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Analyzing Spinal Shape Changes During Posture Training Using a Wearable Device

  • Lower back pain is one of the most prevalent diseases in Western societies. A large percentage of European and American populations suffer from back pain at some point in their lives. One successful approach to address lower back pain is postural training, which can be supported by wearable devices, providing real-time feedback about the user’s posture. In this work, we analyze the changes in posture induced by postural training. To this end, we compare snapshots before and after training, as measured by the Gokhale SpineTracker™. Considering pairs of before and after snapshots in different positions (standing, sitting, and bending), we introduce a feature space, that allows for unsupervised clustering. We show that resulting clusters represent certain groups of postural changes, which are meaningful to professional posture trainers.

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Metadaten
Document Type:Article
Language:English
Parent Title (English):Sensors
Volume:19
Issue:16
First Page:3625
ISSN:1424-8220
URN:urn:nbn:de:hbz:1044-opus-45856
DOI:https://doi.org/10.3390/s19163625
Publisher:MDPI
Date of first publication:2019/08/20
Tag:accelerometer; posture analysis; spinal posture; wearable sensor
Departments, institutes and facilities:Fachbereich Informatik
Institute of Visual Computing (IVC)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 005 Computerprogrammierung, Programme, Daten
Entry in this database:2019/08/23
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International