Suppr超能文献

一种基于足部压力检测与Azure Kinect系统相结合的步态信号采集与参数表征方法

[A gait signal acquisition and parameter characterization method based on foot pressure detection combined with Azure Kinect system].

作者信息

Xu Guofeng, Chen Kai, Yang Ying

机构信息

School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, P. R. China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2023 Apr 25;40(2):350-357. doi: 10.7507/1001-5515.202210026.

Abstract

The gait acquisition system can be used for gait analysis. The traditional wearable gait acquisition system will lead to large errors in gait parameters due to different wearing positions of sensors. The gait acquisition system based on marker method is expensive and needs to be used by combining with the force measurement system under the guidance of rehabilitation doctors. Due to the complex operation, it is inconvenient for clinical application. In this paper, a gait signal acquisition system that combines foot pressure detection and Azure Kinect system is designed. Fifteen subjects are organized to participate in gait test, and relevant data are collected. The calculation method of gait spatiotemporal parameters and joint angle parameters is proposed, and the consistency analysis and error analysis of the gait parameters of proposed system and camera marking method are carried out. The results show that the parameters obtained by the two systems have good consistency (Pearson correlation coefficient ≥ 0.9, < 0.05) and have small error (root mean square error of gait parameters is less than 0.1, root mean square error of joint angle parameters is less than 6). In conclusion, the gait acquisition system and its parameter extraction method proposed in this paper can provide reliable data acquisition results as a theoretical basis for gait feature analysis in clinical medicine.

摘要

步态采集系统可用于步态分析。传统的可穿戴式步态采集系统由于传感器佩戴位置不同,会导致步态参数出现较大误差。基于标记法的步态采集系统成本高昂,且需要在康复医生的指导下与测力系统配合使用。由于操作复杂,不利于临床应用。本文设计了一种结合足底压力检测和Azure Kinect系统的步态信号采集系统。组织了15名受试者参加步态测试,并收集了相关数据。提出了步态时空参数和关节角度参数的计算方法,并对所提系统与相机标记法的步态参数进行了一致性分析和误差分析。结果表明,两种系统获得的参数具有良好的一致性(皮尔逊相关系数≥0.9,<0.05)且误差较小(步态参数的均方根误差小于0.1,关节角度参数的均方根误差小于6)。综上所述,本文提出的步态采集系统及其参数提取方法可为临床医学中的步态特征分析提供可靠的数据采集结果作为理论依据。

相似文献

1
[A gait signal acquisition and parameter characterization method based on foot pressure detection combined with Azure Kinect system].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2023 Apr 25;40(2):350-357. doi: 10.7507/1001-5515.202210026.
2
Ground reaction force and joint moment estimation during gait using an Azure Kinect-driven musculoskeletal modeling approach.
Gait Posture. 2022 Jun;95:49-55. doi: 10.1016/j.gaitpost.2022.04.005. Epub 2022 Apr 9.
3
[Lower limb joint contact forces and ground reaction forces analysis based on Azure Kinect motion capture].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024 Aug 25;41(4):751-757. doi: 10.7507/1001-5515.202311040.
4
Effects of camera viewing angles on tracking kinematic gait patterns using Azure Kinect, Kinect v2 and Orbbec Astra Pro v2.
Gait Posture. 2021 Jun;87:19-26. doi: 10.1016/j.gaitpost.2021.04.005. Epub 2021 Apr 5.
5
Comparison of Azure Kinect overground gait spatiotemporal parameters to marker based optical motion capture.
Gait Posture. 2022 Jul;96:130-136. doi: 10.1016/j.gaitpost.2022.05.021. Epub 2022 May 21.
8
Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study.
PLoS One. 2022 Mar 11;17(3):e0265215. doi: 10.1371/journal.pone.0265215. eCollection 2022.
9
Accuracy of the Microsoft Kinect for measuring gait parameters during treadmill walking.
Gait Posture. 2015 Jul;42(2):145-51. doi: 10.1016/j.gaitpost.2015.05.002. Epub 2015 May 14.
10
Estimation of Ankle Joint Power during Walking Using Two Inertial Sensors.
Sensors (Basel). 2019 Jun 21;19(12):2796. doi: 10.3390/s19122796.

本文引用的文献

1
Total knee arthroplasty improves gait adaptability in osteoarthritis patients; a pilot study.
J Orthop. 2022 Sep 5;34:304-309. doi: 10.1016/j.jor.2022.08.003. eCollection 2022 Nov-Dec.
2
Current applications of gait analysis after total knee arthroplasty: A scoping review.
J Clin Orthop Trauma. 2022 Sep 5;33:102014. doi: 10.1016/j.jcot.2022.102014. eCollection 2022 Oct.
3
High preoperative gait variability is a prognostic predictor of gait and balance in Parkinson disease patients with deep brain stimulation.
Parkinsonism Relat Disord. 2022 Jul;100:1-5. doi: 10.1016/j.parkreldis.2022.05.013. Epub 2022 May 26.
4
Analysing Gait Patterns in Degenerative Lumbar Spine Disease Using Inertial Wearable Sensors: An Observational Study.
World Neurosurg. 2022 Jul;163:e501-e515. doi: 10.1016/j.wneu.2022.04.013. Epub 2022 Apr 8.
7
Postural control assessment via Microsoft Azure Kinect DK: An evaluation study.
Comput Methods Programs Biomed. 2021 Sep;209:106324. doi: 10.1016/j.cmpb.2021.106324. Epub 2021 Aug 4.
8
Kinematic descriptions of upper limb function using simulated tasks in activities of daily living after stroke.
Hum Mov Sci. 2021 Oct;79:102834. doi: 10.1016/j.humov.2021.102834. Epub 2021 Jul 10.
9
Gait Indices for Characterization of Patients with Unilateral Cerebral Palsy.
J Clin Med. 2020 Nov 30;9(12):3888. doi: 10.3390/jcm9123888.
10
Normal pressure hydrocephalus and CSF tap test response: the gait phenotype matters.
J Neural Transm (Vienna). 2021 Jan;128(1):121-125. doi: 10.1007/s00702-020-02270-3. Epub 2020 Oct 26.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验