Robotic Systems Integrated with AI for Patient Rehabilitation

Combining robotic systems with artificial intelligence (AI) could completely change the way patients recover by making treatment plans more personalised, effective, and flexible. Robotic-assisted therapy tools are meant to help people with brain disorders, joint conditions, and physical challenges get better faster. By using AI algorithms in these systems, it is possible to constantly analyse patient-specific data like physical growth and unique movement patterns. This lets the robot make real-time changes to treatment plans. The AI system learns from what the patient says and changes the therapy routines so that the patient recovers as quickly as possible with the least amount of pain or damage. This essay looks at how to create and use robotic systems with AI that are used to help patients recover. Some important parts of the technology are its flexibility to react to a patient's physical and mental state, its use of machine learning to make treatment changes on the fly, and its creation of user interfaces that make it easier for patients to get involved. The paper also talks about problems like making sure the system works well, dealing with safety issues, and finding the right balance between technology and human supervision. As therapy becomes more individualised, AI-powered robotic systems can give a more personalised approach, which can speed up healing and improve patients' quality of life. The results of this study show how important AI is for making robotic therapy work better. In the future, these systems may be an important part of healing methods in healthcare.

Authors

Institutions

Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/incet64471.2025.11140272
Citations
6
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
4.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robotic Systems Integrated with AI for Patient Rehabilitation

Abhishek Madankar, Shilpa C. Patil, Monali Gulhane, Nitin Rakesh et al.
6 citations
Medical Imaging and Analysis
4.04
article

Robotic Systems Integrated with AI for Patient Rehabilitation

Abhishek Madankar, Shilpa C. Patil, Monali Gulhane, Nitin Rakesh, Shamla Mantri, Rajashekar T. S, Akhil Gupta
article en
6 citations

Abstract

Combining robotic systems with artificial intelligence (AI) could completely change the way patients recover by making treatment plans more personalised, effective, and flexible. Robotic-assisted therapy tools are meant to help people with brain disorders, joint conditions, and physical challenges get better faster. By using AI algorithms in these systems, it is possible to constantly analyse patient-specific data like physical growth and unique movement patterns. This lets the robot make real-time changes to treatment plans. The AI system learns from what the patient says and changes the therapy routines so that the patient recovers as quickly as possible with the least amount of pain or damage. This essay looks at how to create and use robotic systems with AI that are used to help patients recover. Some important parts of the technology are its flexibility to react to a patient's physical and mental state, its use of machine learning to make treatment changes on the fly, and its creation of user interfaces that make it easier for patients to get involved. The paper also talks about problems like making sure the system works well, dealing with safety issues, and finding the right balance between technology and human supervision. As therapy becomes more individualised, AI-powered robotic systems can give a more personalised approach, which can speed up healing and improve patients' quality of life. The results of this study show how important AI is for making robotic therapy work better. In the future, these systems may be an important part of healing methods in healthcare.

Nagpur Institute of Technology (IN), Symbiosis International University (IN), MIT World Peace University (IN), Krishna Institute of Medical Sciences (IN), Krishna Institute of Medical Sciences Deemed University (IN)
Openalex Percentile: Top 6%
Medical Imaging and Analysis
4.04
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.