Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain

Use of 3D Printing Techniques to Fabricate Implantable Microelectrodes for Electrochemical Detection of Biomarkers in the Early Diagnosis of Cardiovascular and Neurodegenerative Diseases

This Review provides a comprehensive overview of 3D printing techniques to fabricate implantable microelectrodes for the electrochemical detection of biomarkers in the early diagnosis of cardiovascular and neurodegenerative diseases. Early diagnosis of these diseases is crucial to improving patient outcomes and reducing healthcare systems' burden. Biomarkers serve as measurable indicators of these diseases, and implantable microelectrodes offer a promising tool for their electrochemical detection. Here, we discuss various 3D printing techniques, including stereolithography (SLA), digital light processing (DLP), fused deposition modeling (FDM), selective laser sintering (SLS), and two-photon polymerization (2PP), highlighting their advantages and limitations in microelectrode fabrication. We also explore the materials used in constructing implantable microelectrodes, emphasizing their biocompatibility and biodegradation properties. The principles of electrochemical detection and the types of sensors utilized are examined, with a focus on their applications in detecting biomarkers for cardiovascular and neurodegenerative diseases. Finally, we address the current challenges and future perspectives in the field of 3D-printed implantable microelectrodes, emphasizing their potential for improving early diagnosis and personalized treatment strategies.</p

The Boston University Photonics Center annual report 2014-2015

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2014-2015 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This has been a good year for the Photonics Center. In the following pages, you will see that the center’s faculty received prodigious honors and awards, generated more than 100 notable scholarly publications in the leading journals in our field, and attracted $18.6M in new research grants/contracts. Faculty and staff also expanded their efforts in education and training, and were awarded two new National Science Foundation– sponsored sites for Research Experiences for Undergraduates and for Teachers. As a community, we hosted a compelling series of distinguished invited speakers, and emphasized the theme of Advanced Materials by Design for the 21st Century at our annual symposium. We continued to support the National Photonics Initiative, and are a part of a New York–based consortium that won the competition for a new photonics- themed node in the National Network of Manufacturing Institutes. Highlights of our research achievements for the year include an ambitious new DoD-sponsored grant for Multi-Scale Multi-Disciplinary Modeling of Electronic Materials led by Professor Enrico Bellotti, continued support of our NIH-sponsored Center for Innovation in Point of Care Technologies for the Future of Cancer Care led by Professor Catherine Klapperich, a new award for Personalized Chemotherapy Through Rapid Monitoring with Wearable Optics led by Assistant Professor Darren Roblyer, and a new award from DARPA to conduct research on Calligraphy to Build Tunable Optical Metamaterials led by Professor Dave Bishop. We were also honored to receive an award from the Massachusetts Life Sciences Center to develop a biophotonics laboratory in our Business Innovation Center

The Boston University Photonics Center annual report 2014-2015

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2014-2015 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This has been a good year for the Photonics Center. In the following pages, you will see that the center’s faculty received prodigious honors and awards, generated more than 100 notable scholarly publications in the leading journals in our field, and attracted $18.6M in new research grants/contracts. Faculty and staff also expanded their efforts in education and training, and were awarded two new National Science Foundation– sponsored sites for Research Experiences for Undergraduates and for Teachers. As a community, we hosted a compelling series of distinguished invited speakers, and emphasized the theme of Advanced Materials by Design for the 21st Century at our annual symposium. We continued to support the National Photonics Initiative, and are a part of a New York–based consortium that won the competition for a new photonics- themed node in the National Network of Manufacturing Institutes. Highlights of our research achievements for the year include an ambitious new DoD-sponsored grant for Multi-Scale Multi-Disciplinary Modeling of Electronic Materials led by Professor Enrico Bellotti, continued support of our NIH-sponsored Center for Innovation in Point of Care Technologies for the Future of Cancer Care led by Professor Catherine Klapperich, a new award for Personalized Chemotherapy Through Rapid Monitoring with Wearable Optics led by Assistant Professor Darren Roblyer, and a new award from DARPA to conduct research on Calligraphy to Build Tunable Optical Metamaterials led by Professor Dave Bishop. We were also honored to receive an award from the Massachusetts Life Sciences Center to develop a biophotonics laboratory in our Business Innovation Center

Applications of the Internet of Medical Things to Type 1 Diabetes Mellitus

Type 1 Diabetes Mellitus (DM1) is a condition of the metabolism typified by persistent hyperglycemia as a result of insufficient pancreatic insulin synthesis. This requires patients to be aware of their blood glucose level oscillations every day to deduce a pattern and anticipate future glycemia, and hence, decide the amount of insulin that must be exogenously injected to maintain glycemia within the target range. This approach often suffers from a relatively high imprecision, which can be dangerous. Nevertheless, current developments in Information and Communication Technologies (ICT) and innovative sensors for biological signals that might enable a continuous, complete assessment of the patient’s health provide a fresh viewpoint on treating DM1. With this, we observe that current biomonitoring devices and Continuous Glucose Monitoring (CGM) units can easily obtain data that allow us to know at all times the state of glycemia and other variables that influence its oscillations. A complete review has been made of the variables that influence glycemia in a T1DM patient and that can be measured by the above means. The communications systems necessary to transfer the information collected to a more powerful computational environment, which can adequately handle the amounts of data collected, have also been described. From this point, intelligent data analysis extracts knowledge from the data and allows predictions to be made in order to anticipate risk situations. With all of the above, it is necessary to build a holistic proposal that allows the complete and smart management of T1DM. This approach evaluates a potential shortage of such suggestions and the obstacles that future intelligent IoMT-DM1 management systems must surmount. Lastly, we provide an outline of a comprehensive IoMT-based proposal for DM1 management that aims to address the limits of prior studies while also using the disruptive technologies highlighted beforePartial funding for open access charge: Universidad de Málag

Neuroenhancement in Military Personnel::Conceptual and Methodological Promises and Challenges

Military personnel face harsh conditions that strain their physical and mental well-being, depleting resources necessary for sustained operational performance. Future operations will impose even greater demands on soldiers in austere environments with limited support, and new training and technological approaches are essential. This report highlights the progress in cognitive neuroenhancement research, exploring techniques such as neuromodulation and neurofeedback, and emphasizes the inherent challenges and future directions in the field of cognitive neuroenhancement for selection, training, operations, and recovery

AI in Medical Imaging Informatics: Current Challenges and Future Directions

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine

Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer: Improvements using Radiomics

Multimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics. © 2019 Wolters Kluwer Health, Inc. All rights reserved

Wearable technology for one health: Charting the course of dermal biosensing

Over the last decade, a significant paradigm shift has been observed towards leveraging less invasive biological fluids—such as skin interstitial fluid (ISF), sweat, tears, and saliva—for health monitoring. This evolution seeks to transcend traditional, invasive blood-based methods, offering a more accessible approach to health monitoring for non-specialized personnel. Skin ISF, with its profound resemblance to blood, emerges as a pivotal medium for the real-time, minimally invasive tracking of a broad spectrum of biomarkers, thus becoming an invaluable asset for correlating with blood-based data. Our exploration delves deeply into the development of wearable molecular biosensors, spotlighting dermal sensors for their pivotal roles across both clinical and everyday health monitoring scenarios and underscoring their contributions to the holistic One Health initiative. In bringing forward the myriad challenges that permeate this field, we also project future directions, notably the potential of skin ISF as a promising candidate for continuous health tracking. Moreover, this paper aims to catalyse further exploration and innovation by presenting a curated selection of seminal technological advancements. Amidst the saturated landscape of analytical literature on translational challenges, our approach distinctly seeks to highlight recent developments. In attracting a wider spectrum of research groups to this versatile domain, we endeavour to broaden the collective understanding of its trajectory and potential, mapping the evolution of wearable biosensor technology. This strategy not only illuminates the transformative impact of wearable biosensors in reshaping health diagnostics and personalized medicine but also fosters increased participation and progress within the field. Distinct from recent manuscripts in this domain, our review serves as a distillation of key concepts, elucidating pivotal papers that mark the latest advancements in wearable sensors. Through presenting a curated collection of landmark studies and offering our perspectives on the challenges and forward paths, this paper seeks to guide new entrants in the area. We delineate a division between wearable epidermal and subdermal sensors—focusing on the latter as the future frontier—thereby establishing a unique discourse within the ongoing narrative on wearable sensing technologies

Linking quantitative radiology to molecular mechanism for improved vascular disease therapy selection and follow-up

Objective: Therapeutic advancements in atherosclerotic cardiovascular disease have improved the prevention of ischemic stroke and myocardial infarction. However, diagnostic methods for atherosclerotic plaque phenotyping to aid individualized therapy are lacking. In this thesis, we aimed to elucidate plaque biology through the analysis of computed-tomography angiography (CTA) with sufficient sensitivity and specificity to capture the differentiated drivers of the disease. We then aimed to use such data to calibrate a systems biology model of atherosclerosis with adequate granularity to be clinically relevant. Such development may be possible with computational modeling, but given, the multifactorial biology of atherosclerosis, modeling must be based on complete biological networks that capture protein-protein interactions estimated to drive disease progression. Approach and Results: We employed machine intelligence using CTA paired with a molecular assay to determine cohort-level associations and individual patient predictions. Examples of predicted transcripts included ion transporters, cytokine receptors, and a number of microRNAs. Pathway analyses elucidated enrichment of several biological processes relevant to atherosclerosis and plaque pathophysiology. The ability of the models to predict plaque gene expression from CTAs was demonstrated using sequestered patients with transcriptomes of corresponding lesions. We further performed a case study exploring the relationship between biomechanical quantities and plaque morphology, indicating the ability to determine stress and strain from tissue characteristics. Further, we used a uniquely constituted plaque proteomic dataset to create a comprehensive systems biology disease model, which was finally used to simulate responses to different drug categories in individual patients. Individual patient response was simulated for intensive lipid-lowering, anti-inflammatory drugs, anti-diabetic, and combination therapy. Plaque tissue was collected from 18 patients with 6735 proteins at two locations per patient. 113 pathways were identified and included in the systems biology model of endothelial cells, vascular smooth muscle cells, macrophages, lymphocytes, and the integrated intima, altogether spanning 4411 proteins, demonstrating a range of 39-96% plaque instability. Simulations of drug responses varied in patients with initially unstable lesions from high (20%, on combination therapy) to marginal improvement, whereas patients with initially stable plaques showed generally less improvement, but importantly, variation across patients. Conclusion: The results of this thesis show that atherosclerotic plaque phenotyping by multi-scale image analysis of conventional CTA can elucidate the molecular signatures that reflect atherosclerosis. We further showed that calibrated system biology models may be used to simulate drug response in terms of atherosclerotic plaque instability at the individual level, providing a potential strategy for improved personalized management of patients with cardiovascular disease. These results hold promise for optimized and personalized therapy in the prevention of myocardial infarction and ischemic stroke, which warrants further investigations in larger cohorts