步态分析智能鞋垫预测胫骨骨折不愈合风险数据集

数据集获取（Figshare）

• 源站标题：Data Sheet 1_Gait analysis with smart insoles can identify patients at risk of tibial shaft fracture nonunion as early as six weeks after surgery: longitudinal and cross-sectional study.pdf
• DOI：10.3389/fbioe.2025.1536738.s001
• 发布日期：2025-06-25
• 文件数：1 个
• 文件总体积：563.36 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Gait_analysis_with_smart_insoles_can_identify_patients_at_risk_of_tibial_shaft_fracture_nonunion_as_early_as_six_weeks_after_surgery_longitudinal_and_cross-sectional_study_pdf/29399585

命令行下载

curl -L -o "Data Sheet 1_Gait analysis with smart insoles can identify patients at risk of tibial shaft fracture nonunion as early as six weeks after surgery: lon.pdf" "https://ndownloader.figshare.com/files/55628252"

文件清单

• Data Sheet 1_Gait analysis with smart insoles can identify patients at risk of tibial shaft fracture nonunion as early as six weeks after surgery: lon.pdf（563.36 KB）

文件总体积 563.36 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

BackgroundNonunion, a common and detrimental complication of tibial shaft fractures, is usually diagnosed via X-ray-based imaging. Unfortunately, it often takes months of observation until the indication for revision surgery or other interventions is given, which is why additional methods are desirable to enhance the ability to predict and prevent nonunion earlier.
ObjectiveAs gait patterns and subjective outcomes obtained by questionnaires improved during regular fracture healing, the aim of this study was to determine whether gait analyses with instrumented insoles and patient-reported outcome measurement information system (PROMIS) questionnaires could be used to detect patients at risk of developing nonunion during the healing phase after tibial shaft fracture.
MethodsData were collected from a longitudinal and a cross-sectional tibial fracture cohort via gait analysis with instrumented insoles (OpenGO, Moticon GmbH, Munich, Germany) and in addition via PROMIS questionnaires. The gait parameters included pressure, temporal, angular velocity and acceleration-related parameters. The PROMIS covered the global health, physical function and pain questionnaires. Comparisons between patients with and without union were performed at 1 week, 6 weeks, 3 months and 6 months after surgery.
ResultsSix-month postoperative radiographs revealed nonunion in seven of 18 longitudinally assessed patients and in four patients who underwent a single assessment after nonunion diagnosis. Overall gait patterns, primarily reflected by temporal and pressure distribution parameters, differed significantly between patients with and without union from 6 weeks onward. These differences between union and nonunion patients were detected via gait patterns significantly earlier than by radiographs or PROMIS questionnaires. In detail, 6 weeks after surgery, 16 out of the 33 gait parameters were significantly different between the longitudinal union and longitudinal nonunion groups. Three months after surgery, the center of pressure width (p = 0.022), stride time (p = 0.035), stride frequency (p = 0.008), maximal angular velocity (p = 0.014), and asymmetry of the maximal angular velocity (p = 0

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fbioe.2025.1536738.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Gait_analysis_with_smart_insoles_can_identify_patients_at_risk_of_tibial_shaft_fracture_nonunion_as_early_as_six_weeks_after_surgery_longitudinal_and_cross-sectional_study_pdf/29399585）。