Existing laparoscopic surgery systems use a single laparoscope to visualize the surgical area with a limited field of view (FoV), necessitating maneuvering the laparoscope to search a target region. In some cases, the laparoscope needs to be moved from one surgical port to another one to detect target organs. These maneuvers would cause longer surgical time and degrade the efficiency of operation. We hypothesize that if an array of cameras can be deployed to provide a stitched video with an expanded FoV and small blind spots, the time required to perform multiple tasks at different sites can be significantly reduced. We developed a micro-camera array that can enlarge the FoV and reduce blind spots between the cameras by optimizing the angle of cameras. The video stream of this micro-camera array was designed to be processed in real-time to provide a stitched video with the expanded FoV. We mounted this micro-camera array to a Fundamentals of Laparoscopic Surgery (FLS) laparoscopic trainer box and designed an experiment to validate the hypothesis above. Surgeons, residents, and a medical student were recruited to perform a modified bean drop task, and the completion time was compared against that measured using a traditional single-camera laparoscope. It was observed that utilizing the micro-camera array, the completion time of the modified bean drop task was $203\pm 55$ s while using the laparoscope, the completion time was $245\pm 114$ s, with a p-value of 0.00097. It is also observed that the benefit of using an FoV-expanded camera array does not diminish for subjects who are more experienced. This test provides convincing evidence and validates the hypothesis that expanded FoV with small blind spots can reduce the operation time for laparoscopic surgical tasks.

We developed an ankle-worn gait monitoring system for tracking gait parameters, including length, width, and height. The system utilizes ankle bracelets equipped with wide-angle infrared (IR) stereo cameras tasked with monitoring a marker on the opposing ankle. A computer vision algorithm we have also developed processes the imaged marker positions to estimate the length, width, and height of the person’s gait. Through testing on multiple participants, the prototype of the proposed gait monitoring system exhibited notable performance, achieving an average accuracy of 96.52%, 94.46%, and 95.29% for gait length, width, and height measurements, respectively, despite distorted wide-angle images. The OptiGait system offers a cost-effective and user-friendly alternative compared to existing gait parameter sensing systems, delivering comparable accuracy in measuring gait length and width. Notably, the system demonstrates a novel capability in measuring gait height, a feature not previously reported in the literature.