Artificial Intelligence and Occupational Therapy

Abstract The utilization of artificial intelligence (AI) in pediatric occupational therapy (OT) has emerged as a promising avenue for enhancing assessment, intervention, and outcomes for children with diverse developmental needs. This article provides a comprehensive review of the current state of AI applications in pediatric OT, highlighting key findings, benefits, challenges, and future directions. AI technologies, including machine learning algorithms, computer vision systems, and wearable sensors, offer innovative approaches to assess children’s motor skills, sensory responses, and cognitive functions objectively and efficiently. AI-driven intervention strategies, such as personalized treatment planning, adaptive task selection, virtual reality environments, and gamified activities, promote engagement, motivation, and skill acquisition among pediatric patients. In addition, AI-powered telehealth platforms enable remote delivery of OT services, real-time monitoring of patient progress, and access to care for underserved populations. However, challenges related to data privacy, ethical decision-making, disparities in access, and therapist education must be addressed to ensure the ethical, effective, and equitable integration of AI into pediatric OT practice. By embracing ongoing research, collaboration, and innovation, pediatric OT practitioners can harness the transformative potential of AI to improve outcomes and quality of life for children and families worldwide.

Authors

Institutions

Publication Details

Journal
SBV Journal of Basic Clinical and Applied Health Science
Published
2025-04-01
DOI
https://doi.org/10.4103/sbvj.sbvj_21_25
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence and Occupational Therapy

Nirvi Sharma
SBV Journal of Basic Clinical and Applied Health Science
Healthcare Systems and Public Health
article

Artificial Intelligence and Occupational Therapy

Nirvi Sharma
article en

Abstract

Abstract The utilization of artificial intelligence (AI) in pediatric occupational therapy (OT) has emerged as a promising avenue for enhancing assessment, intervention, and outcomes for children with diverse developmental needs. This article provides a comprehensive review of the current state of AI applications in pediatric OT, highlighting key findings, benefits, challenges, and future directions. AI technologies, including machine learning algorithms, computer vision systems, and wearable sensors, offer innovative approaches to assess children’s motor skills, sensory responses, and cognitive functions objectively and efficiently. AI-driven intervention strategies, such as personalized treatment planning, adaptive task selection, virtual reality environments, and gamified activities, promote engagement, motivation, and skill acquisition among pediatric patients. In addition, AI-powered telehealth platforms enable remote delivery of OT services, real-time monitoring of patient progress, and access to care for underserved populations. However, challenges related to data privacy, ethical decision-making, disparities in access, and therapist education must be addressed to ensure the ethical, effective, and equitable integration of AI into pediatric OT practice. By embracing ongoing research, collaboration, and innovation, pediatric OT practitioners can harness the transformative potential of AI to improve outcomes and quality of life for children and families worldwide.

SBV Journal of Basic Clinical and Applied Health ScienceVol. 8(2)
Rajasthan Dental College and Hospital (IN)
Openalex Percentile: Top 80%
Healthcare Systems and Public Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Artificial Intelligence and Occupational Therapy — Nirvi Sharma · SBV Journal of Basic Clinical and Applied Health Science (2025) | TGRS Research Map | TGRS