New Internet of Medical Things for Home-Based Treatment of Anorectal Disorders

Home-based healthcare provides a viable and cost-effective method of delivery for resource- and labour-intensive therapies, such as rehabilitation therapies, including anorectal biofeedback. However, existing systems for home anorectal biofeedback are not able to monitor patient compliance or assess the quality of exercises performed, and as a result have yet to see wide spread clinical adoption. In this paper, we propose a new Internet of Medical Things (IoMT) system to provide home-based biofeedback therapy, facilitating remote monitoring by the physician. We discuss our user-centric design process and the proposed architecture, including a new sensing probe, mobile app, and cloud-based web application. A case study involving biofeedback training exercises was performed. Data from the IoMT was compared against the clinical standard, high-definition anorectal manometry. We demonstrated the feasibility of our proposed IoMT in providing anorectal pressure profiles equivalent to clinical manometry and its application for home-based anorectal biofeedback therapy.

Genetic overlap between Parkinson disease and inflammatory bowel disease

Importance Parkinson disease (PD) and inflammatory bowel disease (IBD) have been associated, implying shared pathophysiology. Characterizing genetic pleiotropy between the two conditions aids the exploration of common etiology. Objective To estimate the genetic correlation between PD and IBD and to identify specific loci influencing both conditions. Design Genetic study with applications of high definition likelihood and conditional false discovery rate (FDR) framework. Setting The study was based on summary statistics of genome-wide association studies (GWAS). Participants The PD GWAS comprised 37,688 cases and 981,372 controls, and the IBD GWAS included 25,042 cases and 34,915 controls. Participants were of mixed ethnicity. Exposures None. Main Outcomes and Measures The main outcomes were a set of single nucleotide polymorphisms (SNPs) identified by conditional FDR analysis as jointly associated with PD and IBD. Results Weak but statistically significant genetic correlations were detected for PD with both Crohn's disease (CD) and ulcerative colitis (UC), the two main subtypes of IBD. A total of 1333 SNPs in 28 genomic loci and 1915 SNPs in 22 loci were jointly associated with PD-CD and PD-UC, respectively, at conjunctional FDR under 0.01. The pleiotropic loci appeared distinctive for PD-CD and PD-UC, are mostly novel and comprise loci with either same or opposing genetic effects on the two phenotypes. Positional and eQTL mapping prioritized 316 PD-CD and 303 PD-UC genes, among which only <10% are differentially expressed in both colon and substantia nigra. The KEGG pathways enriched by all prioritized genes were highly concordant between PD-CD and PD-UC, with the majority being related to immune and/or autoimmune dysfunction. Conclusions and Relevance Overall, we found robust evidence for a genetic link between PD and each subtype of IBD. The identified genetic overlap is complex at the locus and gene levels, indicating the presence of both common etiology and antagonistic pleiotropy. At the functional level, our results highlighted a central role of host immunity and/or autoimmunity in the PD-IBD relationship.

Fluorescence visualization of deep-buried hollow organs

High-definition fluorescence imaging of deep-buried organs is still challenging. Here, we develop bright fluorophores emitting to 1700 nm by enhancing electron donating ability and reducing donor-acceptor distance. In parallel, the heavy water functions as the solvent of the delicately designed fluorophores, effectively reducing the fluorescent signal loss caused by the absorption by water. The near-infrared-II (NIR-II, 900-1880 nm) emission is eventually recovered and extended beyond 1400 nm. Compared with the spectral range beyond 1500 nm, the one beyond 1400 nm gives a more accurate fluorescence visualization of the hollow organs, owing to the absorption-induced scattering suppression. In addition, the intraluminal lesions containing much water are simultaneously negatively stained, leading to a stark contrast for precise diagnosis. Eventually, the intraluminally perfused fluorescent probes are excreted from mice and thus no obvious side effects emerge. This general method can provide new avenues for future biomedical imaging of deep and highly scattering tissues.

Virtual Bronchoscopy-Guided Transbronchial Biopsy Simulation Using a Head-Mounted Display: A New Style of Flexible Bronchoscopy

Background/need. The increases in reference images and information during bronchoscopy using virtual bronchoscopic navigation (VBN) and fluoroscopy has potentially created the need for support using a head-mounted display (HMD) because bronchoscopists feel difficulty to see displays that are at a distance from them and turn their head and body in various directions. Methodology and device description. The binocular see-through Moverio BT-35E Smart Glasses can be connected via a high-definition multimedia interface and have a 720p high-definition display. We developed a system that converts fluoroscopic (live and reference), VBN, and bronchoscopic image signals through a converter and references them using the Moverio BT-35E. Preliminary results. We performed a virtual bronchoscopy-guided transbronchial biopsy simulation using the system. Four experienced pulmonologists performed a simulated bronchoscopy of 5 cases each with the Moverio BT-35E glasses, using bronchoscopy training model. For all procedures, the bronchoscope was advanced successfully into the target bronchus according to the VBN image. None of the operators reported eye or body fatigue during or after the procedure. Current status. This small-scale simulation study suggests the feasibility of using a HMD during bronchoscopy. For clinical use, it is necessary to evaluate the safety and usefulness of the system in larger clinical trials in the future.

Analysis of the Application Value of X-Ray Digital Tomographic Fusion Technique in Urinary System Diseases

Objective. To explore the application value of the X-ray digital tomographic fusion technique in the diagnosis of urinary system diseases. Methods. 500 patients with suspected urinary diseases in our hospital were examined by three methods: X-ray digital tomographic fusion imaging (DTS), intravenous pyelography (IVP), and abdominal plain film (KUB), and the image quality before and after tomographic fusion was objectively evaluated. The image quality could be divided into three grades: excellent, good, and poor. Results. The image excellent rate of DTS (88%) was higher than that of IVP (27.5%). The sensitivity of DTS in the diagnosis of renal cyst and space occupying of the bladder was higher than that of IVP ( P < 0.05 ). The accuracy rate of DTS in the diagnosis of urinary calculi was 93.33%, higher than 63.3% of KUB ( P < 0.001 ). The accuracy rate of DTS in the diagnosis of ureteral stricture was 90%, higher than 65% of IVP ( P = 0.03 ). The accuracy of DTS in the diagnosis of hydronephrosis was higher than that of IVP and KUB ( P < 0.05 ). Conclusion. In the examination of urinary system-related diseases, high-definition images can be obtained by timely using sectional fusion technology. Compared with conventional IVP, space occupying lesions such as the bladder and kidney can be displayed more clearly with the help of the tomographic fusion technique, which is helpful to improve the possibility of finding lesions and is of great significance in clinical application.

Deep Learning Based Multi-Modal Biometric Security System Using Visible Light Communication

Multi-biometric system is an advanced technology which has a wide application space in the field of information security. This work proposes the design of a personal identification system based on a combination of biometric inputs such as face, finger vein, iris and fingerprint. Viola jones algorithm is used for face detection. Convolutional neural network (CNN) with different optimisers are used to steeply raise the image texture and extract high definition distinct features of the input images. The deep dream image algorithm accompanies CNN by visualizing these images and by highlighting the image features learnt by the network. These images are used for understanding and diagnosing network behaviour. This network obtains a high recognition rate, which proves to be better performing than traditional algorithms. In addition to these, a high-speed advanced wireless communication technology (Li-Fi) is used in combination with GSM which would act as an alert system that effectively helps in notifying the supervisory authority, if the system is being trespassed without proper authentication.