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<p class="MsoNormal"><b><span style="color:black">Apply for a Pilot Project Grant of Up to $30,000 </span></b><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><i><span style="color:black">Applications Deadline: October 1, 2021, 5 PM local time</span></i><span style="color:black"><br>
The <a href="http://restore.stanford.edu/" target="_blank">Restore Center</a> seeks proposals for its pilot project program. The program awards seed grants to innovative and meritorious projects that will accelerate the use of sensor and video technology in
rehabilitation research and will advance real-world monitoring and delivery of medical rehabilitation for individuals with impaired movement. Applicants can request up to $30,000 in funding. We encourage all applicants from diverse backgrounds and experiences,
including but not limited to those from underrepresented racial and ethnic groups, as well as those with disabilities, to apply.
<a href="https://restore.stanford.edu/pilot-funding/pilot-project-application/" target="_blank">
Learn more and apply</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Apply to Participate in Virtual Office Hours for Biomechanical Modeling or Machine Learning Research Questions </span></b><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><i><span style="color:black">Application deadline: September 3, 2021, 5 PM local time </span></i><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">We are pleased to announce we will be holding Virtual Office Hours during the weeks of September 13 and September 20, 2021, to support researchers working with wearable sensors, video technology, and other modalities
in rehabilitation research. We will have two tracks: 1) Biomechanical modeling with <a href="https://opensim.stanford.edu/" target="_blank">OpenSim</a> and <a href="https://simtk-confluence.stanford.edu/display/OpenSim/OpenSense+-+Kinematics+with+IMU+Data" target="_blank">IMUs</a> or
video, and 2) Machine learning, including video analysis. All phases of a research project are supported, such as formulating a research question, choosing and planning appropriate methods, and addressing issues with carrying out the study. We welcome and
encourage individuals to apply as a team, if relevant. <a href="https://forms.gle/A6r2ZeZq2goEJJm67" target="_blank">Learn more and apply</a> <o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal" style="background:white"><b><span style="color:black">Webinar: Accelerating Image-Based Knee Osteoarthritis Research Using Deep Learning: Research Examples and Best Practices</span></b><span style="color:black"> <o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><i><span style="color:black">Tuesday, August 17, 2021, at 10:00 AM Pacific Time </span></i><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:black">Using deep learning to automatically assess individuals' disease status from medical images is an active area of research that is poised to change how outcomes are measured in our field.
In this webinar, Kevin Thomas from Stanford University will discuss his research on using deep learning models to automatically analyze knee X-rays and MRIs of individuals with osteoarthritis. His models produced results that agreed with experts as closely
as experts agree with one another. He will also share tips and tricks for conducting machine learning studies in your own research. <a href="https://mobilize.stanford.edu/webinar-accelerating-image-based-knee-osteoarthritis-research-using-deep-learning-research-examples-and-best-practices/" target="_blank">Register
now</a> <o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Software Engineer Opening for Digital Athlete Project<o:p></o:p></span></b></p>
<p class="MsoNormal">The <a href="https://humanperformance.stanford.edu/">Wu Tsai Human Performance Alliance at Stanford
</a> is part of a newly launched six-university alliance with the mission of uncovering the fundamental principles of peak performance. Its Digital Athlete project is creating predictive models to guide the training and treatment for athletes and builds upon
the OpenSim software capabilities. The Alliance at Stanford is seeking a software developer to join its team of world-class researchers and engineers to develop new tools in support of the Digital Athlete project.
<a href="https://careersearch.stanford.edu/jobs/software-engineer-13659">Learn more and apply</a>
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<p class="MsoNormal"><b><span style="color:black">MATLAB Tool for Bone Deformation of Generic OpenSim Models </span></b><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Luca Modenese from Imperial College London, together with Martina Barzan and Chris Carty from Griffith University, have recently released a MATLAB tool that enables researchers and clinicians in the biomechanical
field to easily modify the rotational profile of the lower limb, e.g., femoral anteversion or tibial torsion, of OpenSim models. Examples of use employing popular lower limb models are available at the project links.
<a href="https://doi.org/10.1016/j.gaitpost.2021.06.014"><span lang="EN-GB">Read publication</span></a></span><span lang="EN-GB" style="color:black"> |
</span><span style="color:black"><a href="https://simtk.org/projects/bone_deformity"><span lang="EN-GB">Download tool and scripts from SimTK</span></a>
</span><span lang="EN-GB" style="color:black"> | </span><span style="color:black"><a href="https://github.com/modenaxe/msk-bone-deformation"><span lang="EN-GB">Access code development via GitHub</span></a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Recordings from Symposium on Motion Analysis and Musculoskeletal Modeling in Treatment of Spinal Disorders</span></b><span style="color:black"> <o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Musculoskeletal modeling and simulations represent an attractive approach to non-invasively investigate the relationships between spinal structure and function in terms of position/motion and internal biomechanical
loading. A symposium organized earlier this year by OpenSim researcher awardees Dennis Anderson and Lennart Scheys virtually brought researchers together to discuss the motion analysis techniques themselves, as well as their use in clinical applications and
in evaluating the effects of spinal disorders on motion and loading. <a href="http://biomechanics.engr.uky.edu/content/program" target="_blank">View recordings from these sessions</a> <o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Contribute to Mobile Health and Human Movement Research </span></b><span style="color:black"> <o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Contribute to mobile health and human movement research with Stanford University, all from your home! You can complete the study in around 20 minutes on a smartphone, and you will be compensated with a $30 Amazon
gift card, in addition to being entered in a lottery for an additional $100 gift card! It consists of: 1) Recording a video with 5 sit-to-stand movements and 2) filling out a questionnaire. Go to <a href="http://sit2stand.ai/" target="_blank">sit2stand.ai</a> on
your mobile device to participate. Anyone can participate – as long as you are over 18 years, in the US, and can safely move from sitting to standing. For participant's rights questions, contact 1-866-680-2906. <o:p></o:p></span></p>
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