scholarly journals Real-Time Vertical Ground Reaction Force Estimation in a Unified Simulation Framework Using Inertial Measurement Unit Sensors

Robotics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 88
Author(s):  
Elliot Recinos ◽  
John Abella ◽  
Shayan Riyaz ◽  
Emel Demircan
Keyword(s):  
Real Time ◽  
Inertial Measurement Unit ◽  
Human Motion ◽  
Whole Body ◽  
Measurement Unit ◽  
Ground Reaction Forces ◽  
Inertial Measurement ◽  
Musculoskeletal Models ◽  
Reaction Forces ◽  
Vertical Ground

Recent advances in computational technology have enabled the use of model-based simulation with real-time motion tracking to estimate ground reaction forces during gait. We show here that a biomechanical-based model including a foot-ground contact can reproduce measured ground reaction forces using inertial measurement unit data during single-leg support, single-support jump, side to side jump, jogging, and skipping. The framework is based on our previous work on integrating the OpenSim musculoskeletal models with the Unity environment. The validation was performed on a single subject performing several tasks that involve the lower extremity. The novelty of this paper includes the integration and real-time tracking of inertial measurement unit data in the current framework, as well as the estimation of contact forces using biologically based musculoskeletal models. The RMS errors of tracking the vertical ground reaction forces are 0.027 bodyweight, 0.174 bodyweight, 0.173 bodyweight, 0.095 bodyweight, and 0.10 bodyweight for single-leg support, single-support jump, side to side jump, jogging, and skipping, respectively. The average RMS error for all tasks and trials is 0.112 bodyweight. This paper provides a computational framework for further applications in whole-body human motion analysis.

scholarly journals Open-Source Software Library for Real-Time Inertial Measurement Unit Data-Based Inverse Kinematics using OpenSim

2021 ◽  
Author(s):  
Jere Lavikainen ◽  
Paavo Vartiainen ◽  
Lauri Stenroth ◽  
Pasi Karjalainen
Keyword(s):  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Inverse Kinematics ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Software Library ◽  
Inertial Measurement ◽  
Musculoskeletal Models ◽  
Full Body

Abstract Background: An open-source software library for multithreaded real-time inverse kinematical (IK) analysis of inertial measurement unit (IMU) data using OpenSim was developed. Its operation delays and throughputs were measured with a varying number of IMUs and parallel computing IK threads using two different musculoskeletal models, one a lower-body and torso model and the other a full-body model. Results: Full-body inverse kinematics with data from 12 IMUs could be calculated in real-time with a mean delay below 100 ms and at more than 900 samples per second. Live visualization of IK is an option but results in limited IK throughput. The effect of this limitation was assessed by comparing the range of motion (ROM) of each joint from visualized real-time IK to the ROM from offline IK at IMU sampling frequency, resulting in mean ROM differences below 0.3 degrees. Conclusions: The software library enables real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models, making it possible to do subject-specific full-body motion analysis outside the motion laboratory in real-time.

scholarly journals Portable Gait Lab: Estimating Over-Ground 3D Ground Reaction Forces Using Only a Pelvis IMU

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6363
Author(s):  
Mohamed Irfan Mohamed Refai ◽  
Bert-Jan F. van Beijnum ◽  
Jaap H. Buurke ◽  
Peter H. Veltink
Keyword(s):  
Inertial Measurement Unit ◽  
Center Of Mass ◽  
Calibration Procedure ◽  
Measurement Unit ◽  
Average Error ◽  
Ground Reaction Forces ◽  
Inertial Measurement ◽  
Reaction Forces ◽  
Error State ◽  
Over Ground Walking

As an alternative to force plates, an inertial measurement unit (IMU) at the pelvis can offer an ambulatory method for measuring total center of mass (CoM) accelerations and, thereby, the ground reaction forces (GRF) during gait. The challenge here is to estimate the 3D components of the GRF. We employ a calibration procedure and an error state extended Kalman filter based on an earlier work to estimate the instantaneous 3D GRF for different over-ground walking patterns. The GRF were then expressed in a body-centric reference frame, to enable an ambulatory setup not related to a fixed global frame. The results were validated with ForceShoesTM, and the average error in estimating instantaneous shear GRF was 5.2 ± 0.5% of body weight across different variable over-ground walking tasks. The study shows that a single pelvis IMU can measure 3D GRF in a minimal and ambulatory manner during over-ground gait.

scholarly journals Open-Source Software Library For Real-Time Inertial Measurement Unit Data-Based Inverse Kinematics Using OpenSim

2021 ◽  
Author(s):  
Jere Lavikainen ◽  
Paavo Vartiainen ◽  
Lauri Stenroth ◽  
Pasi Karjalainen
Keyword(s):  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Inverse Kinematics ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Software Library ◽  
Inertial Measurement ◽  
Musculoskeletal Models ◽  
Full Body

Abstract An open-source software library for multithreaded real-time inverse kinematical (IK) analysis of inertial measurement unit (IMU) data using OpenSim was developed. Its operation delays and throughputs were measured with a varying number of IMUs and parallel computing IK threads using two different musculoskeletal models, one a lower-body and torso model and the other a full-body model. Full-body inverse kinematics with data from 12 IMUs could be calculated in real-time with a mean delay below 100 ms and at more than 900 samples per second. Live visualization of IK is an option but results in limited IK throughput. The effect of this limitation was assessed by comparing the range of motion (ROM) of each joint from visualized real-time IK to the ROM from offline IK at IMU sampling frequency, resulting in mean ROM differences below 0.3 degrees. The software library enables real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models, making it possible to do subject-specific full-body motion analysis outside the motion laboratory in real-time.

scholarly journals The relationship between inertial measurement unit-derived ‘force signatures’ and ground reaction forces during cricket pace bowling

2018 ◽  
Vol 19 (3) ◽  
pp. 307-321 ◽  
Author(s):  
Samuel J. Callaghan ◽  
Robert G. Lockie ◽  
Warren A. Andrews ◽  
Robert F. Chipchase ◽  
Sophia Nimphius
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Ground Reaction Forces ◽  
Inertial Measurement ◽  
Reaction Forces ◽  
The Relationship

scholarly journals Predicting Ground Reaction Forces in Sprint Running Using a Shank Mounted Inertial Measurement Unit

Proceedings ◽  
2018 ◽  
Vol 2 (6) ◽  
pp. 199 ◽  
Author(s):  
David V. Thiel ◽  
Jonathan Shepherd ◽  
Hugo G. Espinosa ◽  
Megan Kenny ◽  
Katrien Fischer ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Ground Reaction Forces ◽  
Inertial Measurement ◽  
Sprint Running ◽  
Reaction Forces

scholarly journals Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing Under Optimal Conditions: One Size Does Not Fit All

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2543
Author(s):  
Marco Caruso ◽  
Angelo Maria Sabatini ◽  
Daniel Laidig ◽  
Thomas Seel ◽  
Marco Knaflitz ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Motion Tracking ◽  
Recent Literature ◽  
Human Motion ◽  
Measurement Unit ◽  
Optimal Conditions ◽  
Inertial Measurement ◽  
Rotation Rates ◽  
Significant Performance ◽  
Parameter Values

The orientation of a magneto and inertial measurement unit (MIMU) is estimated by means of sensor fusion algorithms (SFAs) thus enabling human motion tracking. However, despite several SFAs implementations proposed over the last decades, there is still a lack of consensus about the best performing SFAs and their accuracy. As suggested by recent literature, the filter parameters play a central role in determining the orientation errors. The aim of this work is to analyze the accuracy of ten SFAs while running under the best possible conditions (i.e., their parameter values are set using the orientation reference) in nine experimental scenarios including three rotation rates and three commercial products. The main finding is that parameter values must be specific for each SFA according to the experimental scenario to avoid errors comparable to those obtained when the default parameter values are used. Overall, when optimally tuned, no statistically significant differences are observed among the different SFAs in all tested experimental scenarios and the absolute errors are included between 3.8 deg and 7.1 deg. Increasing the rotation rate generally leads to a significant performance worsening. Errors are also influenced by the MIMU commercial model. SFA MATLAB implementations have been made available online.

scholarly journals Real-Time Gait Analysis Using a Single Head-Worn Inertial Measurement Unit

2018 ◽  
Vol 64 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Tong-Hun Hwang ◽  
Julia Reh ◽  
Alfred O. Effenberg ◽  
Holger Blume
Keyword(s):  
Gait Analysis ◽  
Real Time ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement

Development and Implementation of a Novel Digital Shot Sensor System

2013 ◽  
Vol 364 ◽  
pp. 228-232
Author(s):  
Wei Tian Wang ◽  
Quan Jun Song ◽  
Yu Man Nie ◽  
Bu Yun Wang ◽  
Hong Yu Ren ◽  
...  
Keyword(s):  
Real Time ◽  
Information Acquisition ◽  
Inertial Measurement Unit ◽  
Degrees Of Freedom ◽  
Sensor System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Kinetic Information ◽  
Shot Put

Kinetic information acquisition of shot throwing is significant for the train of shot put athletes. This paper presents a novel sensor system based on a 9 degrees of freedom inertial measurement unit, which provides attitude information of shot throwing in real time. The sensor system is designed with modularized structure and installed in the digital shot which has almost the same size and weight as the standard shot for females. A multi-target and multi-parameter information acquisition platform is constructed to acquire kinematics information. With the help of the sensor system, the coaches can combine attitude information with kinematics data to analyze the shot throwing movements.

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