A Smart Capsule System for Automated Detection of Intestinal Bleeding Using HSL Color Recognition

Automatic polyp image segmentation and cancer prediction based on deep learning

The similar shape and texture of colonic polyps and normal mucosal tissues lead to low accuracy of medical image segmentation algorithms. To solve these problems, we proposed a polyp image segmentation algorithm based on deep learning technology, which combines a HarDNet module, attention module, and multi-scale coding module with the U-Net network as the basic framework, including two stages of coding and decoding. In the encoder stage, HarDNet68 is used as the main backbone network to extract features using four null space convolutional pooling pyramids while improving the inference speed and computational efficiency; the attention mechanism module is added to the encoding and decoding network; then the model can learn the global and local feature information of the polyp image, thus having the ability to process information in both spatial and channel dimensions, to solve the problem of information loss in the encoding stage of the network and improving the performance of the segmentation network. Through comparative analysis with other algorithms, we can find that the network of this paper has a certain degree of improvement in segmentation accuracy and operation speed, which can effectively assist physicians in removing abnormal colorectal tissues and thus reduce the probability of polyp cancer, and improve the survival rate and quality of life of patients. Also, it has good generalization ability, which can provide technical support and prevention for colon cancer.

Design considerations of aptasensors for continuous monitoring of biomarkers in digestive tract fluids

We present a porous Si (PSi)-based label-free optical biosensor for sensitive and continuous detection of a model target protein biomarker in gastrointestinal (GI) tract fluids. The biosensing platform is designed to continuously monitor its target protein within the complex GI fluids without sample preparation and washing steps. An oxidized PSi Fabry-Pérot thin films are functionalized with aptamers, which are used as the capture probes. The optical response of the aptamer-conjugated PSi is studied upon exposure to unprocessed GI fluids, originated from domestic pigs, spiked with the target protein. We investigate biological and chemical surface passivation methods to stabilize the surface and reduce non-specific adsorption of interfering proteins and molecules within the GI fluids. For the passivated PSi aptasensor we simulate continuous in vivo biosensing conditions, demonstrating that the aptasensor could successfully detect the target in a continuous manner without any need for surface washing after the target protein binding events, at a clinically relevant range. Furthermore, we simulate biosensing conditions within a smart capsule, in which the aptasensor is occasionally exposed to GI fluids in flow or via repeated cycles of injection and static incubation events. Such biosensor can be implemented within ingestible capsule devices and used for in situ biomarker detection in the GI tract.

Connected healthcare: Improving patient care using digital health technologies

Now more than ever, traditional healthcare models are being overhauled with digital technologies of Healthcare 4.0 increasingly adopted. Worldwide, digital devices are improving every stage of the patient care pathway. For one, sensors are being used to monitor patient metrics 24/7, permitting swift diagnosis and interventions. At the treatment stage, 3D printers are under investigation for the concept of personalised medicine by allowing patients access to on-demand, customisable therapeutics. Robots are also being explored for treatment, by empowering precision surgery, rehabilitation, or targeted drug delivery. Within medical logistics, drones are being leveraged to deliver critical treatments to remote areas, collect samples, and even provide emergency aid. To enable seamless integration within healthcare, the Internet of Things technology is being exploited to form closed-loop systems that remotely communicate with one another. This review outlines the most promising healthcare technologies and devices, their strengths, drawbacks, and opportunities for clinical adoption.

Smart pills for gastrointestinal diagnostics and therapy

Ingestible smart pills have the potential to be a powerful clinical tool in the diagnosis and treatment of gastrointestinal disease. Though examples of this technology, such as capsule endoscopy, have been successfully translated from the lab into clinically used products, there are still numerous challenges that need to be overcome. This review gives an overview of the research being done in the area of ingestible smart pills and reports on the technical challenges in this field.

Divergent Responses of Floral Traits of Lonicera nervosa to Altitudinal Gradients at the Eastern Margin of Hengduan Mountains

Understanding phenotypic responses is crucial for predicting and managing the effects of environmental change on native species. Color and display size are typically used to evaluate the utilization value of ornamental plants, which are also important ornamental characters of Lonicera nervosa Maxim. (L. nervosa). However, there is limited documentation of its floral environmental adaptation. The environmental conditions for the development of an organism changes with altitudinal variation. The aim of this research was to find flower trait variability maintenance and the tradeoff among the organs in five different populations of L. nervosa growing at distinct altitudes. We investigated the distribution patterns of floral color, floral display, and biomass tradeoff along a 700-m altitude gradient from 2,950 to 3,650 m. One-way ANOVA analysis was performed to assess the variability of flower traits and floral color across different altitudes. Moreover, correlations and tradeoffs between flowers and vegetative organs were also observed at different altitude ranges. The results indicated that L. nervosa flowers had a strong adaptability along the elevation and divergent altitude-range-specific patterns, which was divided by an altitude breakpoint at around 3,300 m. Below 3,300 m, petal lightness (petal L) decreased, but total floral display area (TFDA), individual floral dry mass (IFDM), and total floral dry mass (TFDM) increased with an increase in altitude. Whereas, above 3,300 m no significant difference was observed in petal L, TFDA, IFDM, and TFDM decreased slightly with an increase in altitude. The responsibility for the selection on floral color at a lower altitude was stronger than that at a higher altitude, while the selection agents on floral biomass had significant effects within the entire altitude range. However, the effects on floral biomass were opposite on both sides of 3,300 m. Thus, floral trait and floral color can be useful indicators for the domestication of horticultural plants and help to evaluate and initiate management and conservation actions.

Use of artificial intelligence for detection of gastric lesions by magnetically controlled capsule endoscopy

BACKGROUND AND AIMS

Magnetically controlled capsule endoscopy (MCE) has become an efficient diagnostic modality for gastric diseases. We developed a novel automatic gastric lesion detection system to assist in diagnosis and reduce inter-physician variations. This study aimed to evaluate the diagnostic capability of the computer-aided detection system for MCE images.

METHODS

We developed a novel automatic gastric lesion detection system based on a convolutional neural network (CNN) and faster region-based convolutional neural network (RCNN). A total of 1,023,955 MCE images from 797 patients were used to train and test the system. These images were divided into 7 categories (erosion, polyp, ulcer, submucosal tumor, xanthoma, normal mucosa, and invalid images). The primary endpoint was the sensitivity of the system.

RESULTS

The system detected gastric focal lesions with 96.2% sensitivity (95% confidence interval [CI], 95.7%-96.5%), 76.2% specificity (95% CI, 75.97%-76.3%), 16.0% positive predictive value (95% CI, 15.7%-16.3%), 99.7% negative predictive value (95% CI, 99.74%-99.79%), and 77.1% accuracy (95% CI, 76.9%-77.3%) (sensitivity was 99.3% for erosions; 96.5% for polyps; 89.3% for ulcers; 87.2% for submucosal tumors; 90.6% for xanthomas; 67.8% for normal; and 96.1% for invalid images). Analysis of the receiver operating characteristic curve showed that the area under the curve for all positive images was 0.84. Image processing time was 44 milliseconds per image for the system and 0.38 ± 0.29 seconds per image for clinicians (P < .001). The kappa value of 2 times repeated reads was 1.

CONCLUSIONS

The CNN faster-RCNN-based diagnostic program system showed good performance in diagnosing gastric focal lesions in MCE images.

Monitoring Chemistry In Situ with a Smart Stirrer: A Magnetic Stirrer Bar with an Integrated Process Monitoring System

Inspired by the miniaturization and efficiency of the sensors for telemetry, we have developed a device that provides the functionalities of laboratory magnetic stirring and integrated multisensor monitoring of various chemical reaction parameters. The device, called "Smart Stirrer", when immersed in a solution, can in situ monitor physical properties of the chemical reaction such as the temperature, conductivity, visible spectrum, opaqueness, stirring rate, and viscosity. This data is transmitted real-time over a wireless connection to an external system, such as a PC or smartphone. The flexible open-source software architecture allows effortless programming of the operation parameters of the Smart Stirrer in accordance with the end-user needs. The concept of the Smart Stirrer device with an integrated process monitoring system has been demonstrated in a series of experiments showing its capability for many hours of continuous telemetry with fine accuracy and a high data rate. Such a device can be used in conventional research laboratories, industrial production lines, flow reactors, and others where it can log the state of the process to ensure repeatability and operational consistency.

Development of innovative tools for investigation of nutrient-gut interaction

The gastrointestinal tract is the key interface between the ingesta and the human body. There is wide recognition that the gastrointestinal response to nutrients or bioactive compounds, particularly the secretion of numerous hormones, is critical to the regulation of appetite, body weight and blood glucose. This concept has led to an increasing focus on “gut-based” strategies for the management of metabolic disorders, including type 2 diabetes and obesity. Understanding the underlying mechanisms and downstream effects of nutrient-gut interactions is fundamental to effective translation of this knowledge to clinical practice. To this end, an array of research tools and platforms have been developed to better understand the mechanisms of gut hormone secretion from enteroendocrine cells. This review discusses the evolution of in vitro and in vivo models and the integration of innovative techniques that will ultimately enable the development of novel therapies for metabolic diseases.

Automatic Detection of Intestinal Bleeding using an Optical Sensor for Wireless Capsule Endoscopy

Wireless capsule endoscopy (WCE) has been an effective and safe way to diagnose gastrointestinal (GI) disorders, such as, colon cancers, polyps and bleeding. The detection of bleeding and other anomalies is currently determined through conventional visual inspection of the WCE images by the physicians. An on-chip bleeding sensor is thus required, that can perform an automatic prescreening of the bleeding areas in real-time using blood's optical properties to assist the diagnosis. In this study, a spectrophotometer was initially used to evaluate the chromatic properties of blood. It is found that the reflection ratio pairs of 700 nm to 630 nm and 480 nm to 530 nm provide important statistics to separate blood from non-blood samples. It has been implemented hardware using small LEDs and photodiodes to validate the results. Therefore, the proposed sensor system works as a good candidate to be integrated in a WCE device to detect GI bleeding quickly and in real-time.

Ingestible Sensors and Sensing Systems for Minimally Invasive Diagnosis and Monitoring: The Next Frontier in Minimally Invasive Screening

Ingestible electronic systems that are capable of embedded sensing, particularly within the gastrointestinal (GI) tract and its accessory organs, have the potential to screen for diseases that are difficult if not impossible to detect at an early stage using other means. Furthermore, these devices have the potential to (1) reduce labor and facility costs for a variety of procedures, (2) promote research for discovering new biomarker targets for associated pathologies, (3) promote the development of autonomous or semiautonomous diagnostic aids for consumers, and (4) provide a foundation for epithelially targeted therapeutic interventions. These technological advances have the potential to make disease surveillance and treatment far more effective for a variety of conditions, allowing patients to lead longer and more productive lives. This review will examine the conventional techniques, as well as ingestible sensors and sensing systems that are currently under development for use in disease screening and diagnosis for GI disorders. Design considerations, fabrication, and applications will be discussed.

A wireless tattooing capsule endoscope using external electromagnetic actuation and chemical reaction pressure

In this paper, we present a tattooing capsule endoscope (TCE) that can localize an intestinal lesion or tumor for a preoperative laparoscopic surgery. The TCE is based on a wireless capsule endoscope (WCE) structure and can be actively controlled by an external electromagnetic actuation system to move, observe, and mark the target lesion in the gastrointestinal (GI) tract. The TCE is designed to perform capsule locomotion, needle extrusion and intrusion motions, and ink injection. First, the TCE is controlled to move to the target lesion during GI tract diagnosis via a capsule endoscopic camera. Further, a tattooing needle is extruded by an electromagnetically controlled mechanism to puncture the tissue. Finally, the tattooing ink is injected by the chemically reacted carbon dioxide gas pressure that is triggered by a shape memory alloy wire and a reed switch. The reed switch is also activated by the external magnetic field flux density. The suggested methods were verified by the ex-vivo experiments. The TCE prototype was able to move to the target lesion and inject the ink beneath the mucosa layer safely, thereby leaving a visible tattooed mark for surgical lesion identification. The proposed TCE method can accelerate the development of functionalities as well as tattooing procedures of the WCE in the GI tract.

Gastrointestinal diagnosis using non-white light imaging capsule endoscopy

Capsule endoscopy (CE) has proved to be a powerful tool in the diagnosis and management of small bowel disorders since its introduction in 2001. However, white light imaging (WLI) is the principal technology used in clinical CE at present, and therefore, CE is limited to mucosal inspection, with diagnosis remaining reliant on visible manifestations of disease. The introduction of WLI CE has motivated a wide range of research to improve its diagnostic capabilities through integration with other sensing modalities. These developments have the potential to overcome the limitations of WLI through enhanced detection of subtle mucosal microlesions and submucosal and/or transmural pathology, providing novel diagnostic avenues. Other research aims to utilize a range of sensors to measure physiological parameters or to discover new biomarkers to improve the sensitivity, specificity and thus the clinical utility of CE. This multidisciplinary Review summarizes research into non-WLI CE devices by organizing them into a taxonomic structure on the basis of their sensing modality. The potential of these capsules to realize clinically useful virtual biopsy and computer-aided diagnosis (CADx) is also reported.

Ingestible Sensors

Ingestible sensing capsules are fast emerging as a critical technology that has the ability to greatly impact health, nutrition, and clinical areas. These ingestible devices are noninvasive and hence are very attractive for customers. With widespread access to smart phones connected to the Internet, the data produced by this technology can be readily seen and reviewed online, and accessed by both users and physicians. The outputs provide invaluable information to reveal the state of gut health and disorders as well as the impact of food, medical supplements, and environmental changes on the gastrointestinal tract. One unique feature of such ingestible sensors is that their passage through the gut lumen gives them access to each individual organ of the gastrointestinal tract. Therefore, ingestible sensors offer the ability to gather images and monitor luminal fluid and the contents of each gut segment including electrolytes, enzymes, metabolites, hormones, and the microbial communities. As such, an incredible wealth of knowledge regarding the functionality and state of health of individuals through key gut biomarkers can be obtained. This Review presents an overview of the gut structure and discusses current and emerging digestible technologies. The text is an effort to provide a comprehensive overview of ingestible sensing capsules, from both a body physiology point of view as well as a technological view, and to detail the potential information that they can generate.