In the second part, after performing in-vitro experiments to measure the resistant force of the small intestine, we propose a magnetic actuation method. The magnetic marker for localization acts as a seed to be actuated by multiple coils placed outside of the human body. The basic idea is that the magnetic seed is subject to a force and a torque in a magnetic field. An efficient computation scheme is designed and implemented to calculate the coil currents for real-time actuation. Simulations are performed on a six-coil actuation system to evaluate the method. As an alternative method, an internal actuator, which consists of a magnetic spring and can propel itself forward under an alternating current, is introduced to increase the mobility of the capsule and decrease the demand for a strong external field. The external magnetic field is also simulated to orient the internal actuator. / The development of wireless capsule endoscope realizes the examination of the whole gastrointestinal tract. The technology reduces patients' pain and benefits the doctors as well. However, it loses some functions that conventional endoscope owns because of the passive locomotion mode. To improve the situation, an active capsule endoscope is preferred by the community. / We put emphasis on two important problems in design of an active capsule endoscope: localization and actuation. The first part of our work focuses on the study of localization of the capsule taking advantage of the magnetic field. A small permanent magnet is enclosed in the capsule as a marker, and a tracking method is proposed based on the modelling of the marker as an ideal dipole. The five localization parameters are computed by minimizing the differences between the theoretical field values and sensing signals using Levenberg-Marquardt algorithm. One-axis Hall sensors and three-axis magnetoresistive sensors are employed respectively to implement the localization method. The system performance is evaluated by a series of tracking experiments. / Wang Xiaona. / "September 2006." / Adviser: Max Meng. / Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1771. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 155-171). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Wireless capsule endoscopy (WCE) offers a patient-friendly, non-invasive and painless investigation of the entire small intestine, where other conventional wired endoscopic instruments can barely reach. As a critical component of the capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of intestinal disease after it is detected by the video source. To define the position of the endoscopic capsule, we need to have a map of inside the human body. However, since the shape of the small intestine is extremely complex and the RF signal propagates differently in the non-homogeneous body tissues, accurate mapping and localization inside small intestine is very challenging. In this dissertation, we present an in-body simultaneous localization and mapping technique (Body-SLAM) to enhance the positioning accuracy of the WCE inside the small intestine and reconstruct the trajectory the capsule has traveled. In this way, the positions of the intestinal diseases can be accurately located on the map of inside human body, therefore, facilitates the following up therapeutic operations. The proposed approach takes advantage of data fusion from two sources that come with the WCE: image sequences captured by the WCE's embedded camera and the RF signal emitted by the capsule. This approach estimates the speed and orientation of the endoscopic capsule by analyzing displacements of feature points between consecutive images. Then, it integrates this motion information with the RF measurements by employing a Kalman filter to smooth the localization results and generate the route that the WCE has traveled. The performance of the proposed motion tracking algorithm is validated using empirical data from the patients and this motion model is later imported into a virtual testbed to test the performance of the alternative Body-SLAM algorithms. Experimental results show that the proposed Body-SLAM technique is able to provide accurate tracking of the WCE with average error of less than 2.3cm.

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Background: Capsule endoscopy (CE) is a non-invasive imaging modality designed to evaluate various small bowel pathologies. Failure to reach the cecum within the battery lifespan, termed incomplete examination, may result in inadequate testing and possibly delayed therapy. Several studies have attempted to evaluate the association between CE completion and opioid use. However, their results are conflicting. The aim of this meta-analysis is to evaluate the previously published literature on the association between opioid use and CE completion. Methods: We performed a comprehensive literature search in PubMed, PubMed Central, Embase, and ScienceDirect databases from inception through June 1, 2018, to identify all studies that evaluated the association between CE completion and opioid use. We included studies that presented an odds ratio (OR) with a 95% confidence interval (CI) or presented the data sufficient to calculate the OR with a 95% CI. Statistical analysis was performed using the comprehensive meta-analysis (CMA), version 3 software. Results: Five studies with a total of 1,614 patients undergoing CE in the inpatient (IP) and outpatient (OP) setting were included in this study, 349 of which had an incomplete CE (21.6%). The pooled OR for CE completion is 0.50 (95% CI: 0.38-0.66, I2=36.9%) in opioid users compared to non-users. No publication bias was found using Egger's regression test. Conclusions: Our results indicate that patients on opioids are significantly less likely to have a complete CE examination compared to non-users. To our knowledge, this study represents the first meta-analysis to assess this association.

Recent reports suggest that measuring the objective quality is very essential towards the success of colonoscopy. Several quality indicators (i.e. metrics) proposed in recent studies are implemented in software systems that compute real-time quality scores for routine screening colonoscopy. Most quality metrics are derived based on various temporal events occurred during the colonoscopy procedure. The location of the phase boundary between the insertion and the withdrawal phases and the amount of circumferential inspection are two such important temporal events. These two temporal events can be determined by analyzing various camera motions of the colonoscope. This dissertation put forward a novel method to estimate X, Y and Z directional motions of the colonoscope using motion vector templates. Since abnormalities of a WCE or a colonoscopy video can be found in a small number of frames (around 5% out of total frames), it is very helpful if a computer system can decide whether a frame has any mucosal abnormalities. Also, the number of detected abnormal lesions during a procedure is used as a quality indicator. Majority of the existing abnormal detection methods focus on detecting only one type of abnormality or the overall accuracies are somewhat low if the method tries to detect multiple abnormalities. Most abnormalities in endoscopy images have unique textures which are clearly distinguishable from normal textures. In this dissertation a new method is proposed that achieves the objective of detecting multiple abnormalities with a higher accuracy using a multi-texture analysis technique. The multi-texture analysis method is designed by representing WCE and colonoscopy image textures as textons.

Surgical procedures conducted without proper guidance and dynamic feedback mechanism could lead to unintended consequences. In-vivo diagnostics and imaging (the Gastro-Intestinal tract) has shown to be inconvenient for the patients using traditional endoscopic instruments and often these conventional methods are limited in terms of their access to various organs (e.g. small intestines). Embedding sensors inside the living body is complex and further the communication with the implanted sensors is challenging using the current RF technology. Additionally, continuous replacement and/or batteries recharging for wireless sensors networks both in-vivo and ex-vivo adds towards the complexity. Advances in diagnostics and prognostics techniques require development at multiple levels through systems approach, guided by the futuristic intelligent decision making environment that reduces the human interference. The demands are not only at the component level, but also at the connectivity of the components such that secure, sustainable, self-reliant, and intelligent environment can be realized. This thesis provides important breakthroughs required to achieve the vision of intelligent healthcare environment. The research contributions of this thesis provide foundation for developing a new architecture for continuous medical diagnostic and monitoring. The chapters in this thesis cover four fundamental technologies covering the in-vivo imaging, ex-vivo imaging, energy for sensors, and acoustic communication. These technologies are: locomotion mechanism for wireless capsule endoscope (WCE), multifunctional image guided surgical (MIGS) platform, shape memory alloy (SMA) thermal energy harvester and thermo-acoustic sonar using carbon nanotube (CNT) sheets. First, two types of locomotion mechanisms were developed, the first one inspired by millipede legged type mechanism and the second one based on the traveling waves that were induced onto the walls of the WCEs through vibration. Both mechanisms utilize piezoelectric actuators and couple their dynamics and actuation capability in order to achieve propulsion. This controlled locomotion will provide WCE advantage in terms of conducting localized diagnostics. Next, in order to conduct ex-vivo surgical procedures using the OCT such as removing the unwanted tissue and tumors short distance beneath the skin, MIGS platform was developed. The MIGS platform is composed of three key elements: optical coherence tomography (OCT) probe, laser scalpel and high precision miniature scanning and positioning stage. The focus in this dissertation was on design and development of the programmable scanning and positioning stage. The combination of in-vivo tool such as WCE and ex-vivo tool such as MIGS will provide opportunity to conduct many non-invasive procedures which will save time and cost. In order to power the feedback sensors that assist in remote operation of surgical procedures and automation of the diagnostic algorithms, an energy harvester technology based on the SMA thermal engine was designed, fabricated, and characterized. A mechano-thermal model for the overall SMA engine was developed and experimentally validated. Finally, the thermo-acoustic sound generation mechanism using CNT sheets was investigated with the goal of developing techniques for acoustic localization of WCE and customized sound generation devices. CNT thermo-acoustic projectors were modeled and experimentally characterized to quantify the dynamics of the system under varying drive conditions. The overall vision of this thesis is to lay down the foundation for intelligent healthcare environment that provides the ability to conduct automated diagnostics, prognostics, and non-invasive surgical procedures. In accomplishing this vision, the thesis has addressed several key fundamental aspects of various technologies that will be required for implementing the automation algorithms. / Ph. D.

無線膠囊內窺鏡（CE）是一種用於檢查整個胃腸道，尤其是小腸的無創技術。它極大地改善了許多小腸疾病的診斷和管理方式，如不明原因的消化道出血，克羅恩病，小腸腫瘤，息肉綜合征等。儘管膠囊內窺鏡有很好的臨床表現，但它仍然有一定的局限性。主要問題是每次檢查產生約50,000 幅低質量的圖像，對於醫生來說，評估如此大量的圖像是一項非常耗時、耗力的工作。 / 到目前為止，對於膠囊內窺鏡的分析和評估，學者們都把膠囊內窺鏡圖像視為單獨的，獨立的觀測對象。事實並非如此，因為圖像之間往往有顯著的重疊。特別是當膠囊內窺鏡在被小腸蠕動緩緩推動時，它可以捕捉同一病灶的多個視圖。我們的研究目的是使用所有可用的資訊，包括多幅圖像，研究對於膠囊內窺鏡的電腦輔助診斷（CAD）系統。 / 在這篇論文中，我們提出了一個嵌入分類器的多類隱馬爾可夫模型（HMM）的方案，它可以融合多幅相鄰圖像的時間資訊。由於膠囊內窺鏡圖像的品質比較低，我們首先進行預處理，以加強膠囊內窺鏡圖像，增加其對比度，消除噪聲。我們調查研究了多種圖像增強的方法，並調整了它們的參數使其適用於膠囊內窺鏡圖像。 / 對於基於單幅圖像的有監督的分類，AdaBoost 作為一個集成分類器來融合多個分類器，即本論文中的支持向量機（SVM），k-近鄰（k-NN），貝葉斯分類。在分類之前，我們提取和融合了顏色，邊緣和紋理特徵。 / 對於無線膠囊內窺鏡的視頻摘要，我們提出了有監督和無監督的兩類方法。對於有監督方法，我們提出了一個基於隱馬爾可夫模型的，靈活的，可擴展的框架，用於整合膠囊內窺鏡中連續圖像的時間資訊。它可以擴展到多類別，多特徵，多狀態。我們還提出了聯合隱馬爾可夫模型和並行隱馬爾可夫（PHMM）模型對系統進行改進，它們可以被看作是決策級的資訊融合。聯合隱馬爾可夫模型通過多層次的隱馬爾可夫模型，結合不同的資訊來源，對膠囊內窺鏡視頻進行分類和視頻摘要。 並行隱馬爾可夫模型採用貝葉斯推理，在決策時融合多個不同來源的資訊。對於無監督的方法，我們首先提出了一種基於顏色的特徵提取方法。在反色顏色空間中對亮度不變的色度不變矩用來表示膠囊內窺鏡圖像的顏色特徵。接著，我們又提出了一種基於輪廓元（Contourlet）變換的局部二元模式（LBP）作為紋理特徵。在特徵空間中，我們測量了相鄰圖像的距離，並把它視為一個位於二維平面上的開放輪廓上的點。 然後，我們採用一個無參數的關鍵點檢測方法檢測在視頻片段上的突變關鍵點。基於這些突變關鍵點，我們對膠囊內窺鏡視頻進行分割。最後，在每段被分割的視頻片段上，我們通過提取有代表性的關鍵幀來實現膠囊內窺鏡視頻摘要。我們分別用模擬和真實的病人數據進行實驗，對提出的方法進行驗證，結果表明了我們所提出的方案的有效性。它在實現自動評估膠囊內窺鏡圖像上具有很大的潛力。 / Wireless Capsule Endoscopy (CE) is a non-invasive technology to inspect the whole gastrointestinal (GI) tract, especially the small intestine. It has dramatically changed the way of diagnosis and management of many diseases of the small intestine, such as obscure gastrointestinal bleeding, Crohn’s disease, small bowel tumors, polyposis syndromes, etc. Despite its promising clinical findings, it still has some limitations. The main problem is that it requires manual assessment of approximately 50,000 low quality images per examination which is highly time-consuming and labor-intense. / CE analysis and assessment so far treated CE images as individual and independent observations. It is obviously not the case as there is often significant overlap among images. In particular, CE captures multiple views of the same anatomy as the capsule is slowly propelled by peristalsis. Our broader work aims to perform computer aided diagnosis (CAD) in endoscopy using all available information, including multiple images. / In this dissertation, a framework of multi-class Hidden Markov Models (HMM) embedded with statistical classifiers for combining information from multiple CE images is proposed. Due to the low quality of CE image, pre-processing is performed to enhance CE images by increasing the contrast and removing noises. Several image enhancement methods are investigated and customized for CE images. For frame-based supervised classification, AdaBoost is used as the ensemble classifier to combine multiple classifiers, i.e. support vector machine (SVM), k-nearest neighbor (k-NN), and Bayes classifier. Before classification, color, edge and texture features are extracted and fused. Finally, both supervised and unsupervised methods are proposed for CE study synopsis. For supervised method, a flexible and extensible framework based on HMM is developed to integrate temporal information in CE images. It can be extended to multi-class, multi-features, and multi-states. Improvements can be made by combined HMM and Parallel HMM (PHMM) which are introduced as decision-level fusion schemes. Combined HMM considers different sources via a multi-layer HMM model to perform classification and video synopsis. PHMM employs Bayesian inference to combine the recognition results at decision level. For unsupervised method, illumination-independent opponent color moment invariants and local binary pattern (LBP) based on Contourlet transform are explored as color and texture features, respectively. Pair-wise image dissimilarity is measured in the feature space and treated as points on an open contour in a 2-D plane. CE video is segmented based on sudden change points which are detected using a non-parametric key-point detection method. From each segment, representative frames are extracted to summarize the CE video. Validation results on simulated and real patient data show promising performance of the proposed framework. It has great potential to achieve automatic assessment for CE images. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zhao, Qian. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 142-175). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.ii / Acknowledgments --- p.vii / List of Tables --- p.xiii / List of Figures --- p.xv / Chapter 1 --- The Relevance of Synopsis --- p.1 / Chapter 1.1 --- Problem Statement --- p.1 / Chapter 1.2 --- Application - Capsule Endoscopy Assessment --- p.4 / Chapter 1.3 --- Literature Review --- p.9 / Chapter 1.3.1 --- Methods Based on Frame Classification --- p.11 / Chapter 1.3.2 --- Methods Integrating Temporal Information --- p.14 / Chapter 1.4 --- Contributions --- p.19 / Chapter 1.5 --- Organization --- p.23 / Chapter 2 --- Preliminary --- p.25 / Chapter 2.1 --- Hidden Markov Model (HMM) --- p.25 / Chapter 2.2 --- Factorial HMM --- p.35 / Chapter 3 --- Temporal Integration in Capsule Endoscopy Image Analysis --- p.37 / Chapter 3.1 --- Pre-processing --- p.38 / Chapter 3.2 --- Feature Extraction --- p.43 / Chapter 3.3 --- Frame-based Supervised Classification --- p.47 / Chapter 3.3.1 --- Supervised Classification using Individual Frames --- p.47 / Chapter 3.3.2 --- Ensemble Learning Based on AdaBoost --- p.50 / Chapter 3.4 --- Sequence-based Supervised Classification --- p.52 / Chapter 3.5 --- Experiments --- p.58 / Chapter 3.5.1 --- Capsule Endoscopy Image Enhancement --- p.60 / Chapter 3.5.2 --- Frame-based Supervised Classification --- p.67 / Chapter 3.5.3 --- Image Sequence Classification --- p.68 / Chapter 3.6 --- Discussion --- p.80 / Chapter 3.7 --- Summary --- p.82 / Chapter 4 --- Capsule Endoscopy Study Synopsis --- p.98 / Chapter 4.1 --- Supervised Synopsis Using Statistical Models --- p.98 / Chapter 4.2 --- Unsupervised Synopsis via Representative Frame Extraction --- p.100 / Chapter 4.2.1 --- Feature Extraction --- p.100 / Chapter 4.2.2 --- Non-parametric Key-point Detection --- p.111 / Chapter 4.2.3 --- Representative Frame Extraction --- p.112 / Chapter 4.3 --- Experiments --- p.119 / Chapter 4.3.1 --- Supervised Synopsis Based on HMM --- p.119 / Chapter 4.3.2 --- Unsupervised Synopsis --- p.125 / Chapter 4.4 --- Discussion --- p.132 / Chapter 4.5 --- Summary --- p.133 / Chapter 5 --- Conclusions and Future Work --- p.138 / Chapter 5.1 --- Conclusions --- p.138 / Chapter 5.2 --- Future Work --- p.141 / Bibliography --- p.142

A feature extraction approach based on color is firstly proposed. Exploiting color histogram of an image, we can obtain distribution of different colors in images. Then we employ minimum distance classifier based on a new distance criterion to judge status of regions. In this section, we also validate benefits of WCE image enhancement to the proposed CAD system. / Finally, we propose a new approach of chrominance moment as another kind of feature to discriminate normal regions from abnormal regions, which makes full use of Tchebichef polynomials and HSI color space. This new feature extraction scheme preserves illumination invariance without numerical approximation. / In conclusion, this thesis investigates several major and challenging problems such as WCE images enhancement and feature extractions in CAD for WCE images, and proposes several novel schemes to solve those problems. Extensive experiments are reported to demonstrate effectiveness of the proposed algorithms. / Next, we investigate automatic diseases detection for WCE images to partially solve the second problem. In this part we explore different features that are suitable for detection of diseases from three viewpoints, i.e., color, texture and chromaticity, because clinicians mainly use these clues to diagnose. At the same time, we introduce their corresponding classifiers. / We further advance a new texture feature extraction method, curvelet based local binary pattern, to detect abnormal regions in WCE images. This method takes advantage of curvelet transform and local binary pattern to describe textural features of WCE images. / Wireless capsule endoscopy (WCE) is a state-of-the-art technology to diagnose gastrointestinal (GI) tract diseases without invasiveness. However, there exist two major problems concerning WCE images. One problem is that many images for diagnosis have rather low contrast and are noisy, which causes difficulties to diagnosis and also to computer-aided detection, so it is necessary to enhance these images. The other one is that the viewing process of video data per examination is very time consuming because of the great amount of video data. If we can use computerized methods to help the physicians detect some abnormal regions in WCE images, it will certainly reduce the burden of physicians. Focusing on these two goals, this thesis mainly studies some main challenging problems in computer-aided diagnosis (CAD) system for WCE images. To solve the first problem, we put forward an adaptive curvature strength diffusion method to enhance WCE images. Based on local characteristics analysis of WCE images, we propose a new concept of curvature strength. Then, we employ curvature strength diffusion to enhance WCE images with an adaptive choice of conductance parameter. Finally, we extend the curvature strength diffusion to color space since WCE images are color images. / Li, Baopu. / Adviser: Max Q. H. Meng. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3640. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 126-150). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

by Chan Yawen. / Thesis submitted in: September 12, 2005. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 57-64). / Abstracts in English and Chinese. / Acknowledgement --- p.ii / Abstract --- p.iv / 摘要 --- p.vii / Table of Contents --- p.ix / List of Figures --- p.xii / List of Tables --- p.xiv / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Diseases of the Gastrointestinal (GI) Tract --- p.1 / Chapter 1.2 --- Wireless Capsule Endoscopy --- p.2 / Chapter 1.3 --- Goals of My Research Project --- p.9 / Chapter Part I - --- Experimental Study to Determine the Frequency of Wireless Transmission --- p.11 / Chapter Chapter 2 --- Background --- p.11 / Chapter 2.1 --- Analog and Digital Wireless Video Transmission --- p.11 / Chapter 2.2 --- "Industrial, Scientific and Medical (ISM) Bands" --- p.11 / Chapter 2.3 --- Adsorption of RP Energy by Biological Tissue --- p.13 / Chapter 2.4 --- Frequency used by Implanted/Ingested Devices --- p.13 / Chapter 2.5 --- Incentives of using Higher Frequencies --- p.14 / Chapter 2.6 --- Radiation Efficiency from an Implanted/Ingested Source --- p.15 / Chapter Chapter 3 --- Material and Method --- p.18 / Chapter 3.1 --- Human Body Trunk Experimental Model --- p.18 / Chapter 3.2 --- Radiating and Receiving Antennas --- p.19 / Chapter 3.3 --- Experimental Procedures --- p.21 / Chapter Chapter 4 --- Results and Discussions --- p.23 / Chapter Chapter 5 --- Conclusions --- p.30 / Chapter Part II - --- Prototype Design and Implementation --- p.31 / Chapter Chapter 6 --- Background --- p.31 / Chapter 6.1 --- Prototype Overview --- p.31 / Chapter 6.2 --- Digital and Analog Cameras --- p.32 / Chapter 6.3 --- Digital and Analog Transmitters --- p.34 / Chapter Chapter 7 --- Possible Solutions --- p.38 / Chapter 7.1 --- Analog Camera + Analog Video Transmission --- p.38 / Chapter 7.2 --- Digital Camera + Analog Video Transmission --- p.38 / Chapter 7.3 --- Digital Camera + Digital Video Transmission using WLAN Technology --- p.40 / Chapter 7.4 --- Digital Camera + Digital Video Transmission with Video Compression --- p.42 / Chapter Chapter 8 --- Implementation of the Analog Camera + Analog Transmission Solution --- p.44 / Chapter 8.1 --- Circuit Implementation --- p.44 / Chapter 8.2 --- System Verification --- p.49 / Chapter 8.3 --- Conclusions --- p.51 / Chapter Chapter 9 --- Conclusions and Future Work --- p.53 / Chapter 9.1 --- General Conclusions --- p.53 / Chapter 9.2 --- Future Work --- p.55 / List of Abbreviations --- p.65

The significant development in medical diagnostics and imaging has brought up a lot of new wireless capsule endoscopes coming to health care market. The capsule has been able to minimize patient discomfort and pain during digestive tract screening with less risk of infection and harmless to body organs. This kind of medical procedure is less invasive and gives a great impact compared to the traditional method. Although pill-shaped capsules have existed for over 11 years by now and are currently being used successfully in medical screening to study the GI tract, these systems are passive and are dependent to the peristaltic movement of the gastric wall to propel. The aim of this work is to provide the electronics needed to control an endoscopic capsule robot and the electronics needed to enable active locomotion and advanced vision functions (like autofocus). Enabling such functions the capsules will be able to perform screening, diagnosis and therapy. Such capsule robot has been designed in the framework of the “Versatile Endoscopic Capsule for Gastrointestinal Tumour Recognition and Therapy” (VECTOR) project. This project pursues the goal of realizing smart pill technologies and applications for gastrointestinal (GI) diagnosis and therapy. The overall medical goal of the project is to enable medical devices through advanced technology that can dramatically improve early detection and treatment of GI early cancers and cancer precursors. The main technological objective of the project is the take-up of microsystems and sub-components and their integration into robotic, mobile pill devices for useful and large impact applications in the medical field.