrical Control & Medical Cybernetics Department
ORCID: 0000-0003-2277-7411, e-mail: spirotech85@ukr.net
International Research and Training Center for Information Technologies
and Systems of the NAS of Ukraine and of MES of Ukraine,
40, Acad. Hlushkov av. Kyiv, 03187, Ukraine
MOBILE AI-TECHNOLOGY FOR FORMING THE PERSONALIZED MOVEMENTS REHABILITATION PLAN AFTER A STROKE
Introduction. The consequences of stroke change seriously the quality of life. Especially motor activity suffers. Speech disorders occupy a significant place. The synthesis of effective technologies for restoration of limb movements, fine motor hand, that plays significant role in restoring the speech motor skills, is the urgent scientific and applied task.
Recently, the use of artificial intelligence in medicine has attracted attention. At the same time, mobile technologies are developing. It is considered that artificial intelligence in a smartphone will make the medicine of the future accessible for everybody.
The purpose of the paper is to develop the technology for movement restoration after a stroke that uses the artificial intelligence tool for increasing the effectiveness of rehabilitation process – specialized software module for mobile platforms to assist the user (physician) in the formation of personalized plans at different rehabilitation stages.
Results. The AI-technology for forming the personalized movement training plan to patient after a stroke is developed. This technology uses artificial intelligence tool – the software module for information assistance in forming the plan “MovementRehabStroke 1.0 (MD)” that installed in mobile platforms. This module provides the user with recommended movement training plan based on results of quantitative assessment of movements deficit is determined by software module “MovementTestStroke 1.1 (MD)” and patient general state. This plan may be corrected. The structural and functional model of user (physician) and software module “MovementRehabStroke 1.0 (MD)” interaction, and algorithm for forming the personalized movements rehabilitation plan – recommended and finally user-formed are given.
Conclusions. The usage of artificial intelligence tools reduces the physician error in diagnostic and treatment decisions, prevents complications, reduces the disability risks, improves the quality and widespread usage of medical and rehabilitation services for patients after stroke.
Keywords: stroke, AI-technology, personalized plan, movement training, rehabilitation, diagnostics, software module, structural and functional model, algorithm.
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Received 15.09.2021