IOT-INTEGRATED ADAPTIVE PAINRELIEF USING THERMAL AND VIBRO-STIMULATION

This abstract presents an intelligent IoT-enabled system developed to enhance chronic and acute pain management through adaptive, personalized therapy. Pain remains a significant clinical challenge due to its subjective nature, variability among individuals, and the limitations of conventional treatment approaches. The proposed system integrates thermal and mechanical stimulation mechanisms, delivering controlled heat and vibration therapy based on real-time physiological and activity data. An embedded microcontroller continuously analyzes sensor inputs such as skin temperature, motion patterns, and usage duration to dynamically adjust therapy parameters. This adaptive control strategy ensures optimized pain relief while maintaining user safety and comfort.The system is designed with IoT connectivity to enable remote monitoring, data logging, and bidirectional communication between users, caregivers, and healthcare professionals. Through a secure cloud platform, therapy sessions can be supervised, historical data can be reviewed, and personalized treatment adjustments can be recommended without requiring frequent clinical visits. This feature makes the solution particularly suitable for home-based care, elderly patients, and individuals with mobility constraints. The modular architecture allows seamless integration of additional sensors or therapeutic modules, enhancing scalability and future upgrades.Experimental validation of the prototype demonstrates stable performance, reliable data transmission, and effective adaptive response under varying operating conditions. User observations indicate improved pain relief consistency, reduced discomfort, and enhanced confidence in self-managed therapy. The system also minimizes the risks associated with excessive heat or vibration through predefined safety thresholds and real-time feedback control. By combining embedded intelligence with IoT-based supervision, the proposed solution bridges the gap between conventional pain relief devices and smart healthcare systems.Overall, this intelligent pain management system offers a cost-effective, non-invasive, and user-centric approach to pain therapy. It supports personalized treatment, continuous monitoring, and remote clinical support, thereby improving therapeutic outcomes and quality of life. The proposed architecture demonstrates strong potential for application in rehabilitation centers, hospitals, and home-care environments, contributing to the advancement of smart healthcare technologies

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-09
DOI
https://doi.org/10.5281/zenodo.20096326
Primary Topic
Infrared Thermography in Medicine
Type
article
Field-Weighted Citation Impact
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article

IOT-INTEGRATED ADAPTIVE PAINRELIEF USING THERMAL AND VIBRO-STIMULATION

R. Bharath, Ms. Sona Mithya J S -, S. Eswaran
Zenodo (CERN European Organization for Nuclear Research)
Infrared Thermography in Medicine
article

IOT-INTEGRATED ADAPTIVE PAINRELIEF USING THERMAL AND VIBRO-STIMULATION

R. Bharath, Ms. Sona Mithya J S -, S. Eswaran
article en

Abstract

This abstract presents an intelligent IoT-enabled system developed to enhance chronic and acute pain management through adaptive, personalized therapy. Pain remains a significant clinical challenge due to its subjective nature, variability among individuals, and the limitations of conventional treatment approaches. The proposed system integrates thermal and mechanical stimulation mechanisms, delivering controlled heat and vibration therapy based on real-time physiological and activity data. An embedded microcontroller continuously analyzes sensor inputs such as skin temperature, motion patterns, and usage duration to dynamically adjust therapy parameters. This adaptive control strategy ensures optimized pain relief while maintaining user safety and comfort.The system is designed with IoT connectivity to enable remote monitoring, data logging, and bidirectional communication between users, caregivers, and healthcare professionals. Through a secure cloud platform, therapy sessions can be supervised, historical data can be reviewed, and personalized treatment adjustments can be recommended without requiring frequent clinical visits. This feature makes the solution particularly suitable for home-based care, elderly patients, and individuals with mobility constraints. The modular architecture allows seamless integration of additional sensors or therapeutic modules, enhancing scalability and future upgrades.Experimental validation of the prototype demonstrates stable performance, reliable data transmission, and effective adaptive response under varying operating conditions. User observations indicate improved pain relief consistency, reduced discomfort, and enhanced confidence in self-managed therapy. The system also minimizes the risks associated with excessive heat or vibration through predefined safety thresholds and real-time feedback control. By combining embedded intelligence with IoT-based supervision, the proposed solution bridges the gap between conventional pain relief devices and smart healthcare systems.Overall, this intelligent pain management system offers a cost-effective, non-invasive, and user-centric approach to pain therapy. It supports personalized treatment, continuous monitoring, and remote clinical support, thereby improving therapeutic outcomes and quality of life. The proposed architecture demonstrates strong potential for application in rehabilitation centers, hospitals, and home-care environments, contributing to the advancement of smart healthcare technologies

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Infrared Thermography in Medicine
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