OpenSim 4.4 is Released! We are pleased to announce the release of OpenSim 4.4. The new software includes improvements to the look and feel of the visualizer, easier ways to access OpenSim's MATLAB, Python, and C++ interfaces (Conda and Docker), additional Moco<https://simtk.org/projects/opensim-moco> functionality, and performance improvements for models with muscle wrapping. Learn more<https://simtk-confluence.stanford.edu:8443/pages/viewpage.action?pageId=83468789> Apply to Participate in Virtual Office Hours for Biomechanical Modeling or Machine Learning Research Questions Application Deadline: August 5, 2022, 5 PM local time Office Hour Dates: September 12-16, 2022 We are pleased to announce we will be holding Virtual Office Hours on September 12-16, 2022, to support researchers working with wearable sensors, video technology, and other modalities in rehabilitation research. We will have two tracks: 1) Biomechanical modeling with OpenSim<https://opensim.stanford.edu/> and IMUs<https://simtk-confluence.stanford.edu/display/OpenSim/OpenSense+-+Kinematics+with+IMU+Data> 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. Learn more and apply<https://restore.stanford.edu/2022/06/28/apply-to-participate-in-virtual-office-hours-for-biomechanical-modeling-or-machine-learning-research-questions-6/> Estimating Energy Expenditure During Exercise Using Wearable Sensors - Access Resources from Webinar Thank you to everyone who joined us for our Restore<http://restore.stanford.edu/>/Mobilize<http://mobilize.stanford.edu/> Center webinar featuring Patrick Slade from Stanford University. He presented an overview and tutorial of his algorithm that can provide real-time estimates of energy expenditure during common steady-state and time-varying activities with substantially lower error than state-of-the-art methods. The recordings of the research presentation<https://youtu.be/v1eBDL4l7Nk> and tutorial<https://youtu.be/nyKwnSWQMpw> are now available on our YouTube channel. To learn more, read the publication<https://www.nature.com/articles/s41467-021-24173-x> or try the algorithm<https://github.com/stanfordnmbl/mobilize-tutorials/blob/main/Tutorial_Estimating_Energy_Expenditure_During_Exercise.ipynb> with your own data in the interactive Google Colab notebook used during the tutorial. Register for the MR3 Network 2nd Annual Scientific Retreat “Rehabilitation Clinical Trials: Innovations, Designs, and Tribulations” September 29-30, 2022 The Medical Rehabilitation Research Resource (MR3)<https://ncmrr.org/> Network<https://ncmrr.org/> is pleased to announce its 2nd scientific retreat. The goal of the virtual retreat is to learn more about novel research design, technology development, and implementation practice/policy for rehabilitation clinical trials. Register and learn more<https://ncmrr.org/education-training/2022-retreat>