AI-Guided Inflatable Neck Brace for Personalized Cervical Support

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Authors: Abderrezaq Chemmami, Lyamine Guezouli, Aymen Ahmed Houasnia, Nabil Djenfi, Mohammed Amine Merzoug, Meriem Outtas, Djallel Eddine Boubiche, Homero Toral-Cruz, Rafael Martínez-Peláez, Francisco Méndez‐Martínez, Manuel May-Alarcón
Cited by: 1
References: 26

Abstract

Many people suffer from cervical disc herniation, which significantly affects the lives of individuals, causing chronic pain and functional limitations. This paper presents the development and evaluation of an AI-powered inflatable neck collar designed to provide personalized and adaptive support for individuals experiencing neck pain, particularly those with disc herniations. The system seamlessly integrates motion sensors, a robust AI model trained on a dataset of MRI scans, and a custom-designed inflatable collar. The AI model accurately detects disc herniations and segments vertebral structures, enabling real-time, targeted inflation adjustments based on the user's unique anatomy, posture, and movements. A user-centered design approach ensures a seamless and intuitive user experience, allowing for personalized profile management, control over inflation levels, and data logging for tracking progress. Extensive simulations using 3D models and real-time data flow systems validated the effectiveness of the AI-guided system. Results demonstrated accurate detection and segmentation of disc herniations, robust real-time response, and adaptability to user needs. The proposed system, reviewed and validated by a neurosurgeon, demonstrates significant potential as a novel and effective solution for personalized treatment of neck pain, particularly in cases of disc herniation. Further development and research will focus on expanding the dataset to improve fairness and accuracy for diverse demographics and increasing the robustness and generalizability of the system.

Fields of Study & Subjects

Medical Imaging and Analysis Stroke Rehabilitation and Recovery Cervical and Thoracic Myelopathy

Publication details

Journal / source
Sensors
Publisher
MDPI AG
Volume
26
Issue
10
Pages
2928–2928
Publication date
7 May 2026
Language
EN