Integration of Biomechanical Sensor in Spinal Brace for Posture Detection and Correction

Over the past decade, 60% of people have been affected by spinal curvature at some point in their lives. It is a disease of the spine bones such as kyphosis, lordosis, and scoliosis that affects humans and occurs most commonly in adults, although the cause of most childhood cases is unknown. Everyone has some degree of curvature, but when it exceeds about certain degrees, it causes turbulence and difficulty breathing. It is diagnosed by methods such as X-rays and other measurements. It is treated using a variety of techniques, such as Back support requires less adjustment and is more comfortable. This may cause back pain, injury, and ventilation insufficiency for the person wearing the brace. The main goal of our research is to develop a spinal brace with circuits to detect the biomechanical properties of the spine in order to develop innovative and improved functions. The proposed system used for detection spinal curvature angle using biomechanical sensors like IMU and flex sensors. The sensor data is processed by NodeMCU so that the data can be compared with real-time data. When a difference is detected, a signal is passed to a vibrator and it begin alert. Furthermore, the system enhances the automatic correction with pressure cuff mechanism. The developed system overcome the disadvantages of traditional construction methods and proposes a model with high flexibility, strength, durability, and breathability. The system is resulting in less pain, better ventilation, and increased comfort and adjustability. The conclusion marks that the system has better efficiency and effectiveness in usage, which made bridge between gap of clinical and remote assessment

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Publication Details

Published
2025-02-06
DOI
https://doi.org/10.1109/aide64228.2025.10986818
Citations
2
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
1.35
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article

Integration of Biomechanical Sensor in Spinal Brace for Posture Detection and Correction

M. Vasanth, Midhuna Santhosh, C. Sivamani, K Arulmozhi et al.
2 citations
Medical Imaging and Analysis
1.35
article

Integration of Biomechanical Sensor in Spinal Brace for Posture Detection and Correction

M. Vasanth, Midhuna Santhosh, C. Sivamani, K Arulmozhi, V Abinaya
article en
2 citations

Abstract

Over the past decade, 60% of people have been affected by spinal curvature at some point in their lives. It is a disease of the spine bones such as kyphosis, lordosis, and scoliosis that affects humans and occurs most commonly in adults, although the cause of most childhood cases is unknown. Everyone has some degree of curvature, but when it exceeds about certain degrees, it causes turbulence and difficulty breathing. It is diagnosed by methods such as X-rays and other measurements. It is treated using a variety of techniques, such as Back support requires less adjustment and is more comfortable. This may cause back pain, injury, and ventilation insufficiency for the person wearing the brace. The main goal of our research is to develop a spinal brace with circuits to detect the biomechanical properties of the spine in order to develop innovative and improved functions. The proposed system used for detection spinal curvature angle using biomechanical sensors like IMU and flex sensors. The sensor data is processed by NodeMCU so that the data can be compared with real-time data. When a difference is detected, a signal is passed to a vibrator and it begin alert. Furthermore, the system enhances the automatic correction with pressure cuff mechanism. The developed system overcome the disadvantages of traditional construction methods and proposes a model with high flexibility, strength, durability, and breathability. The system is resulting in less pain, better ventilation, and increased comfort and adjustability. The conclusion marks that the system has better efficiency and effectiveness in usage, which made bridge between gap of clinical and remote assessment

Karunya University (IN)
Openalex Percentile: Top 20%
Medical Imaging and Analysis
1.35
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