目的 针对目前青少年特发性脊柱侧弯（AIS）筛查中X线辐射大、手持仪器主观性强及功能评估缺失的问题,设计一种集成“背部深度形态-足底压力中心-表面肌电”的多模态无辐射筛查系统。方法 硬件端采用间接飞行时间（iToF）深度相机获取背部三维点云,配合压电式压力阵列与差分肌电模块,通过统一时间戳机制实现多源数据毫秒级同步;从软件端提出一种基于最小能量法的动态中线追踪与躯干旋转角（ATR）估计算法,并结合压力中心（COP）稳定性与肌电对称指数（SI）构建自适应风险分级模型。结果 实验表明,该系统能够以30 fps的帧率同步采集三类模态数据,ATR测量值与标准量具误差小于2°;在受试者姿态晃动（COP偏移>10 mm）时,融合算法能有效降低误判率,单次筛查流程缩短至90 s以内。结论 本研究实现了一种可量化、可视化的多模态脊柱侧弯初筛方案,不仅提升了筛查效率,还为侧弯的早期风险提示与康复随访提供了客观的功能学依据。
Objective To develop a multimodal, radiation-free screening device combining back depth imaging, plantar pressure monitoring, and back surface electromyography, to address current issues in adolescent idiopathic scoliosis （AIS） screening, including high X-ray irradiation, strong subjectivity of handheld devices, and lack of functional assessment. Methods An indirect time of flight （iToF） depth camera for 3D point cloud of the back, a pressure-sensing balance platform, and a high-sampling surface electromyography module were integrated into a hardware architecture with unified triggering and timestamps for multimodal synchronous acquisition at millisecond level. The software pipeline proposed a dynamic midline tracking and angle of trunk rotation （ATR） estimation algorithm based on minimum energy method, and constructed an adaptive risk grading model by integrating centre of pressure （COP） stability and the symmetry index （SI） of electromyography. Results The system synchronously acquired three-modal data at 30 fps, and the error between ATR and standard instrument measurements was less than 2°. The fusion algorithm effectively reduced false positive rates in the case of posture disturbance with COP shift > 10 mm, and a complete screening workflow was achieved within 90 s. Conclusion The proposed quantitative and visualized multimodal scoliosis primary screening system could elevate screening efficiency and provide an objective functional basis for early risk warning and rehabilitation follow-up.
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