Automatic Angle of Trunk Rotation Detection Using 3D Sensor Imaging in Scoliosis Assessment

Abstract

Early detection of adolescent idiopathic scoliosis (AIS) is essential for AIS treatment and prevention of AIS progression. However, the existing clinical scoliosis assessment method, the standing full-column radiographs (X-ray) imaging, is radioactive, making this method unsuitable for large-scale promotion among adolescents. As a result, many countries have implemented school scoliosis screening programs (SSS) to achieve large-scale scoliosis screening and monitoring of adolescents by measuring the angle of trunk rotation (ATR). However, the SSS is time-consuming and inaccurate due to subjective manual examination. In this paper, we present an automatic method to calculate ATR based on the contour curve of the human back. This automatic method begins with a 3D depth sensor-scanned point cloud model of the human back and identifies the spinous process and stress points by obtaining the back contour curve from the depth information. Finally, the ATR is calculated according to the measurement principle of scoliosis meter. We demonstrate the effectiveness of our method using twenty-seven pairs of ATR data from nine participants with AFBT. There is not only a significant positive correlation, but also a convinced level of agreement between ATRs obtained using automatic method and ATRs obtained using manual method in the SSS. The experiment results reveal that the proposed method can efficiently achieve accurate measurement of ATR in the SSS.