scholarly journals Quaternion Entropy for Analysis of Gait Data

Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 79 ◽  
Author(s):  
Agnieszka Szczęsna
Keyword(s):  
Approximate Entropy ◽  
Dynamical Analysis ◽  
Human Gait ◽  
Nonlinear Dynamical ◽  
Walking Gait ◽  
Powerful Approach ◽  
Time Signals ◽  
Quaternion Signal ◽  
Optical Motion ◽  
Optical Motion Capture

Nonlinear dynamical analysis is a powerful approach to understanding biological systems. One of the most used metrics of system complexities is the Kolmogorov entropy. Long input signals without noise are required for the calculation, which are very hard to obtain in real situations. Techniques allowing the estimation of entropy directly from time signals are statistics like approximate and sample entropy. Based on that, the new measurement for quaternion signal is introduced. This work presents an example of application of a nonlinear time series analysis by using the new quaternion, approximate entropy to analyse human gait kinematic data. The quaternion entropy was applied to analyse the quaternion signal which represents the segments orientations in time during the human gait. The research was aimed at the assessment of the influence of both walking speed and ground slope on the gait control during treadmill walking. Gait data was obtained by the optical motion capture system.

DEVELOPMENT OF MOTION CAPTURE SYSTEM USING DUAL VIDEO CAMERAS FOR THE GAIT DESIGN OF A BIPED ROBOT

2011 ◽  
Vol 08 (02) ◽  
pp. 275-299 ◽  
Author(s):  
JUNG-YUP KIM ◽  
YOUNG-SEOG KIM
Keyword(s):  
Motion Capture ◽  
Human Walking ◽  
Human Gait ◽  
Motion Capture System ◽  
System Calibration ◽  
Walking Gait ◽  
Video Cameras ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

This paper, describes the development of a motion capture system with novel features for biped robots. In general, motion capture is effectively utilized in the field of computer animation. In the field of humanoid robotics, the number of studies attempting to design human-like gaits by using expensive optical motion capture systems is increasing. The optical motion capture systems used in these studies have involved a large number of cameras because such systems use small-sized ball markers; hence the position accuracy of the markers and the system calibration are very significant. However, since the human walking gait is a simple periodic motion rather than a complex motion, we have developed a specialized motion capture system for this study using dual video cameras and large band-type markers without high-level system calibration in order to capture the human walking gait. In addition to its lower complexity, the proposed capture method requires only a low-cost system and has high space efficiency. An image processing algorithm is also proposed for deriving the human gait data. Finally, we verify the reliability and accuracy of our system by comparing a zero moment point (ZMP) trajectory calculated by the motion captured data with a ZMP trajectory measured by foot force sensors.

Non-rigid alignment pipeline applied to human gait signals acquired with optical motion capture systems and inertial sensors

2020 ◽  
Vol 98 ◽  
pp. 109429 ◽  
Author(s):  
Rubén Soussé ◽  
Jorge Verdú ◽  
Ricardo Jauregui ◽  
Ventura Ferrer-Roca ◽  
Simone Balocco
Keyword(s):  
Motion Capture ◽  
Inertial Sensors ◽  
Human Gait ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

Gait Parameters Determination by 2D Optical Motion Analyzer System

2011 ◽  
Vol 83 ◽  
pp. 123-129 ◽  
Author(s):  
Andi Isra Mahyuddin ◽  
Sandro Mihradi ◽  
Tatacipta Dirgantara ◽  
Prisanto N. Maulido
Keyword(s):  
Video Camera ◽  
The Body ◽  
Human Gait ◽  
Maximum Speed ◽  
Normal Walking ◽  
Kinetics Parameters ◽  
Gait Parameters ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Clinical Gait Analysis

In the present work, an optical motion-capture system combined with software for 2D clinical gait analysis is utilized to determine spatiotemporal gait parameters such as stride-length, cadence, cycle-time, and speed as well as joint angles. The developed system consists of a video camera with a maximum speed of 90fps, LED markers, PC and technical computing software, which are developed for tracking markers attached to human body during motion and to calculate kinematics and kinetics parameters of human gait. Gait data of 60 subjects within the age group between 18 to 49 years are measured as part of an effort to develop normal walking database of Indonesian people. In the experiments, the subject is instructed to walk in a specially-arranged measurement area, which is calibrated using the Direct Linear Transformation (DLT) method. Before the measurement, the body posture of each subject is evaluated to ensure normalcy. To validate the system, the obtained gait data is compared to the available normal walking database, and the results obtained by the system show good compatibility.

Rigid Body Guidance of Human Gait as Constrained TRS Serial Chain

2014 ◽  
Author(s):  
Gim Song Soh
Keyword(s):  
Degrees Of Freedom ◽  
Point Of View ◽  
Human Gait ◽  
Synthesis Process ◽  
Dimensional Synthesis ◽  
Two Degrees Of Freedom ◽  
Serial Chain ◽  
Optical Motion ◽  
Musculoskeletal Function ◽  
Optical Motion Capture

The motion of gait is a cyclical activity that requires the coordination between locomotion mechanism, motor control and musculoskeletal function. The basic assumption is that one stride is the same as the next. From a simplified kinematics point of view, the human gait can be considered as a TRS serial chain with six degrees-of-freedom driven by the pelvis rotational and tilting motion during walking. This paper presents a dimensional synthesis procedure for the design of two degrees-of-freedom of spatial eight-bar linkages by mechanically constraining a TRS serial chain. The goal is to develop a methodology for the design of under-actuated lower limb walking devices or passively driven exoskeleton systems. The dimensional synthesis process starts with the specification of the links of a TRS chain according to the gait anthropometric data. We show the various ways how four TS constraints can be used to constrain the links of the this chain to obtain a two degrees-of-freedom spatial eight-bar linkage. We formulate and solve the design equations as well as analyze the resulting eight-bar linkage from the data we obtained from an optical motion capture system. An example demonstrates our results.

scholarly journals An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2869
Author(s):  
Jiaen Wu ◽  
Kiran Kuruvithadam ◽  
Alessandro Schaer ◽  
Richie Stoneham ◽  
George Chatzipirpiridis ◽  
...  
Keyword(s):  
Real Time ◽  
Inertial Sensor ◽  
Neurological Diseases ◽  
Principal Component ◽  
Sampling Frequency ◽  
Powerful Analytical Tool ◽  
Optical Motion ◽  
Analysis System ◽  
Optical Motion Capture ◽  
Gait Monitoring

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

Validation of a Wireless Sensor System for the Estimation of Cumulative Lumbar Loads in Occupational Settings

2021 ◽  
Vol 65 (1) ◽  
pp. 489-494
Author(s):  
Ivan Nail-Ulloa ◽  
Sean Gallagher ◽  
Rong Huangfu ◽  
Dania Bani-Hani ◽  
Nathan Pool
Keyword(s):  
Repeated Measures ◽  
Sensor System ◽  
Wireless Sensor ◽  
Close Correspondence ◽  
Manual Lifting ◽  
Moment Estimates ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Occupational Settings ◽  
Laboratory Models

This study aimed to evaluate the accuracy of 3D L5/S1 moment estimates from a wearable inertial motioncapture system during manual lifting tasks. Reference L5/S1 moments were calculated using inversedynamics bottom-up and top-down laboratory models, based on the data from a measurement systemcomprising optical motion capture and force plates. Nine groups of four subjects performed tasks consistingof lifting and lowering 10 lbs. load with three different heights and asymmetry angles. As a measure ofsystem performance, the root means square errors and absolute peak errors between models werecompared. Also, repeated measures analyses of variance were calculated comparing the means and theabsolute peaks of the estimated moments. The results suggest that most of the estimates obtained from thewireless sensor system are in close correspondence when comparing the means, and more variability isobserved when comparing peak values to other models calculating estimates of L5/S1 moments.

Sign in / Sign up

Export Citation Format

Share Document