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Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim
BACKGROUND: Inertial measurements (IMUs) facilitate the measurement of human motion outside the motion laboratory. A commonly used open-source software for musculoskeletal simulation and analysis of human motion, OpenSim, includes a tool to enable kinematics analysis of IMU data. However, it only en...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082569/ https://www.ncbi.nlm.nih.gov/pubmed/37038471 http://dx.doi.org/10.7717/peerj.15097 |
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author | Lavikainen, Jere Vartiainen, Paavo Stenroth, Lauri Karjalainen, Pasi A. |
author_facet | Lavikainen, Jere Vartiainen, Paavo Stenroth, Lauri Karjalainen, Pasi A. |
author_sort | Lavikainen, Jere |
collection | PubMed |
description | BACKGROUND: Inertial measurements (IMUs) facilitate the measurement of human motion outside the motion laboratory. A commonly used open-source software for musculoskeletal simulation and analysis of human motion, OpenSim, includes a tool to enable kinematics analysis of IMU data. However, it only enables offline analysis, i.e., analysis after the data has been collected. Extending OpenSim’s functionality to allow real-time kinematics analysis would allow real-time feedback for the subject during the measurement session and has uses in e.g., rehabilitation, robotics, and ergonomics. METHODS: We developed an open-source software library for real-time inverse kinematics (IK) analysis of IMU data using OpenSim. The software library reads data from IMUs and uses multithreading for concurrent calculation of IK. 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. We published the code under an open-source license on GitHub. RESULTS: A standard desktop computer calculated full-body inverse kinematics from treadmill walking at 1.5 m/s with data from 12 IMUs in real-time with a mean delay below 55 ms and reached a throughput of more than 90 samples per second. A laptop computer had similar delays and reached a throughput above 60 samples per second with treadmill walking. Minimal walking kinematics, motion of lower extremities and torso, were calculated from treadmill walking data in real-time with a throughput of 130 samples per second on the laptop and 180 samples per second on the desktop computer, with approximately half the delay of full-body kinematics. CONCLUSIONS: The software library enabled real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models. The performance results show that subject-specific full-body motion analysis is feasible in real-time, while a laptop computer and IMUs allowed the use of the method outside the motion laboratory. |
format | Online Article Text |
id | pubmed-10082569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100825692023-04-09 Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim Lavikainen, Jere Vartiainen, Paavo Stenroth, Lauri Karjalainen, Pasi A. PeerJ Bioinformatics BACKGROUND: Inertial measurements (IMUs) facilitate the measurement of human motion outside the motion laboratory. A commonly used open-source software for musculoskeletal simulation and analysis of human motion, OpenSim, includes a tool to enable kinematics analysis of IMU data. However, it only enables offline analysis, i.e., analysis after the data has been collected. Extending OpenSim’s functionality to allow real-time kinematics analysis would allow real-time feedback for the subject during the measurement session and has uses in e.g., rehabilitation, robotics, and ergonomics. METHODS: We developed an open-source software library for real-time inverse kinematics (IK) analysis of IMU data using OpenSim. The software library reads data from IMUs and uses multithreading for concurrent calculation of IK. 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. We published the code under an open-source license on GitHub. RESULTS: A standard desktop computer calculated full-body inverse kinematics from treadmill walking at 1.5 m/s with data from 12 IMUs in real-time with a mean delay below 55 ms and reached a throughput of more than 90 samples per second. A laptop computer had similar delays and reached a throughput above 60 samples per second with treadmill walking. Minimal walking kinematics, motion of lower extremities and torso, were calculated from treadmill walking data in real-time with a throughput of 130 samples per second on the laptop and 180 samples per second on the desktop computer, with approximately half the delay of full-body kinematics. CONCLUSIONS: The software library enabled real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models. The performance results show that subject-specific full-body motion analysis is feasible in real-time, while a laptop computer and IMUs allowed the use of the method outside the motion laboratory. PeerJ Inc. 2023-04-05 /pmc/articles/PMC10082569/ /pubmed/37038471 http://dx.doi.org/10.7717/peerj.15097 Text en © 2023 Lavikainen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Lavikainen, Jere Vartiainen, Paavo Stenroth, Lauri Karjalainen, Pasi A. Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim |
title | Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim |
title_full | Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim |
title_fullStr | Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim |
title_full_unstemmed | Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim |
title_short | Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim |
title_sort | open-source software library for real-time inertial measurement unit data-based inverse kinematics using opensim |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082569/ https://www.ncbi.nlm.nih.gov/pubmed/37038471 http://dx.doi.org/10.7717/peerj.15097 |
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