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iCrutch: Addressing the Therapeutic Challenges of Nystagmus

Project Description:

Acquired nystagmus is a condition characterized by repetitive, involuntary eye movements that impair visual stability and quality of life. Current treatments, including pharmacological therapy and surgery, are often ineffective, non-specific, and unable to adapt to progressive symptom changes. Here, we present a real-time eye-tracking system that detects nystagmus, classifies its subtype using machine learning, and computes a corrective motion vector. The system integrates infrared cameras with Fourier-based processing to distinguish pathological oscillations from voluntary gaze shifts, achieving 99% detection accuracy with a 10 ms response latency. A computational model predicts the necessary counteracting motion to stabilize gaze, mapping corrective movements to extraocular muscles. Preliminary results demonstrate high precision in nystagmus classification and motion compensation, establishing a foundation for future electrode-based stimulation therapies. This system represents a step toward adaptive, closed-loop therapies.

Project Photo:

The image shows the logo for iCrutch, a wearable solution for nystagmus. It features a human eye with circuit lines extending into the word

Our project, iCrutch, is a wearable device for individuals with nystagmus, using implanted electrodes to correct involuntary eye movements in real-time. The logo features a human eye and circuit lines, symbolizing the innovation of our device that is focused on improving visual focus and quality of life.

Project Poster

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Student Team Members

  • Archis Shankaran
  • Dennis Ngo
  • Kenzi Griffith
  • Simren Shah
  • Immanuel Etoh
  • Evan Batten
  • Travis Tran
  • Esha Venkat

Course Faculty

Project Mentors, Sponsors, and Partners

  • Kemar E. Green, DO – Assistant Professor of Neurology, Johns Hopkins School of Medicine

Project Video