A Non-Rigid Map Fusion-Based RGB-Depth SLAM Method for Endoscopic Capsule Robots

In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is considered as a minimally invasive novel diagnostic technology to inspect the entire GI tract and to diagnose various diseases and pathologies. Since the development of this technology, medical device companies and many groups have made significant progress to turn such passive capsule endoscopes into robotic active capsule endoscopes to achieve almost all functions of current active flexible endoscopes. However, the use of robotic capsule endoscopy still has some challenges. One such challenge is the precise localization of such active devices in 3D world, which is essential for a precise three-dimensional (3D) mapping of the inner organ. A reliable 3D map of the explored inner organ could assist the doctors to make more intuitive and correct diagnosis. In this paper, we propose to our knowledge for the first time in literature a visual simultaneous localization and mapping (SLAM) method specifically developed for endoscopic capsule robots. The proposed RGB-Depth SLAM method is capable of capturing comprehensive dense globally consistent surfel-based maps of the inner organs explored by an endoscopic capsule robot in real time. This is achieved by using dense frame-to-model camera tracking and windowed surfelbased fusion coupled with frequent model refinement through non-rigid surface deformations

Towards an Implantable Vestibular Prosthesis: The Surgical Challenges

Published versio

A Self-tracked High-dielectric Wireless Power Transfer System for Neural Implants

This paper introduces a novel, efficient and long-range ( 0.5λ) wireless power transfer system for implantable neural devices. The operating principle of this system is based on the high-dielectric coupling, which occurs between an external lossless high-dielectric metamaterial (permittivity, ε r =100, loss tangent, tanδ = 0.0001) and lossy dielectric such as rat (ε r =54.1, conductivity, σ = 1.5 S/m). As magnetic field coupling occurs between two dielectric resonators, therefore, the rat (lossy dielectric) itself acts as a self-tracking energy source. The Ansoft HFSS simulation software was used to verify the concept. Initially, the rat was modelled as a phantom box and the resonant frequency was found to be 1.5 GHz. Then, for matching this intrinsic mode of the rat model, the external high-dielectric metamaterial designed accordingly to realize a highly efficient (η = 1×10 -3 ) and self-tracked wireless power system for neural implants

Biomedical Sensing - A Sensor Fusion Approach for Improved Medical Detection and Monitoring

Enhanced technological advancement in computation, communication, and sensing has dramatically changed the dynamics of modern medicine. Advancing preventive medicine is paramount to a sustainable improvement in the quality of life and life expectancy. On-body sensors provide continuous measurements for healthy and ailing individuals leading to faster recovery and more timely detection of illnesses. Novel sensor designs and sensor fusion for preventive monitoring can provide extensible benefits, including a better understanding of ailment progression, treatment optimization, and patient feedback through data analytics and visualization. However, existing research does not thoroughly investigate sensor fusion approaches in biomedical sensing, as well as spot sensing, which can provide better information through more accurate detection of specific tissues instead of secondary measurements. This article presents the development of an ex-vivo sensor fusion system to track a person\u27s muscular condition. The embedded system provides a significant benefit by notifying users of particular muscle events in real-time