目的：基于文献计量学梳理惯性测量技术在步态分析领域的研究演进与热点结构，并从护理评估与干预转化角度分析其应用空白。方法：检索 Web of Science 核心合集2005年1月1日至2025年4月5日相关英文文献，纳入1,079篇记录；采用 CiteSpace 6.3.R1、VOSviewer 1.6.20 分析年度发文、国家/地区合作、期刊分布、关键词共现与突现，并在 Python 3.10 中以 PPMI/TF-IDF 表征、SVD降维、UMAP-HDBSCAN聚类开展关键词和摘要语义分析。结果：2006—2024年发文量由1篇增至140篇，年复合增长率为31.6%，2024年达到峰值；最高频关键词为 gait（404次）、gait analysis（268次）、walking（252次）、balance（183次）和 inertial sensors（156次）。关键词与摘要语义聚类的二维轮廓系数分别为0.579和0.642，热点集中于帕金森病/冻结步态、跌倒风险、平衡稳定性、可穿戴传感器、机器学习和康复干预。含 nursing/care 等护理相关词项的记录为142篇，但“护理”尚未形成独立主题簇。结论：惯性测量步态分析已形成医工交叉的成熟热点，但护理主导的连续评估、风险预警和干预闭环仍不足。未来应将步速、步态变异性、稳定性、对称性等参数转化为可执行的护理评估指标，推动精准护理场景中的临床验证与流程整合。
Objective: To map the research evolution and hotspot structure of inertial-measurement-based gait analysis and to examine its translational gap in nursing assessment and intervention. Methods: A total of 1,079 English records published from January 1, 2005 to April 5, 2025 were retrieved from the Web of Science Core Collection. CiteSpace 6.3.R1 and VOSviewer 1.6.20 were used for annual output, collaboration, journal distribution, keyword co-occurrence and burst analyses. Keyword and abstract semantic clusters were further examined in Python 3.10 using PPMI/TF-IDF representation, SVD, UMAP and HDBSCAN. Results: Publications increased from 1 in 2006 to 140 in 2024, with a compound annual growth rate of 31.6%. The most frequent terms were gait, gait analysis, walking, balance and inertial sensors. The two-dimensional silhouette coefficients of keyword and abstract semantic clusters were 0.579 and 0.642, respectively. Major hotspots involved Parkinson disease/freezing of gait, fall risk, balance and stability, wearable sensors, machine learning and rehabilitation. Records containing nursing/care-related terms accounted for 142 publications, but nursing did not form an independent topic cluster. Conclusion: Inertial-measurement-based gait analysis has become a mature medical-engineering research field, while nurse-led continuous assessment, risk warning and intervention feedback loops remain underdeveloped. Translating gait speed, variability, stability and symmetry into actionable nursing indicators should be prioritized in future clinical validation.
