Bounds on RF cooperative localization for video capsule endoscopy

Wireless video capsule endoscopy has been in use for over a decade and it uses radio frequency (RF) signals to transmit approximately fifty five thousands clear pictures of inside the GI tract to the body-mounted sensor array. However, physician has no clue on the exact location of the capsule inside the GI tract to associate it with the pictures showing abnormalities such as bleeding or tumors. It is desirable to use the same RF signal for localization of the VCE as it passes through the human GI tract. In this thesis, we address the accuracy limits of RF localization techniques for VCE localization applications. We present an assessment of the accuracy of cooperative localization of VCE using radio frequency (RF) signals with particular emphasis on localization inside the small intestine. We derive the Cramer-Rao Lower Bound (CRLB) for cooperative location estimators using the received signal strength(RSS) or the time of arrival (TOA) of the RF signal. Our derivations are based on a three-dimension human body model, an existing model for RSS propagation from implant organs to body surface and a TOA ranging error model for the effects of non-homogenity of the human body on TOA of the RF signals. Using models for RSS and TOA errors, we first calculate the 3D CRLB bounds for cooperative localization of the VCE in three major digestive organs in the path of GI tract: the stomach, the small intestine and the large intestine. Then we analyze the performance of localization techniques on a typical path inside the small intestine. Our analysis includes the effects of number of external sensors, the external sensor array topology, number of VCE in cooperation and the random variations in transmit power from the capsule

On Simultaneous Localization and Mapping inside the Human Body (Body-SLAM)

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\u27s 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

On the Accuracy of Wireless Capsule Endoscope RF and Visual Localization

Wireless capsule endoscope (WCE) is becoming one of the most patient-friendly inspection device which provides visual investigation of entire gastrointestinal (GI) tract, while the other traditional (wired) endoscopic devices are usually designed for colon inspection. Locating abnormalities tract such as tumors, polyps and bleedings with wire-connected endoscope in GI tract is simple as long as we could measure the length of the wires inside human body. When WCE is applied, however, this becomes a critical challenge of examination since there is no wires connected to WCE while physicians need to find the exact locations of WCE to identify the position of abnormalities. To locate the WCE accurately, methods have come up in last decade including time of arrival (TOA) based methods, received signal strength (RSS) based methods, phase difference of arrival (PDOA) based methods, electromagnetic methods and video-based tracking methods, etc.. In this thesis, time of arrival (TOA), phase difference of arrival (PDOA) and video based localization methods are proposed and their performance are analyzed. We first propose an novel video-based tracking technique based on maximum mutual information. With this technique, we can tell the displacement and rotation between consecutive frames. Then in TOA chapter, the Cramer-Rao lower bound (CRLB) of TOA ranging inside homogeneous tissue is calculated first then three TOA ranging methods are proposed and compared with the CRLB which is used as the performance guideline. After that, PDOA based ranging technique is applied exploiting phase difference of two signals. Since the phase difference is taken into consideration, the ranging ambiguity is eliminated. We also evaluate the performance of the proposed PDOA ranging method. Finally, these ranging methods are evaluated in non-homogeneous tissues, the results of which are also compared to that in homogeneous tissue to analyze the impact of non-homogeneity

UWB Characteristics of RF Propagation for Body Mounted and Implanted Sensors

Body Area Network (BAN) technology is related to many applications inside, on and around the human body. The basic configuration of a BAN is a set of sensors, which are wearable or are placed inside the human body, transmitting signals to a terminal situated in a doctor’s office, in order to assess or monitor some aspect of a patient’s physical condition. Additionally, in many BAN applications the information about the sensor location is very important, since without knowing a sensor’s location, the transmitted data may be of limited value. As an example, Wireless Video Capsule Endoscopy (VCE) can benefit greatly from the addition of location information. The capsule transmits an RF signal from inside the human body to another sensor on the body surface or external. From the image data provided by the capsule, taken together with the location information, the doctor can locate the infection or lesion and initiate appropriate medical care. In this way, the treatment can be more effective and accurate. In this thesis we investigate the characteristics of Ultra-Wide Band (UWB) RF propagation for BAN devices placed around and inside the human body. We have made measurements around the human body and around a water-filled phantom using an E8363B Vector Network Analyzer (VNA), specifically measuring the S21 signal, which gives the transfer function. Based on these measurement results, we discuss the channel propagation for cases where the transmitter and the receiver are on the surface of the body and analyze the UWB propagation characteristics for RF localization. Because it is impractical or even impossible to make measurements inside the human body, we chose to apply the measurements using a simulation model of homogenous tissue, which serves as an approximation of the signal propagation environment inside the body. First, by comparing the multipath situation in free space and within a model of homogenous tissue, we are able to analyze the multipath effects inside human body. Then, because of the different characteristics of RF propagation in different bandwidths, we have made measurements at UWB (3GHz to 10GHz), and narrowband (402MHz) frequencies

Detection of Intestinal Bleeding in Wireless Capsule Endoscopy using Machine Learning Techniques

Gastrointestinal (GI) bleeding is very common in humans, which may lead to fatal consequences. GI bleeding can usually be identified using a flexible wired endoscope. In 2001, a newer diagnostic tool, wireless capsule endoscopy (WCE) was introduced. It is a swallow-able capsule-shaped device with a camera that captures thousands of color images and wirelessly sends those back to a data recorder. After that, the physicians analyze those images in order to identify any GI abnormalities. But it takes a longer screening time which may increase the danger of the patients in emergency cases. It is therefore necessary to use a real-time detection tool to identify bleeding in the GI tract. Each material has its own spectral ‘signature’ which shows distinct characteristics in specific wavelength of light [33]. Therefore, by evaluating the optical characteristics, the presence of blood can be detected. In the study, three main hardware designs were presented: one using a two-wavelength based optical sensor and others using two six-wavelength based spectral sensors with AS7262 and AS7263 chips respectively to determine the optical characteristics of the blood and non-blood samples. The goal of the research is to develop a machine learning model to differentiate blood samples (BS) and non-blood samples (NBS) by exploring their optical properties. In this experiment, 10 levels of crystallized bovine hemoglobin solutions were used as BS and 5 food colors (red, yellow, orange, tan and pink) with different concentrations totaling 25 non-blood samples were used as NBS. These blood and non-blood samples were also combined with pig’s intestine to mimic in-vivo experimental environment. The collected samples were completely separated into training and testing data. Different spectral features are analyzed to obtain the optical information about the samples. Based on the performance on the selected most significant features of the spectral wavelengths, k-nearest neighbors algorithm (k-NN) is finally chosen for the automated bleeding detection. The proposed k-NN classifier model has been able to distinguish the BS and NBS with an accuracy of 91.54% using two wavelengths features and around 89% using three combined wavelengths features in the visible and near-infrared spectral regions. The research also indicates that it is possible to deploy tiny optical detectors to detect GI bleeding in a WCE system which could eliminate the need of time-consuming image post-processing steps

New Techniques in Gastrointestinal Endoscopy

As result of progress, endoscopy has became more complex, using more sophisticated devices and has claimed a special form. In this moment, the gastroenterologist performing endoscopy has to be an expert in macroscopic view of the lesions in the gut, with good skills for using standard endoscopes, with good experience in ultrasound (for performing endoscopic ultrasound), with pathology experience for confocal examination. It is compulsory to get experience and to have patience and attention for the follow-up of thousands of images transmitted during capsule endoscopy or to have knowledge in physics necessary for autofluorescence imaging endoscopy. Therefore, the idea of an endoscopist has changed. Examinations mentioned need a special formation, a superior level of instruction, accessible to those who have already gained enough experience in basic diagnostic endoscopy. This is the reason for what these new issues of endoscopy are presented in this book of New techniques in Gastrointestinal Endoscopy

Frontiers of robotic endoscopic capsules: a review

Digestive diseases are a major burden for society and healthcare systems, and with an aging population, the importance of their effective management will become critical. Healthcare systems worldwide already struggle to insure quality and affordability of healthcare delivery and this will be a significant challenge in the midterm future. Wireless capsule endoscopy (WCE), introduced in 2000 by Given Imaging Ltd., is an example of disruptive technology and represents an attractive alternative to traditional diagnostic techniques. WCE overcomes conventional endoscopy enabling inspection of the digestive system without discomfort or the need for sedation. Thus, it has the advantage of encouraging patients to undergo gastrointestinal (GI) tract examinations and of facilitating mass screening programmes. With the integration of further capabilities based on microrobotics, e.g. active locomotion and embedded therapeutic modules, WCE could become the key-technology for GI diagnosis and treatment. This review presents a research update on WCE and describes the state-of-the-art of current endoscopic devices with a focus on research-oriented robotic capsule endoscopes enabled by microsystem technologies. The article also presents a visionary perspective on WCE potential for screening, diagnostic and therapeutic endoscopic procedures

Ultrawideband Technology for Medical In-Body Sensor Networks: An Overview of the Human Body as a Propagation Medium, Phantoms, and Approaches for Propagation Analysis

[EN] An in-body sensor network is that in which at least one of the sensors is located inside the human body. Such wireless in-body sensors are used mainly in medical applications, collecting and monitoring important parameters for health and disease treatment. IEEE Standard 802.15.6-2012 for wireless body area networks (WBANs) considers in-body communications in the Medical Implant Communications Service (MICS) band. Nevertheless, high-data-rate communications are not feasible at the MICS band because of its narrow occupied bandwidth. In this framework, ultrawideband (UWB) systems have emerged as a potential solution for in-body highdata-rate communications because of their miniaturization capabilities and low power consumption.This work was supported by the Programa de Ayudas de Investigación y Desarrollo (PAID-01-16) at the Universitat Politècnica de València, Spain; by the Ministerio de Economía y Competitividad, Spain (TEC2014-60258-C2-1-R); and by the European FEDER funds. It was also funded by the European Union’s H2020:MSCA:ITN program for the Wireless In-Body Environ-ment Communication–WiBEC project under grant 675353.Garcia-Pardo, C.; Andreu-Estellés, C.; Fornés Leal, A.; Castelló-Palacios, S.; Pérez-Simbor, S.; Barbi, M.; Vallés Lluch, A.... (2018). Ultrawideband Technology for Medical In-Body Sensor Networks: An Overview of the Human Body as a Propagation Medium, Phantoms, and Approaches for Propagation Analysis. IEEE Antennas and Propagation Magazine. 60(3):19-33. https://doi.org/10.1109/MAP.2018.2818458S193360