In recent years, open-source 3D printing technologies have become increasingly applied to biological research. We have created a fully open-source, versatile and low cost XYZ positioning system using 3D printer components. As this system is controlled by a Python3 based operating system running on a Raspberry Pi 3 Model B, its behaviour can be adapted to meet multiple needs in neurophysiology. We have developed two main applications of this system. First, we have created an automated microscopy script that links seamlessly with image stitching plugins in ImageJ (Fiji) allowing the user to create high resolution montages. Second, we have created a series of movement scripts allowing the application of graded rates of stretch to muscle spindles. Here we outline the construction and implementation of this system and discuss how we have utilised this tool in our research.
Keywords: 3D, Three Dimensional; AC, Alternating Current; Arduino; Automated microscopy; CNC, Computed Numerical Code; DC, Direct Current; EMI, Electromagnetic Interference; FDM, Fused Deposition Modelling; FFF, Fused Filament Fabrication; GPIO, General-Purpose Input/Output; IDE, Integrated Developer Environment; LCD, Liquid Crystal Display; Mechanotransduction; NEMA17, National Electrical Manufacturers Association (stepper motor with faceplate dimensions of 1.7 × 1.7 in.); Neurophysiology; OpenCV, Open Computer Vision; PLA, Polylactic Acid; PVA, Polyvinyl Acetate; RAMPS 1.4, Reprap Arduino Mega Pololu Shield (version 1.4); Raspberry Pi; SD Card, Secure Digital Card; STEM, Science, Technology, Engineering and Mathematics; STL, Stereolithography; USB, Universal Serial Bus; UTF-8, Unicode Transformation Format, 8-bit blocks; VAT, Value Added Tax; XYZ positioning system.
© 2020 The Authors.