Neves Ana Beatriz, Martins Rodrigo, Matela Nuno, Atalaia Tiago
Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal.
Escola Superior De Saúde Da Cruz Vermelha Portuguesa, 1300-125 Lisboa, Portugal.
Bioengineering (Basel). 2023 Oct 8;10(10):1171. doi: 10.3390/bioengineering10101171.
From an early age, people are exposed to risk factors that can lead to musculoskeletal disorders like low back pain, neck pain and scoliosis. Medical screenings at an early age might minimize their incidence. The study intends to improve a software that processes images of patients, using specific anatomical sites to obtain risk indicators for possible musculoskeletal problems. This project was divided into four phases. First, markers and body metrics were selected for the postural assessment. Second, the software's capacity to detect the markers and run optimization tests was evaluated. Third, data were acquired from a population to validate the results using clinical software. Fourth, the classifiers' performance with the acquired data was analyzed. Green markers with diameters of 20 mm were used to optimize the software. The postural assessment using different types of cameras was conducted via the blob detection method. In the optimization tests, the angle parameters were the most influenced parameters. The data acquired showed that the postural analysis results were statistically equivalent. For the classifiers, the study population had 16 subjects with no evidence of postural problems, 25 with mild evidence and 16 with moderate-to-severe evidence. In general, using a binary classification with the train/test split validation method provided better results.
从早年起，人们就接触到可能导致肌肉骨骼疾病（如腰痛、颈痛和脊柱侧弯）的风险因素。早年进行医学筛查可能会降低这些疾病的发病率。该研究旨在改进一款处理患者图像的软件，利用特定解剖部位获取可能存在的肌肉骨骼问题的风险指标。这个项目分为四个阶段。首先，选择标记物和身体指标用于姿势评估。其次，评估软件检测标记物并运行优化测试的能力。第三，从人群中获取数据，使用临床软件验证结果。第四，分析分类器对所获取数据的性能。使用直径为20毫米的绿色标记物来优化软件。通过斑点检测方法，使用不同类型的相机进行姿势评估。在优化测试中，角度参数是受影响最大的参数。所获取的数据表明，姿势分析结果在统计学上是等效的。对于分类器而言，研究人群中有16名受试者没有姿势问题的迹象，25名有轻微迹象，16名有中度至重度迹象。总体而言，使用训练/测试分割验证方法进行二元分类能提供更好的结果。
