Recording of time-varying back-pain data: A wireless solution

Chronic back pain is a debilitating experience for a considerable proportion of the adult population, with a significant impact on countries’ economies and health systems. While there has been increasing anecdotal evidence to support the fact that for certain categories of patients (such as wheelchair users), the back pain experienced is dynamically varying with time, there is a relative scarcity of data to support and document this observation, with consequential impact upon such patients’ treatment and care. Part of the reason behind this state of affairs is the relative difficulty in gathering pain measurements at precisely defined moments in time. In this paper,we describe a wireless-enabled solution that collects both questionnaire and diagrammatic, visual-based data, via a pain drawing, which overcomes such limitations, enabling seamless data collection and its upload to a hospital server using existing wireless fidelity technology. Results show that it is generally perceived to be an easy-to-use and convenient solution to the challenges of anywhere/anytime data collection

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months

KEHAMILAN DENGAN PENYAKIT JANTUNG: PENGHALANG ATAU TANTANGAN?

The changing of lifestyle on young women lead to the increasing of their heart disease prevalence. Once upon the time, those women will be pregnant and bring-changes to their cardiovascular system. Therefore, the pregnancy has probability to worse woman’s heart condition. A systematic review describe about 123 up to 943 per 100,000 childbirth happened to, women with heart disease. Meanwhile, Stangl et.al report that 12.9 % pregnant women with heart disease had suffered with heart abnormalities during their pregnancy. However, that complication can be decreased with pre conception counselling, ante natal care, intrapartum care, and post partum care. ABSTRAK Perubahan gaya hidup menyebabkan prevalensi penyakit jantung pada wanita usia muda meningkat. Pada masanya, wanita tersebut akan memasuki fase kehamilan yang membuatnya mengalami perubahan pada sistem kardiovaskular. Dengan demikian, kehamilan memiliki peluang memperburuk kondisi jantung wanita tersebut. Hasil systematic review memaparkan bahwa 123 sampai dengan 943 per 100.000 persalinan terjadi pada ibu dengan penyakit jantung. Sementara Stangl dan kawan-kawan melaporkan bahwa sebesar 12, 9 % ibu hamil dengan penyakit jantung mengalami kejadian penyakit jantung selama kehamilannya. Walaupun demikian, komplikasi tersebut dapat diperkecil dengan melakukan pemeriksaan pre konsepsi, selama kehamilan, saat persalinan, dan setelahnya

ИТ-диагностика заболеваний легких с помощью голосового анализа в сети интернет вещей

Проект использует Python для предварительной обработки данных и обучения модели, PyCharm и Jupyter Notebook для локального развертывания и отладки кода. Часть облачных вычислений использует платформу Google Cloud Storage Platform и средство Flask в качестве механизма вызова интерфейса веб-службы. Чтобы удобнее собирать данные и улучшить пользовательский опыт, в рамках проекта было разработано приложение для прогнозирования заболеваний легких, платформой разработки является Android Studio, а языком разработки - Kotlin

Crossing the digital divide : family caregivers' acceptance of technology

The purpose of this pilot project was to collect data on how electronic technology might be used to assist family members who are caring for a relative with dementia at home. In Phase 1, we conducted five focus groups with 26 caregivers of relatives with dementia to document the specific challenges faced by caregivers and assess their access to, and familiarity with, electronic technology. In Phase 2, a technology-based solution B the Xanboo Smart House Management System B was identified. The System allows monitoring of a residence through placement and control of video cameras and other enabled devices, including sensors that detect motion, the presence of water, or noise. Sensors may be set to provide a caregiver or other interested party with immediate notification by e-mail, pager, or text messaging cell phone. In Phase 3, a household was outfitted with The System and two focus groups comprised of 8 caregivers to relatives with dementia were conducted to evaluate its utility. The report concludes with an annotated bibliography on technology and aging, with special focus on caring for a relative with dementia. Key Findings: Caregivers and the relatives for whom they provide care are in an evolving struggle to maintain continuity of roles, relationships, and lifestyles. Challenges include the safety of the individual with dementia and keeping geographically distant family members aware of their relative s condition. Caregivers used a range of technologies in their day-to-day lives, including low- tech solutions to challenges in caregiving. Caregivers felt strongly that technological solutions were neither appropriate nor useful across all situations, and were cognizant of the inherent trade-off between safety on the one hand and dignity, respect, privacy, and desires for independence and autonomy on the other hand. Caregivers do not aspire to become technology whizzes ; rather, they are interested in easily obtained, affordable, easy to use, solutions to some of the challenges they face. An affordable, easy to use, off the shelf, monitoring system (The System) was identified. Caregivers attitudes regarding The System were generally quite positive. When prompted to identify barriers to using The System, caregivers identified the need for a computer and Internet access, and cost. Conclusions: The results from this pilot project suggest that there are affordable technologies that can assist family members in their efforts to care for relatives with dementia at home, and that these caregivers were amenable to the use of these technologies. Future efforts should evaluate the installation, use, and impact of The System in the homes of family caregivers to relatives with dementia