Background: Low back pain during pregnancy is very common and thermography seems to be a promising method of evaluation for pregnant women, because it is painless and safe. The aim of the present study was to evaluate low back pain, during pregnancy, using thermography together with artificial intelligence.
Methods: A cross-sectional study was carried out with pregnant women recruited from a university hospital. The following data were collected: (a) clinical data; (b) physical assessment with mobility and low back pain provocation tests; and (c) thermograms acquisitions, in a controlled environment. Artificial intelligence and the statistical tests were used to compare the groups' mean: with low back pain (LBP) and without low back pain (WLBP).
Results: Thirty pregnant women took part, with fifteen in each group. The mean ± Standard Deviation temperature of the lumbar region in both groups were 32.7 ± 1.05 °C and 32.6 ± 1.01 °C for LBP and WLBP, respectively. There was not any difference in temperature between the groups; however, the artificial intelligence software found thermogram differences between groups; furthermore, the correlation between pain intensity and functionality was found.
Conclusion: Thermography associated with artificial intelligence analyses demonstrated to be a promising method as an adjunct to clinical evaluation.
Keywords: Low back pain; Pregnancy; Thermography.
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