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Machine Learning Identifies Chronic Low Back Pain Patients from an Instrumented Trunk Bending and Return Test
03 juillet 2022,
- CeREF Technique
,
- Article scientifique
Article scientifique
Nowadays, the better assessment of low back pain (LBP) is an important challenge, as it is
the leading musculoskeletal condition worldwide in terms of years of disability. The objective of this
study was to evaluate the relevance of various machine learning (ML) algorithms and Sample Entropy
(SampEn), which assesses the complexity of motion variability in identifying the condition of low back
pain. ...
Sample Entropy as a Tool to Assess Lumbo-Pelvic Movements in a Clinical Test for Low-Back-Pain Patients
22 mars 2022,
- CeREF Technique
,
- Article scientifique
Article scientifique
Low back pain (LBP) obviously reduces the quality of life but is also the world’s leading
cause of years lived with disability. Alterations in motor response and changes in movement patterns
are expected in LBP patients when compared to healthy people. Such changes in dynamics may be
assessed by the nonlinear analysis of kinematical time series recorded from one patient’s motion.
Since sample ...