[Opensim-announcement] OpenSim 4.3, Tutorials for EMG- and IMU-Tracking, OpenSense for IMU data, and more

[Joy P. Ku]

OpenSim 4.3 Available for Download

We are pleased to announce OpenSim 4.3<https://simtk.org/frs/?group_id=91>, the newest version of the OpenSim software. The new software brings improvements that make it easier to use inertial measurement unit (IMU) data and direct collocation methods (Moco) with OpenSim. For example, OpenSim Moco now has tools to track EMG and IMU data, along with new tutorials, as described below. We also fixed several bugs reported by users. Read more about the new features<https://simtk-confluence.stanford.edu:8443/pages/viewpage.action?pageId=48988964> and download OpenSim 4.3<https://simtk.org/frs/?group_id=91>



Tutorials for Using OpenSim Moco for EMG- and IMU-Tracking

OpenSim Moco is a software package for solving common problems in simulation biomechanics, such as tracking motion based on experimental data from wearable sensors or optimizing the stiffness of an assistive device. Moco enables researchers to apply state-of-the-art direct collocation optimal control methods to solve these types of problems without requiring numerical expertise. Two new hands-on tutorials are now available that demonstrate how to use Moco to track accelerometer/inertial measurement unit (IMU) signals and perform EMG-driven simulations. Access hands-on tutorials by downloading OpenSim 4.3<https://simtk.org/frs/?group_id=91> and navigating to the folder where you installed OpenSim resources. Read more<https://simtk-confluence.stanford.edu:8443/pages/viewpage.action?pageId=48988964>



Learn more about OpenSense for IMU data and access a new shared dataset

The ability to measure joint kinematics in natural environments over long durations using inertial measurement units (IMUs) could enable at-home monitoring and personalized treatment of neurological and musculoskeletal disorders. However, drift, or the accumulation of error over time, inhibits the accurate measurement of movement over long durations. We sought to develop an open-source workflow to estimate lower extremity joint kinematics from IMU data that was accurate, and capable of assessing and mitigating drift. We developed OpenSense (in OpenSim) and computed IMU-based estimates of kinematics using sensor fusion and an inverse kinematics approach with a constrained biomechanical model. We compared IMU- with optical-based estimates of kinematics from 11 subjects as they performed two 10-minute trials: walking and a repeated sequence of varied lower-extremity movements. Read the preprint<https://www.biorxiv.org/content/10.1101/2021.07.01.450788v1> | Access OpenSense by downloading OpenSim<https://simtk.org/frs/?group_id=91> |  View the data<https://simtk.org/projects/opensense_val>



An Open-source and Wearable System for Measuring 3D Human Motion in Real-time

Want to monitor human movement in the wild? We've developed OpenSenseRT, a wearable motion capture system that uses IMUs and OpenSim to compute joint kinematics in real-time, building on the OpenSense tools discussed in the news item above. The system is low-cost ($100-$300), lightweight (400g), open-source, customizable, simple to build (no soldering or coding), and has similar accuracy to commercial systems. Read the paper<https://ieeexplore.ieee.org/document/9512410> | Read SimTK Instructions<https://simtk-confluence.stanford.edu/display/OpenSim/Wearable+and+Real-time+Kinematics+Estimates+with+OpenSense> | View the demo<https://youtu.be/aYc-mX_-NAA> | View the assembly<https://youtu.be/9cg7VGpuxHU> | SimTK Repo<https://simtk.org/projects/realtimekin>



Wu Tsai Human Performance Alliance at Stanford Seeking Software Engineer

Do you want to be a key contributor to an award-winning, open-source software project whose mission is to transform what we know about human performance? Are you interested in helping athletes of all levels, from elite to beginner, understand how to optimize performance and prevent injury? Are you a full-stack software developer eager to work with world-class researchers and engineers on simulating and analyzing human performance? Join the Digital Athlete team as a software developer. The project is part of the Wu Tsai Human Performance Alliance at Stanford<https://humanperformance.stanford.edu/>. Apply now<https://careersearch.stanford.edu/jobs/software-engineer-13659>



Attend a Course on Wearable Sensors in Rehabilitation: Tracking for the Future

Course runs October 26-27, 2021

This course, being co-taught by C-STAR<https://www.sralab.org/cstar> and the Restore Center<https://restore.stanford.edu> at Stanford, will explore basic principles of using wearable sensors to effectively measure biometrics such as muscle health, movement, and vital signs in a rehabilitation population. First, we will review how common wearable sensors work and what they measure. Next, we will explore 3 research/clinical applications where wearable sensors were actively employed using IMU or EMG features. Finally, participants will have the opportunity to discuss potential approaches to using wearable devices to answer their own clinical or research questions with our esteemed faculty and peers. Register now<https://www.sralab.org/academy/person-learning/1026-1027-c-star-wearable-sensors-rehabilitation-tracking-future>



Torsion Tool: An Automated Tool for Personalizing Femoral and Tibial Geometries in OpenSim Musculoskeletal Models
The Torsion Tool allows an automatic, fast, and user-friendly way of personalizing femoral and tibial geometry in an OpenSim musculoskeletal model. Personalization is expected to be particularly relevant in pathological populations, as will be further investigated by evaluating the effects on simulation outcomes. This tool was developed by an international collaboration between Amsterdam UMC (Marjolein van der Krogt; Kirsteen Veerkamp, Hulda Jonasdottir), KU Leuven (Bryce Killen) and University of Vienna (Hans Kainz). The Matlab tool is available via the link below and has the advantage that it enables users to modify the neck-shaft angle additionally to the femoral anteversion and tibial torsion angles. The neck-shaft angle and the femoral anteversion angle greatly influence hip joint contact forces as shown in related publication. Read the publication<https://www.sciencedirect.com/science/article/pii/S0021929021003687?via%3Dihub> | View the Matlab tool<https://simtk.org/projects/torsiontool> | Read the related publication<https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0235966>

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Joy P. Ku, PhD
Deputy Director | Wu Tsai Human Performance Alliance at Stanford<https://humanperformance.stanford.edu/>
Director of Education & Communications | Mobilize Center<https://mobilize.stanford.edu/> & Restore Center<https://restore.stanford.edu/>
Stanford University

650.736.8434 | joyku at stanford.edu
Supporting open-source biocomputational resources | OpenSim<https://opensim.stanford.edu/> & SimTK<https://simtk.org/>

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