Suppr超能文献

使用惯性测量单元测量足部角度运动学:实时步态事件检测的可靠标准。

Foot angular kinematics measured with inertial measurement units: A reliable criterion for real-time gait event detection.

机构信息

Department of Mechanical Engineering, University of Alberta, Donadeo Innovation Centre for Engineering, Edmonton, Alberta, T6G-1H9, Canada.

出版信息

J Biomech. 2022 Jan;130:110880. doi: 10.1016/j.jbiomech.2021.110880. Epub 2021 Nov 27.

Abstract

Accurate and reliable real-time detection of gait events using inertial measurement units (IMUs) is crucial for (1) developing clinically meaningful gait parameters to differentiate normal and impaired gait or (2) creating patient-tailored gait rehabilitation strategies or control of prosthetic devices using feedback from gait phases. However, most previous studies focused only on algorithms with high temporal accuracy and neglected the importance of (1) high reliability, i.e., detecting only and all true gait events, and (2) real-time implementation. Thus, in this study, we presented a novel approach for initial contact (IC) and terminal contact (TC) detection in real-time based on the measurement of the foot orientation. Unlike foot/shank angular velocity and acceleration, foot orientation provides physiologically meaningful kinematic features corresponding to our observational recognition of IC and TC, regardless of the walking modality. We conducted an experimental study to validate our algorithm, including seven participants performing four walking/running activities. By analyzing 5,555 ICs/TCs recorded during the tests, only our algorithm achieved a sensitivity and precision of 100%. Our obtained temporal accuracy (mean ± standard deviation of errors ranging from 0 ± 3 to 6 ± 5 time samples; sampling frequency: 100 Hz) was better than or comparable to those reported in the literature. Our algorithm's performance does not depend on thresholds and gait speed/modality, and it can be used for feedback-based therapeutic gait training or real-time control of assistive or prosthetic technologies. Nevertheless, its performance for pathological gait must be validated in the future. Finally, we shared the codes and sample data on https://www.ncbl.ualberta.ca/codes.

摘要

使用惯性测量单元(IMU)准确可靠地实时检测步态事件对于(1)开发具有临床意义的步态参数以区分正常和受损步态,或(2)使用步态相位的反馈为患者量身定制步态康复策略或控制假肢设备至关重要。然而,大多数先前的研究仅关注具有高时间准确性的算法,而忽略了(1)高可靠性,即仅检测和检测所有真实的步态事件,以及(2)实时实现的重要性。因此,在这项研究中,我们提出了一种基于脚部方向测量的实时初始接触(IC)和终端接触(TC)检测的新方法。与脚/小腿角速度和加速度不同,脚的方向提供了与我们对 IC 和 TC 的观察识别相对应的生理上有意义的运动学特征,而与行走方式无关。我们进行了一项实验研究来验证我们的算法,包括 7 名参与者进行的 4 种行走/跑步活动。通过分析测试中记录的 5555 个 IC/TC,只有我们的算法达到了 100%的灵敏度和精度。我们获得的时间准确性(误差的平均值±标准偏差范围为 0±3 到 6±5 个时间样本;采样频率:100 Hz)优于或可与文献报道的相媲美。我们的算法的性能不依赖于阈值和步态速度/模式,可用于基于反馈的治疗性步态训练或辅助或假肢技术的实时控制。然而,其在病理性步态中的性能必须在未来得到验证。最后,我们在 https://www.ncbl.ualberta.ca/codes 上分享了代码和示例数据。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验