Jessica Jessica
Papers
1
Total Citations
2
H-Index
1
About
Jessica Jessica’s research lies at the intersection of medical robotics, image-guided intervention, and motion control algorithms. Her most cited work, “Evaluasi Algoritme Bresenham dan Digital Differential Analyzer (DDA) untuk Pengontrolan Koordinasi Gerakan Dua Motor Stepper pada Robot untuk Simulator Penusukan Jarum Medis” (2019), addresses a critical challenge in ultrasound-guided needle insertion: maintaining consistent needle visibility. By evaluating Bresenham and DDA algorithms for coordinating dual stepper motors in a robotic simulator, she demonstrated how precise motion control can enhance the stability and accuracy of needle placement—a key factor in reducing procedural errors. While her citation count (2) reflects the niche, early-stage nature of this work, its practical relevance to medical training and real-time imaging guidance is significant. Her contributions lay foundational groundwork for integrating low-cost, algorithm-driven robotics into clinical simulation, with potential to improve patient safety in minimally invasive procedures. Jessica’s research is particularly valuable for students and engineers exploring how classic computer graphics algorithms can be repurposed for precise electromechanical control in medical contexts.
Research Focus
Key Achievements
Top Papers
- 1