References

rehab

Реабилитология

Journal of Medical Rehabilitation

2949-58732949-5881

IRBIS Publishing House (IRBIS LLC)

10.17749/2949-5873/rehabil.2026.87

rehab-195

Research Article

ОБЗОРНЫЕ СТАТЬИ

REVIEW ARTICLES

Персонализированная реабилитация при расстройстве аутистического спектра: технологии искусственного интеллекта для диагностики, прогнозирования и адаптивных вмешательств

Personalized rehabilitation in autism spectrum disorder: artificial intelligence technologies for diagnosis, prediction, and adaptive interventions

https://orcid.org/0000-0002-7670-6566

Широлапов

И. В.

Shirolapov

I. V.

Широлапов Игорь Викторович, к.м.н., доцент

Scopus Author ID: 35776847200

ул. Чапаевская, д. 89, Самара 443099

Igor V. Shirolapov, PhD, Assoc. Prof.

Scopus Author ID: 35776847200

89 Chapaevskaya Str., Samara 443099

i.v.shirolapov@samsmu.ru

https://orcid.org/0000-0002-0926-8551

Сергеева

М. С.

Sergeeva

M. S.

Сергеева Мария Станиславовна, к.б.н., доцент

Scopus Author ID: 57195917349

ул. Чапаевская, д. 89, Самара 443099

Mariya S. Sergeeva, PhD, Assoc. Prof.

Scopus Author ID: 57195917349

89 Chapaevskaya Str., Samara 443099

https://orcid.org/0000-0003-1709-6195

Захаров

А. В.

Zakharov

A. V.

Захаров Александр Владимирович, к.м.н., доцент

WoS ResearcherID: G-7595-2016

Scopus Author ID: 36115593500

ул. Чапаевская, д. 89, Самара 443099

Alexander V. Zakharov, PhD, Assoc. Prof.

WoS ResearcherID: G-7595-2016

Scopus Author ID: 36115593500

89 Chapaevskaya Str., Samara 443099

Федеральное государственное бюджетное образовательное учреждение высшего образования «Самарский государственный медицинский университет» Министерства здравоохранения Российской ФедерацииРоссияSamara State Medical UniversityRussian Federation

2026

12102026

43243256

2026

Широлапов И.В., Сергеева М.С., Захаров А.В.

Shirolapov I.V., Sergeeva M.S., Zakharov A.V.

Данная работа распространяется под лицензией Creative Commons Attribution 4.0.

This work is licensed under a Creative Commons Attribution 4.0 License.

https://www.rehabilitology.com/jour/article/view/195

Расстройства аутистического спектра (РАС) представляют собой гетерогенную группу нарушений нейроразвития. Проблема диагностики и терапии аутизма характеризуется высокой социальной значимостью и необходимостью разработки эффективных реабилитационных стратегий. Технологии искусственного интеллекта (ИИ) открывают принципиально новые возможности для персонализации реабилитационных вмешательств при РАС. В настоящем обзоре рассматриваются ключевые направления интеграции ИИ в клиническую практику: объективизация диагностики чрез анализ цифровых фенотипов, прогнозирование индивидуальных траекторий развития и ответа на терапию, а также создание адаптивных терапевтических систем. Отдельное внимание уделено ИИ-ассистированным технологиям развития социально-коммуникативных навыков, включая виртуальную реальность и социальную робототехнику. Метааналитические данные подтверждают клиническую пользу ИИ-технологий с умеренно высокими эффектами для социальной коммуникации, распознавания эмоций и адаптивных навыков. Показано, что естественные развивающие поведенческие вмешательства в сочетании с технологиями альтернативной коммуникации демонстрируют устойчивые улучшения спонтанной коммуникации у минимально вербальных пациентов. Обсуждаются перспективы персонализации терапии на основе данных физиологического мониторинга и прогностического моделирования, а также роль телемедицинских технологий и интеллектуальных систем поддержки семей. Анализируются критические вызовы внедрения ИИ-систем: от рисков конфиденциальности до трансляционного разрыва между исследованиями и клинической практикой. В целом максимальная реализация потенциала ИИ в реабилитации пациентов с РАС требует сбалансированного подхода, объединяющего точные и объяснимые алгоритмы, инклюзивный пользовательский дизайн и междисциплинарное сотрудничество с активным вовлечением аутичных лиц и их семей на всех этапах разработки и внедрения передовых технологий.

Autism spectrum disorders (ASDs) represent a heterogeneous group of neurodevelopmental conditions. Diagnosis and treatment of autism carry high social significance, necessitating the development of effective rehabilitation strategies. Artificial intelligence (AI) technologies offer fundamentally new opportunities to personalize rehabilitation interventions in ASD. This comprehensive review examines key directions for AI integration into clinical practice: enhancing diagnostic objectivity through digital phenotyping, predicting individual developmental trajectories and treatment responses, and designing adaptive therapeutic systems. Particular attention is paid to AI-assisted technologies for developing social communication skills, including virtual reality and social robotics. Meta-analytic data confirm the clinical utility of AI technologies, showing moderate-to-large effects for social communication, emotion recognition, and adaptive skills. Naturalistic developmental behavioral interventions, combined with augmentative and alternative communication technologies have been shown to demonstrate sustained improvements in spontaneous communication in minimally verbal patients. The review discusses prospects for personalizing interventions based on physiological monitoring data and prognostic modeling along with the role of telehealth technologies and intelligent family support systems. Critical challenges of AI system implementation are analyzed, ranging from privacy risks to the translational gap between research and clinical practice. Overall, maximizing the potential of AI in ASD rehabilitation requires a balanced approach combining accurate and explainable algorithms, inclusive user design, and interdisciplinary collaboration with active involvement of autistic individuals and their families at all stages of frontier technology development and implementation.

аутизмискусственный интеллектперсонализированная реабилитацияпрогнозированиеречевые нарушениямашинное обучение

autismartificial intelligencepersonalized rehabilitationpredictionspeech disordersmachine learning

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The authors declare that there are no conflicts of interest present.