Study on IoT based automated paralysis patient healthcare system

Internet of Things (IoT) and Artificial Intelligence (AI) integration has transformed healthcare using improved patient monitoring, assistive technology, and voice pathology. This study discusses IoT real-time health monitoring, gesture-based automated reminders, and assistive gesture-based devices for providing a healthy life for the handicapped. Machine learning algorithms such as SVM, CNN, and BiLSTM exhibit excellent accuracy in diagnosis of voice pathology, while homecare robotic systems (HRS) provide rehabilitation and daily care support. Though there has been an improvement, data security, cost-effectiveness, and real-time processing problems still persist, and hence it is important to integrate blockchain-based security and cost-effective approaches. Future research needs to ensure scalability, security, and real-time AI automation in order to make wider availability and improved healthcare outcomes possible.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.17223968
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Study on IoT based automated paralysis patient healthcare system

Zenodo (CERN European Organization for Nuclear Research)
Assembly Line Balancing Optimization
article

Study on IoT based automated paralysis patient healthcare system

article en

Abstract

Internet of Things (IoT) and Artificial Intelligence (AI) integration has transformed healthcare using improved patient monitoring, assistive technology, and voice pathology. This study discusses IoT real-time health monitoring, gesture-based automated reminders, and assistive gesture-based devices for providing a healthy life for the handicapped. Machine learning algorithms such as SVM, CNN, and BiLSTM exhibit excellent accuracy in diagnosis of voice pathology, while homecare robotic systems (HRS) provide rehabilitation and daily care support. Though there has been an improvement, data security, cost-effectiveness, and real-time processing problems still persist, and hence it is important to integrate blockchain-based security and cost-effective approaches. Future research needs to ensure scalability, security, and real-time AI automation in order to make wider availability and improved healthcare outcomes possible.

Zenodo (CERN European Organization for Nuclear Research)
Bharathiar University (IN)
Openalex Percentile: Top 41%
Assembly Line Balancing Optimization
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