Publicação
The role of postural and plantar pressure asymmetries predicting pain in aging adults
| Resumo: | Research lacks an integrated approach that incorporates body composition, postural asymmetries, plantar pressure distribution, and sex comparisons to comprehensively understand the complex relationship between these variables and pain levels. The study employed an observational cross-sectional design. The study sample comprised 52 participants of both sexes. The average age of participants was 57.35 years for males and 64.69 years for females. Pain levels were assessed using the numeric pain rating scale. Group comparisons (t-test) and machine learning algorithms were employed for analysis. The results indicated sex differences in height, weight, lean mass percentage, basal metabolism, shoe size, left foot area, podal axis, and distance between foot and body center of pressure (COPs). Significant differences between sexes were also observed in shoulder angles (p = 0.002). Machine learning analysis revealed that neck left deviation and left knee angle were predictive of participants’ pain levels. In conclusion, this study highlights differences in baropodometry and anthropometrics between sexes, with neck deviation and left knee angle identified as predictors of pain levels. |
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| Autores principais: | Dikhtyarenko, Svitlana |
| Outros Autores: | Encarnação, Samuel; Esteves, Dulce; Forte, Pedro |
| Assunto: | Baropodometry Bioimpedance Artificial intelligence Physical suffering |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | Research lacks an integrated approach that incorporates body composition, postural asymmetries, plantar pressure distribution, and sex comparisons to comprehensively understand the complex relationship between these variables and pain levels. The study employed an observational cross-sectional design. The study sample comprised 52 participants of both sexes. The average age of participants was 57.35 years for males and 64.69 years for females. Pain levels were assessed using the numeric pain rating scale. Group comparisons (t-test) and machine learning algorithms were employed for analysis. The results indicated sex differences in height, weight, lean mass percentage, basal metabolism, shoe size, left foot area, podal axis, and distance between foot and body center of pressure (COPs). Significant differences between sexes were also observed in shoulder angles (p = 0.002). Machine learning analysis revealed that neck left deviation and left knee angle were predictive of participants’ pain levels. In conclusion, this study highlights differences in baropodometry and anthropometrics between sexes, with neck deviation and left knee angle identified as predictors of pain levels. |
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