PDF(Pubmed)
Abstract：
This research proposes an innovative, intelligent hand-assisted diagnostic system aiming to achieve a comprehensive assessment of hand function through information fusion technology. Based on the single-vision algorithm we designed, the system can perceive and analyze the morphology and motion posture of the patient\'s hands in real time. This visual perception can provide an objective data foundation and capture the continuous changes in the patient\'s hand movement, thereby providing more detailed information for the assessment and providing a scientific basis for subsequent treatment plans. By introducing medical knowledge graph technology, the system integrates and analyzes medical knowledge information and combines it with a voice question-answering system, allowing patients to communicate and obtain information effectively even with limited hand function. Voice question-answering, as a subjective and convenient interaction method, greatly improves the interactivity and communication efficiency between patients and the system. In conclusion, this system holds immense potential as a highly efficient and accurate hand-assisted assessment tool, delivering enhanced diagnostic services and rehabilitation support for patients.
摘要：
这项研究提出了一种创新，智能手辅助诊断系统旨在通过信息融合技术实现手功能的全面评估。基于我们设计的单视觉算法,该系统可以实时感知和分析患者手的形态和运动姿势。这种视觉感知可以提供客观的数据基础，并捕获患者手部运动的连续变化，从而为评估提供更详细的信息，并为后续治疗计划提供科学依据。通过引入医学知识图谱技术,该系统集成和分析医学知识信息，并将其与语音问答系统相结合，即使手功能有限，患者也能有效地沟通和获取信息。语音问答,作为一种主观和方便的交互方法，大大提高了患者与系统之间的交互和沟通效率。总之,该系统作为高效和准确的人工辅助评估工具具有巨大的潜力，为患者提供增强的诊断服务和康复支持。
