ArticleScience progress
Design and research of a wearable system for spinal deformity rehabilitation based on curvature and electromyography sensors.
Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abnormal spinal curvature poses a significant health risk to children and adolescents, highlighting the importance of maintaining good posture for spinal health. However, current posture detection methods face challenges such as insufficient detection accuracy, discomfort during use, and overall inconvenience. This study aims to design and implement a wearable system that integrates angle sensors and surface electromyography (sEMG) sensors to monitor spinal alignment and muscle activity in real-time. The system consists of a smart vest equipped with flexible bending sensors and sEMG electrodes, a microcontroller unit for data processing, and a mobile application for data visualization and user feedback. To validate the system's effectiveness, the study involved 65 eligible undergraduate students wearing the device, collecting sEMG signals under different posture conditions, and conducting posture analysis to evaluate the device's performance. The results showed a significant correlation between asymmetric paraspinal muscle activity and the direction of the spinal curve, with the system achieving an accuracy rate of 90.8% in predicting the curve direction using a logistic regression model. Although the system verifies spinal alignment through indirect measurement rather than direct imaging, the high consistency between sEMG asymmetry and expected biomechanical patterns supports its reliability as a functional screening tool. Wearable devices can provide timely posture correction reminders and personalized rehabilitation plans, offering a noninvasive, user-friendly solution for the prevention and rehabilitation of spinal curvature abnormalities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.