Evidence map›Paper›PMID 38653882›Full record

ArticleMedical & biological engineering & computing2024

Design and development of an intelligent wearing system for adolescent spinal orthotics.

Liang Xuan, Luo Lei, Mengqi Shao, Qingkai Han

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Article in Medical & biological engineering & computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
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  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Liang XuanSchool of Intelligent Manufacturing, Jianghan University, Wuhan, 430056, China. xuanl@jhun.edu.cn.ORCID http://orcid.org/0000-0002-8420-3109
Luo LeiSchool of Intelligent Manufacturing, Jianghan University, Wuhan, 430056, China.
Mengqi ShaoSchool of Intelligent Manufacturing, Jianghan University, Wuhan, 430056, China.
Qingkai HanSchool of Mechanical Engineering and Automation, Northeastern University, Shenyang, 110819, China.
Jianghan University · CNNortheastern University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adolescent idiopathic scoliosis is the deformity of the human spine in three-dimensional space. It is a disease with a long course and difficult to recover in a short time. Currently, spinal orthotic braces are an effective non-surgical treatment for this condition. However, existing spinal orthotic braces are still deficient. For example, existing spinal orthotics braces have no way of knowing how correct, effective, and comfortable a patient is wearing the orthotics. Based on distributed pressure monitoring technology, this paper conducts pressure acquisition and compensation research on spinal orthotics used by adolescent patients. After analyzing the principles of orthopedics and selecting monitoring points, this paper selects appropriate sensors and calibrates them. An intelligent wearable system for adolescent spinal orthotics was developed based on these findings. The experimental results show that the system can effectively monitor the process of patients wearing spinal orthotic braces. In addition, the system can compensate and visualize the pressure in real-time, so that doctors and patients can know the process and make judgments and adjustments.

Indexed as

Equipment DesignScoliosisAdolescentBracesHumansOrthotic DevicesPressureSpineWearable Electronic DevicesAdolescent idiopathic scoliosisIntelligent wearable systemPressure monitoringPressure visualizationSpinal orthotics

Identifiers

PMID38653882
OpenAlexW4395072869

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.