Architecture and Applications of IoT Devices in Socially Relevant Fields

Number of IoT enabled devices are being tried and introduced every year and there is a healthy competition among researched and businesses to capitalize the space created by IoT, as these devices have a great market potential. Depending on the type of task involved and sensitive nature of data that the device handles, various IoT architectures, communication protocols and components are chosen and their performance is evaluated. This paper reviews such IoT enabled devices based on their architecture, communication protocols and functions in few key socially relevant fields like health care, farming, firefighting, women/individual safety/call for help/harm alert, home surveillance and mapping as these fields involve majority of the general public. It can be seen, to one's amazement, that already significant number of devices are being reported on these fields and their performance is promising. This paper also outlines the challenges involved in each of these fields that require solutions to make these devices reliableComment: 1

Opto-physiological modeling applied to photoplethysmographic cardiovascular assessment

This paper presents opto-physiological (OP) modeling and its application in cardiovascular assessment techniques based on photoplethysmography (PPG). Existing contact point measurement techniques, i.e., pulse oximetry probes, are compared with the next generation noncontact and imaging implementations, i.e., non-contact reflection and camera-based PPG. The further development of effective physiological monitoring techniques relies on novel approaches to OP modeling that can better inform the design and development of sensing hardware and applicable signal processing procedures. With the help of finite-element optical simulation, fundamental research into OP modeling of photoplethysmography is being exploited towards the development of engineering solutions for practical biomedical systems. This paper reviews a body of research comprising two OP models that have led to significant progress in the design of transmission mode pulse oximetry probes, and approaches to 3D blood perfusion mapping for the interpretation of cardiovascular performance

The design of a low-cost pulse sensor for remote healthcare

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2020Ghana has a low doctor to patient ratio, and to help ease pressure from the health care sector, interest in remote healthcare is growing. This paper explores design options for low-cost pulse monitors for use by patients who require access to healthcare but do not have the means to visit regularly for consultation. The product measures their heart rate and sends the data to a remote database using a mobile app implemented with flutter as a gateway. Patients can view their health trends in the app, and health professionals can monitor their patients using the app. The circuit for this pulse sensor was designed in Eagle and implemented on a breadboard to show that the non-invasive technique of acquiring heart rate using infrared light-emitting diodes (LEDs) could be used favorably on persons with darker skin tones. The research project designed an algorithm for the task and compared this with an existing algorithm using PPG and ECG datasets from medical databases as well as PPG signals generated from the pulse sensor. Heart rates detected ranged from 30-300 beats/minute. 5 datasets from the device were statistically compared to PPG signals from a medical database to ascertain their reliability.Ashesi Universit

Pragmatic Evaluation of Health Monitoring & Analysis Models from an Empirical Perspective

Implementing and deploying several linked modules that can conduct real-time analysis and recommendation of patient datasets is necessary for designing health monitoring and analysis models. These databases include, but are not limited to, blood test results, computer tomography (CT) scans, MRI scans, PET scans, and other imaging tests. A combination of signal processing and image processing methods are used to process them. These methods include data collection, pre-processing, feature extraction and selection, classification, and context-specific post-processing. Researchers have put forward a variety of machine learning (ML) and deep learning (DL) techniques to carry out these tasks, which help with the high-accuracy categorization of these datasets. However, the internal operational features and the quantitative and qualitative performance indicators of each of these models differ. These models also demonstrate various functional subtleties, contextual benefits, application-specific constraints, and deployment-specific future research directions. It is difficult for researchers to pinpoint models that perform well for their application-specific use cases because of the vast range of performance. In order to reduce this uncertainty, this paper discusses a review of several Health Monitoring & Analysis Models in terms of their internal operational features & performance measurements. Readers will be able to recognise models that are appropriate for their application-specific use cases based on this discussion. When compared to other models, it was shown that Convolutional Neural Networks (CNNs), Masked Region CNN (MRCNN), Recurrent NN (RNN), Q-Learning, and Reinforcement learning models had greater analytical performance. They are hence suitable for clinical use cases. These models' worse scaling performance is a result of their increased complexity and higher implementation costs. This paper compares evaluated models in terms of accuracy, computational latency, deployment complexity, scalability, and deployment cost metrics to analyse such scenarios. This comparison will help users choose the best models for their performance-specific use cases. In this article, a new Health Monitoring Metric (HMM), which integrates many performance indicators to identify the best-performing models under various real-time patient settings, is reviewed to make the process of model selection even easier for real-time scenarios

An inclusive survey of contactless wireless sensing: a technology used for remotely monitoring vital signs has the potential to combating COVID-19

With the Coronavirus pandemic showing no signs of abating, companies and governments around the world are spending millions of dollars to develop contactless sensor technologies that minimize the need for physical interactions between the patient and healthcare providers. As a result, healthcare research studies are rapidly progressing towards discovering innovative contactless technologies, especially for infants and elderly people who are suffering from chronic diseases that require continuous, real-time control, and monitoring. The fusion between sensing technology and wireless communication has emerged as a strong research candidate choice because wearing sensor devices is not desirable by patients as they cause anxiety and discomfort. Furthermore, physical contact exacerbates the spread of contagious diseases which may lead to catastrophic consequences. For this reason, research has gone towards sensor-less or contactless technology, through sending wireless signals, then analyzing and processing the reflected signals using special techniques such as frequency modulated continuous wave (FMCW) or channel state information (CSI). Therefore, it becomes easy to monitor and measure the subject’s vital signs remotely without physical contact or asking them to wear sensor devices. In this paper, we overview and explore state-of-the-art research in the field of contactless sensor technology in medicine, where we explain, summarize, and classify a plethora of contactless sensor technologies and techniques with the highest impact on contactless healthcare. Moreover, we overview the enabling hardware technologies as well as discuss the main challenges faced by these systems.This work is funded by the scientific and technological research council of Turkey (TÜBITAK) under grand 119E39

Recent Advances in Wearable Sensing Technologies

Wearable sensing technologies are having a worldwide impact on the creation of novel business opportunities and application services that are benefiting the common citizen. By using these technologies, people have transformed the way they live, interact with each other and their surroundings, their daily routines, and how they monitor their health conditions. We review recent advances in the area of wearable sensing technologies, focusing on aspects such as sensor technologies, communication infrastructures, service infrastructures, security, and privacy. We also review the use of consumer wearables during the coronavirus disease 19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and we discuss open challenges that must be addressed to further improve the efficacy of wearable sensing systems in the future

A universal platform for electronic health records for low resource hospitals

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, May 2022Due to the lack of health management systems and technical know-how, most hospitals in Ghana continue to use a file-based system approach. While this method works, it is ineffective for storing and managing medical records. It is difficult to organize and maintain track of information that's dispersed all over the place. Likewise, there is no smart system in place to help transfer medical data from an instrument into the database system of a hospital management to aid in efficiency. Hence, this paper examines the shortcomings in the management methods utilized by Ghana's healthcare institutions, as well as the inefficiencies that result. It goes into details on the nature of electronic health records and the benefits they provide, such as making distance communication and data interchange more accessible, improving the quality of medical treatment, and so on. The project is broken down into three sections. The project's initial goal is to create a hospital management system that eliminates the need for paper medical records. Followed by the transfer of patient data from one hospital to another however, the hospitals must be on the same management system. Finally, to aid in making the system smart is the creation a pulse oximeter that sends the SpO2 value to the hospital management system's database. The report finishes by elaborating on the project's challenges, limitations, and a recommendation for what to do next.Ashesi Universit

Multigenerational Independent Colony for Extraterrestrial Habitation, Autonomy, and Behavior Health (MICEHAB): An Investigation of a Long Duration, Partial Gravity, Autonomous Rodent Colony

The path from Earth to Mars requires exploration missions to be increasingly Earth-independent as the foundation is laid for a sustained human presence in the following decades. NASA pioneering of Mars will expand the boundaries of human exploration, as a sustainable presence on the surface requires humans to successfully reproduce in a partial gravity environment independent from Earth intervention. Before significant investment is made in capabilities leading to such pioneering efforts, the challenges of multigenerational mammalian reproduction in a partial gravity environment need be investigated. The Multi-generational Independent Colony for Extraterrestrial Habitation, Autonomy, and Behavior health is designed to study these challenges. The proposed concept is a conceptual, long duration, autonomous habitat designed to house rodents in a partial gravity environment with the goal of understanding the effects of partial gravity on mammalian reproduction over multiple generations and how to effectively design such a facility to operate autonomously while keeping the rodents healthy in order to achieve multiple generations. All systems are designed to feed forward directly to full-scale human missions to Mars. This paper presents the baseline design concept formulated after considering challenges in the mission and vehicle architectures such as: vehicle automation, automated crew health management/medical care, unique automated waste disposal and hygiene, handling of deceased crew members, reliable long-duration crew support systems, and radiation protection. This concept was selected from an architectural trade space considering the balance between mission science return and robotic and autonomy capabilities. The baseline design is described in detail including: transportation and facility operation constraints, artificial gravity system design, habitat design, and a full-scale mock-up demonstration of autonomous rodent care facilities. The proposed concept has the potential to integrate into existing mission architectures in order to achieve exploration objectives, and to demonstrate and mature common capabilities that enable a range of destinations and missions

Dual-modality thermoacoustic and photoacoustic imaging

Diagnosis of early breast cancer is the key to survival. The combined contrasts from thermoacoustic and photoacoustic tomography: TAT and PAT) can potentially predict early stage breast cancer. We have designed and engineered a breast imaging system integrating both thermoacoustic and photoacoustic imaging techniques to achieve dual-contrast: microwave and light absorption), non-ionizing, low-cost, high-resolution, three-dimensional breast imaging. We have also developed a novel concept of using a negative acoustic lens to increase the acceptance angle of an unfocused large-area ultrasonic transducer: detector), leading to more than twofold improvement of the tangential resolution in both TAT and PAT when the object is far from the scanning center. A contrast agent could be greatly beneficial for early cancer diagnosis using TAT/PAT, because the early stage intrinsic contrast can be low. We have developed a carbon nanotube-based contrast agent for both TAT and PAT. In comparison with deionized water, single-walled carbon nanotubes: SWNTs) exhibited more than twofold signal enhancement for TAT at 3 GHz, and in comparison with blood, they exhibited more than sixfold signal enhancement for PAT at 1064 nm wavelength. Using PAT in conjunction with an intradermal injection of SWNTs, we also showed the feasibility of noninvasive in vivo sentinel lymph node imaging in a rat model. We have also developed and demonstrated molecular photoacoustic imaging using unique soft-type colloidal gold nanobeacons: GNBs) in the near-infrared region. GNBs represent a novel class of stable, colloidal gold nanoparticles, incorporating small metallic gold nanoparticles that can clear from the body when the particles are metabolically disrupted. We have also imaged the sentinel lymph node using different sizes of GNBs, showing that size plays an important role in their in vivo behavior and uptake to the lymph nodes. In addition to providing diagnostic imaging, TAT and PAT can be used in therapy for real-time temperature monitoring with high spatial resolution and high temperature sensitivity, which are both needed for safe and efficient thermotherapy. Using a tissue phantom, these noninvasive methods have been demonstrated to have a high temperature sensitivity of 0.15 0C at 2 s temporal resolution: 20 signal averages)