Applying the Internet of Things (IoT) to biomedical development for surgical research and healthcare professional training

Individual surgeons rely on residency programs as their main conduit for developing the necessary soft skills needed to succeed and excel in the operating room. One critical skill requiring subjective (qualitative) learning involves navigating through varying soft and hard tissues by hand, and, most importantly, understanding how medical instruments respond under these conditions. During residency, students learn the specific methods of the teaching surgeons, using specific instruments chosen by both the administrators of the residency programs and medical staff. The availability of practice time is limited not by the interest of the resident, but due to limitations in resources (e.g. high cost of cadaver parts, program insurance, and available contact time with patients in the operating room). By using data extraction during training, teaching surgeons can determine how well participants learn a subjective skill. Without data extraction, residents lack quantifiable numbers to guide them. Such values would verify correct techniques and highlight areas for improvement. In the end, the effectiveness of surgical training, mastery of soft skills, and overall surgical experience directly helps or harms patient outcomes [1]. We intend to coordinate with research scientists to develop Internet of Things (IoT) solutions incorporating existing data for training and real-time feedback. This data, which pertains to bicortical drilling conditions, will provide teaching surgeons and their surgical residents evaluation tools beyond those currently available.