ArticleScientific reports2023
Initial study on an expert system for spine diseases screening using inertial measurement unit.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Deep learning based screening and regular assessment of adolescent idiopathic scoliosis using wearable IMU sensors.Frontiers in bioengineering and biotechnology · 2026Article
- Key Fundamentals and Examples of Sensors for Human Health: Wearable, Non-Continuous, and Non-Contact Monitoring Devices.Sensors (Basel, Switzerland) · 2025Article
- Validation of the EmotiBit wearable sensor for heart-based measures under varying workload conditions.Frontiers in neuroergonomics · 2025Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent times, widely understood spine diseases have advanced to one of the most urgetn problems where quick diagnosis and treatment are needed. To diagnose its specifics (e.g. to decide whether this is a scoliosis or sagittal imbalance) and assess its extend, various kind of imaging diagnostic methods (such as X-Ray, CT, MRI scan or ST) are used. However, despite their common use, some may be regarded as (to a level) invasive methods and there are cases where there are contraindications to using them. Besides, which is even more of a problem, these are very expensive methods and whilst their use for pure diagnostic purposes is absolutely valid, then due to their cost, they cannot rather be considered as tools which would be equally valid for bad posture screening programs purposes. This paper provides an initial evaluation of the alternative approach to the spine diseases diagnostic/screening using inertial measurement unit and we propose policy-based computing as the core for the inference systems. Although the methodology presented herein is potentially applicable to a variety of spine diseases, in the nearest future we will focus specifically on sagittal imbalance detection.
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