ReSuture simulation research quantifies operative performance. Through NSF SBIR-funded work combining simulated surgical platforms, capacitive sensing, and machine learning, we are building objective measures of surgical skill for training programs and the medical device industry.
$2.6MGrant Funded Research
5Major Research Partners
2Issued Patents
2Funded SBIRs
Simulation Research Partnerships
Our simulation research is conducted alongside five major research partners: St. Joseph’s Hospital and Medical Center, the Mayo Clinic, the machine learning lab of Dr. Baoxin Li at Arizona State University, the NSF ASSIST Center, and the Arizona WearTech Center. Together we are working to make ReSuture the first company to deliver quantitative data on surgical performance.
Capacitive Sensing and Machine Learning
Funded by our NSF Phase II SBIR, we embed capacitive sensors in synthetic anatomy to capture how instruments interact with tissue during simulated procedures. Machine learning algorithms trained on this data classify surgical skill, producing objective benchmarks that strengthen surgical simulation and vascular surgical training.
Quantifying Medical Device Performance
Our instrumented simulations bring measurement to medical device development, quantifying how new devices perform in lifelike anatomy long before first clinical use. The same objective metrics support medical device training, documenting physician proficiency as new technologies are adopted.
Extending Research to Endovascular Training
A core aim of our Phase II work is demonstrating an endovascular training system that can quantifiably evaluate operative performance. Building on the radiation-free endovascular simulation developed for the NAVIS Lab, this research extends objective skill measurement from open surgery into endovascular training.
Become a Research Partner
Interested in partnering with ReSuture or learning more about our work? Contact us or email research@resuture.com.
