PD3D | Magnetic Tracking
16622
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Magnetic Tracking

About This Project

Minimally invasive surgery performed both robotically and manually are increasing in adoption at a dramatic rate. As surgery systems continue to advance across a broad scope, the inherent technical requirement for spatial awareness data will only increase. For example, Renishaw’s Neuromate and Accuray’s CyberKnife both require the precise location of fiducial markers to operate. Surgeons performing teleoperations will benefit from the availability of high-quality, real-time, auxiliary sensor information that enables the extension of their dexterity and spatial awareness. Providers will also deploy cost-effective user input systems for simulation programs designed to train aspiring and established healthcare professionals on using state-of-the-art medical tools.

To advance this field and to provide simulation inputs for training applications, we have constructed a robust, scalable, highly-customizable, and non-intrusive system for dynamically tracking magnetized objects by taking advantage of well-characterized magnetic field properties. Ultimately, this extremely low-cost proof-of-concept prototype serves as a foundation for exploring this approach to tracking surgical instruments and devices in the medical industry.

The MAGNETO platform has been developed by our team of engineers and undergraduate students. Latest hardware and software builds, including development branches, can be found on our magneto repository. Our team has spun-off a few applications based on the magnetic tracking method.

Mohammad Odeh

Edward “Danny” Nichols

Matthew Boutelle

Samer Armaly

Fluvio Lobo Fenoglietto

Jack Stubbs

LOCAR

MAGNETO v.1.0

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Original Sensor Array. Six (6) LSM9DS1 IMU sensors were connected to an Arduino Mega 2560 via I2C. The communication was mediated
through a 74HC4051 8-channel multiplexer. The array was fixed to a 300 mm x 300 mm aluminum optics breadboard. Sensors were held in place using 3D-printed standoffs.
Original Sensor Array. Six (6) LSM9DS1 IMU sensors were connected to an Arduino Mega 2560 via I2C. The communication was mediated
through a 74HC4051 8-channel multiplexer. The array was fixed to a 300 mm x 300 mm aluminum optics breadboard. Sensors were held in place using 3D-printed standoffs.
MAGNETO v.2.0
MAGNETO v.2.5
DaisyHub module. Fabrication image of the copper-fill on the top side of the
Moving Forth

Our team will seek further the MAGNETO project in the following areas:

  • Extended calibration protocols for different permanent magnets
  • Investigate and feature additional application areas for the technology
  • Custom PCBs specific to application areas
Category
Medical, Planning, Prototype