Abstract: Heat-sensitive moxibustion can enhance therapeutic outcomes by eliciting propagated sensation along meridians (PSM) and facilitating the arrival of qi at the affected site. It is widely used for analgesia, functional regulation, and chronic disease rehabilitation. However, the technique is highly experience-dependent and individualized. Current assessments of practitioner skill rely largely on direct expert observation and subjective judgment. Consequently, evaluation criteria remain poorly defined, scores are susceptible to rater bias, and technical performance is difficult to quantify objectively. Moreover, practitioners must dynamically adjust the moxibustion location, stimulation area, and movement rhythm according to patients’ heat-sensitization responses. Assessment methods based on trajectory-shape matching or static-template matching may therefore incorrectly classify clinically appropriate individualized adaptations as performance errors. To address these limitations, this study proposes an objective scoring method that integrates expert knowledge with multidimensional kinematic features, drawing on acupoint heat-sensitization theory and clinical practice. Three-dimensional motion trajectories of the moxa stick were analyzed using a multidimensional framework encompassing spatial control, movement rhythm, and procedural timing. Technique-specific assessment strategies were developed to accommodate differences in movement patterns among moxibustion techniques. A scoring model based on a modified cumulative distribution function was then constructed. A scale parameter was introduced to control the model’s sensitivity to deviations in individual metrics, allowing feature deviations expressed in different units to be mapped to normalized component and composite scores. The method was validated using an in-house dataset comprising 108 motion-trajectory samples representing four techniques: circling moxibustion, sparrow-pecking moxibustion, stationary suspended moxibustion, and round-trip meridian moxibustion. The mean absolute errors (MAEs) between the model-generated scores and expert reference scores ranged from 0.037 to 0.059, while the corresponding intraclass correlation coefficient (ICC) values, calculated using ICC(3,1), ranged from 0.757 to 0.860, indicating good scoring accuracy and reliability across all four techniques. The proposed method also achieved lower overall scoring errors and more stable performance than several comparison methods based on time-series matching or trajectory similarity. These findings indicate that the method can objectively quantify adherence to moxibustion procedural standards while providing component-level scores with clear practical meaning, thereby offering a reliable and interpretable digital assessment framework for practical training, skill assessment, and performance feedback in heat-sensitive moxibustion.

摘要： 热敏灸通过诱发经络感传及气至病所反应，能够显著提升艾灸疗效，已在镇痛、功能调节及慢性病康复等领域得到广泛应用。然而，热敏灸操作具有较强的经验性和个体化特征，现有技能评估主要依赖专家现场观察与主观判断，存在评价标准模糊、结果易受主观因素影响以及操作质量难以客观量化等问题。此外，热敏灸强调根据患者热敏反应动态调整施灸位置、范围和节律，若采用轨迹形状匹配或静态模板匹配进行评价，容易将临床上合理的个体化调整判定为操作偏差。针对上述挑战，本文以腧穴热敏化理论和临床施灸经验为支撑，面向热敏灸实践教学与技能考核，提出一种融合专家经验与多维运动特征的客观评分方法。该方法以施灸过程中灸条的三维运动轨迹为分析对象，构建涵盖空间控制、运动节律和操作时序的多维评价体系，并针对不同灸法在操作特征上的差异，采用与运动模式相适应的差异化评价策略。在此基础上，构建基于修正累积分布函数的评分模型，利用评分尺度参数调节模型对不同指标偏差的响应程度，将不同量纲的特征偏差统一映射为归一化得分，实现各维度分项评分与综合评分。为验证所提方法的有效性，在108组涵盖回旋灸、雀啄灸、悬灸和循经往返灸四种典型灸法的自建数据集上开展实验。实验结果表明，所提方法评分与人工参照评分之间的MAE为0.037～0.059，ICC(3,1)为0.757～0.860，在不同灸法上均表现出较好的评分准确性和一致性。与多种基于时间序列或轨迹相似度匹配的评价方法相比，所提方法整体具有更低的评分误差和更稳定的评价性能。研究结果显示，所提方法能够在客观量化施灸规范程度的同时，提供具有明确操作含义的分项评价结果，可为热敏灸实践教学、技能考核及操作反馈提供稳定、可解释的数字化评价依据。