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KMID : 1812820210050020072
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Journal of Korean Dental Hygiene Science
2021 Volume.5 No. 2 p.72 ~ p.79
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Classification Model to Discriminate People with and without Pain in the Lower Back and Lower Limb using Symmetry Data
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Kim Si-Hyun
Jeong Si-Woo
Park Kyue-Nam
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Abstract
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Background: Multiple factors are associated with lower back and lower limb (LB & LL) pain, such as impaired muscle strength, balance, endurance, and motor control, and altered movement patterns. Symmetry of motion, strength and balance are goals for rehabilitation in patients with LB & LL pain. When classifying patients before or during on- and offline assessment, it is necessary that an easy to use functional test be available for clinicians.
Purpose: To establish a classification tree model for discriminating people with and without LB & LL pain during walking using symmetry values from side plank endurance test, hip abductor strength test, one-leg standing time tests and walking tests.
Study design: Cross-sectional study
Methods: A total of 100 subjects with and without LB & LL pain during walking participated. We measured the side plank endurance time, hip abductor strength and one-leg standing time with eyes open and closed, and the sagittal and frontal head angles at comfortable and fast walking speeds using a wearable wireless earbud sensor and calculated the symmetry index (SI) for each test. Classification and regression tree analysis with 10-fold cross validation was used to develop the classification model.
Results: The classification tree had 83% accuracy for discriminating people with and without LB & LL pain during walking. The most important factor for classification was the SI of the one-leg standing time with eyes closed; the second-most important factor was the SI of the frontal head angle during fast walking.
Conclusions: The present classification model can differentiate people with and without LB & LL pain during walking based on symmetry data acquired during functional tests, such as one-leg standing time with the eyes closed and fast walking test using the wearable device. Based on the present results, clinicians can classify patients before and during on- and offline assessments using cutoff values of the SI of the one-leg standing test with eyes closed of 63.88%, and of frontal head motion during a fast-walking test of 63.31%.
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KEYWORD
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Decision tree, Lower back, Lower limb, Pain, Symmetry
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