3D-printed Hindlimb Stabilization Apparatus
Danny Lam and colleagues out of the Shoffstall Lab at Case Western Reserve University published their open source tool, a 3D-printed Hindlimb Stabilization Apparatus, in eLife in December 2023.
Motor function evaluation is a necessary measurement in Neuroscience research to study the peripheral nervous system in response to stimuli and to examine evoked nerve responses. Standard measurements of motor function exist, but are either extremely invasive or largely inaccurate. EMG methods involve electrode insertion into muscles, which causes trauma over time to the area of interest. Video analysis, while not invasive, is often inconsistent in quality and measurement. Ankle torque measurement, on the other hand, is noninvasive and a highly accurate measurement for muscle contractility. The issue with this method, though, is that there is insufficient literature on stabilizing rodent hind limbs in order to successfully complete the measurement.
The Shoffstall Lab addressed this by publishing a comprehensive toolkit for building an open-source, 3D-printed hindlimb stabilizer, with data to assess its accuracy. The apparatus is made up of 3 key components: a Foot Pedal, a Knee-Locking component, and an Acrylic Base Platform. The design is adjustable for variations in anatomy across sex and size of rodents, and is low in cost. The components are almost entirely 3D-printed, and any other supplies are published along with the build instructions.
The apparatus provides a low cost and customizable design for measuring evoked motor responses, along with an adequate protocol for ankle torque measurement.
This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. RRID: SCR_025415
Special thanks to Abby St. Jean, a neuroscience undergraduate at American University, for providing this project summary.
Access the code from GitHub!
Check out the repository on GitHub.
Read more about it!
Check out more about the development and validation of this project from the eNeuro publication!
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