scholarly journals Kalman-Filtering-Based Joint Angle Measurement with Wireless Wearable Sensor System for Simplified Gait Analysis

2011 ◽  
Vol E94-D (8) ◽  
pp. 1716-1720 ◽  
Author(s):  
Hiroki SAITO ◽  
Takashi WATANABE
Keyword(s):  
Gait Analysis ◽  
Kalman Filtering ◽  
Joint Angle ◽  
Angle Measurement ◽  
Sensor System ◽  
Wearable Sensor

Graphene Film Based Wireless and Flexibly Wearable Sensor for Human Joint Angle Measurement

2021 ◽  
Author(s):  
Rongguo Song ◽  
Zelong Hu ◽  
Shaoqiu Jiang ◽  
Li Ma ◽  
Qingsong Ai ◽  
...  
Keyword(s):  
Joint Angle ◽  
Graphene Film ◽  
Angle Measurement ◽  
Wearable Sensor ◽  
Human Joint

613 Development of a Wearable Sensor System for Gait Analysis

2006 ◽  
Vol 2006.6 (0) ◽  
pp. 23-24
Author(s):  
Tao LIU ◽  
Yoshio INOUE ◽  
Kyoko SHIBATA
Keyword(s):  
Gait Analysis ◽  
Sensor System ◽  
Wearable Sensor

A Compact Low Cost Wearable Sensor System for Quantitative Gait Measurement

2014 ◽  
Vol 627 ◽  
pp. 212-216
Author(s):  
Ming Gui Tan ◽  
Cheng Boon Leong ◽  
Jee Hou Ho ◽  
Hui Ting Goh ◽  
Hoon Kiat Ng
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Vision System ◽  
Low Cost ◽  
Sensor System ◽  
Wearable Sensor ◽  
Gait Parameters ◽  
Emg Electrodes ◽  
3D Motion Capture ◽  
Quantitative Gait Analysis

The demand for quantitative gait analysis increases due to increasing number of neurological disorder patients. Conventional gait analysis tools such as 3D motion capture systemsare relatively expensive. Therefore, there is a need to develop a low cost sensor system to obtain the spatial temporal gait parameters without compromising too much on the accuracy. This paper describesthe development of a wearable low cost sensor system which consists ofrelatively less sensing elements with 2 accelerometers, 4 force sensitive resistors (FSR) and 2 EMG electrodes. Thesensor output was validated by a vision system and the relative error was less than 5% formost of the gait parameters measured.

scholarly journals IMU-Based Joint Angle Measurement for Gait Analysis

Sensors ◽  
2014 ◽  
Vol 14 (4) ◽  
pp. 6891-6909 ◽  
Author(s):  
Thomas Seel ◽  
Jörg Raisch ◽  
Thomas Schauer
Keyword(s):  
Gait Analysis ◽  
Joint Angle ◽  
Angle Measurement

scholarly journals A Mechanical Sensor Designed for Dynamic Joint Angle Measurement

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Congo Tak-Shing Ching ◽  
Su-Yu Liao ◽  
Teng-Yun Cheng ◽  
Chih-Hsiu Cheng ◽  
Tai-Ping Sun ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Linear Correlation ◽  
Lower Limb ◽  
Joint Angle ◽  
Intraclass Correlation ◽  
Reliability And Validity ◽  
Angle Measurement ◽  
Joint Angles ◽  
Rehabilitation Programs ◽  
Analysis System

Background. The measurement of the functional range of motion (FROM) of lower limb joints is an essential parameter for gait analysis especially in evaluating rehabilitation programs.Aim. To develop a simple, reliable, and affordable mechanical goniometer (MGR) for gait analysis, with six-degree freedom to dynamically assess lower limb joint angles.Design. Randomized control trials, in which a new MGR was developed for the measurements of FROM of lower limb joints.Setting. Reliability of the designed MGR was evaluated and validated by a motion analysis system (MAS).Population. Thirty healthy subjects participated in this study.Methods. Reliability and validity of the new MGR were tested by intraclass correlation coefficient (ICC), Bland-Altman plots, and linear correlation analysis.Results. The MGR has good inter- and intrarater reliability and validity withICC≥0.93(for both). Moreover, measurements made by MGR and MAS were comparable and repeatable with each other, as confirmed by Bland-Altman plots. Furthermore, a very high degree of linear correlation (R≥0.92for all joint angle measurements) was found between the lower limb joint angles measured by MGR and MAS.Conclusion. A simple, reliable, and affordable MGR has been designed and developed to aid clinical assessment and treatment evaluation of gait disorders.

scholarly journals Wearable Inertial Sensor System towards Daily Human Kinematic Gait Analysis: Benchmarking Analysis to MVN BIOMECH

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2185 ◽  
Author(s):  
Joana Figueiredo ◽  
Simão P. Carvalho ◽  
João Paulo Vilas-Boas ◽  
Luís M. Gonçalves ◽  
Juan C. Moreno ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Real Time ◽  
Joint Angle ◽  
Inertial Sensor ◽  
Party Systems ◽  
Lower Limbs ◽  
Third Party ◽  
Sensor System ◽  
Open Architecture ◽  
Kinematic Gait Analysis

This paper presents a cost- and time-effective wearable inertial sensor system, the InertialLAB. It includes gyroscopes and accelerometers for the real-time monitoring of 3D-angular velocity and 3D-acceleration of up to six lower limbs and trunk segment and sagittal joint angle up to six joints. InertialLAB followed an open architecture with a low computational load to be executed by wearable processing units up to 200 Hz for fostering kinematic gait data to third-party systems, advancing similar commercial systems. For joint angle estimation, we developed a trigonometric method based on the segments’ orientation previously computed by fusion-based methods. The validation covered healthy gait patterns in varying speed and terrain (flat, ramp, and stairs) and including turns, extending the experiments approached in the literature. The benchmarking analysis to MVN BIOMECH reported that InertialLAB provides more reliable measures in stairs than in flat terrain and ramp. The joint angle time-series of InertialLAB showed good waveform similarity (>0.898) with MVN BIOMECH, resulting in high reliability and excellent validity. User-independent neural network regression models successfully minimized the drift errors observed in InertialLAB’s joint angles (NRMSE < 0.092). Further, users ranked InertialLAB as good in terms of usability. InertialLAB shows promise for daily kinematic gait analysis and real-time kinematic feedback for wearable third-party systems.

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