A new method for determining lumbar spine motion using Bayesian belief network
Publication in refereed journal


摘要A Bayesian network dynamic model was developed to determine the kinematics of the intervertebral joints of the lumbar spine. Radiographic images in flexion and extension postures were used as input data for modeling, together with movement information from the skin surface using an electromagnetic motion tracking system. Intervertebral joint movements were then estimated by the graphic network. The validity of the model was tested by comparing the predicted position of the vertebrae in the neutral position with those obtained from the radiographic image in the neutral posture. The correlation between the measured and predicted movements was 0.99 (p < 0.01) with a mean error of less than 1.5 degrees. The movement sequence of the various vertebrae was examined based on the model output, and wide variations in the kinematic patterns were observed. The technique is non-invasive and has potential to be used clinically to measure the kinematics of lumbar intervertebral movement.
著者Ma HT, Yang ZY, Griffith JF, Leung PC, Lee RYW
期刊名稱Medical and Biological Engineering and Computing
出版社Springer Verlag (Germany)
頁次333 - 340
關鍵詞Bayesian belief networks; dynamic modeling; intervertebral kinematics; lumbar spine motion; spine biomechanics
Web of Science 學科類別Computer Science; Computer Science, Interdisciplinary Applications; COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS; Engineering; Engineering, Biomedical; ENGINEERING, BIOMEDICAL; Mathematical & Computational Biology; MATHEMATICAL & COMPUTATIONAL BIOLOGY; Medical Informatics; MEDICAL INFORMATICS

上次更新時間 2020-25-11 於 00:23