Projects
Training Kit for Laparoscopic Surgery
Project Overview:
This project is a low-cost novel training kit consisting of a laparoscopic training box, which is designed to mimic the conditions of actual laparoscopic surgery including realistic tissue and organ simulations, as well as instruments that mimic the feel and function of real laparoscopic instruments. The kit uses artificial intelligence technology to analyze data from the training sessions and provide surgeons-in-training with personalized feedback and guidance. The goal of the training kit is to provide surgeons-in-training with the opportunity to practice and improve their laparoscopic skills in a safe and controlled environment before performing the surgery on actual patients.
Health Issue Addressed:
This project is addressing the limited accessibility of laparoscopic surgery training kits in low resource settings, that possess a major barrier for surgeons-in-training to learn necessary skills to perform laparoscopic procedures, which is a vital component of surgical education.
Development Status:
Alpha prototype
Training Kit for Neonatal Airway Suctioning
Project Overview:
This project is a low-cost novel training kit consisting of a mannequin, which is designed to mimic actual anatomy of a neonate head in size and detail, and uses electronics, to help healthcare professionals develop the necessary skills and knowledge to perform airway suctioning procedures on newborns.
Health Issue Addressed:
This project is addressing the limited accessibility of standard training kits for airway suction in low resource settings to allows medical students and paramedics to easily practice oral and nasal intubation, as well as various suction techniques.
Development Status:
Alpha prototype
Smart IV Drip Monitoring and Control Device
Project Overview:
This project is a novel low-cost intelligent device that uses artificial intelligence (AI) and machine learning to monitor and control the administration of IV fluids to a patient. make predictions about the patient's condition, The device predicts the patient's fluid and electrolyte requirements, adjust the infusion rate accordingly, as well as detect early signs of complications and alert the healthcare provider.
Innovation Overview:
Health Issue Addressed:
This project is addressing prevalent medication errors and patient complications during intravenous (IV) medication delivery in low resource settings, resulted from limited in-person check-ins, because of high patient to nurse ratio.
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Development Status:
Alpha prototype
