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Journal ArticleDOI

Smart health monitoring systems: an overview of design and modeling.

15 Jan 2013-Journal of Medical Systems (Springer US)-Vol. 37, Iss: 2, pp 9898
TL;DR: The main aim is to review current state of the art monitoring systems and to perform extensive and an in-depth analysis of the findings in the area of smart health monitoring systems.
Abstract: Health monitoring systems have rapidly evolved during the past two decades and have the potential to change the way health care is currently delivered. Although smart health monitoring systems automate patient monitoring tasks and, thereby improve the patient workflow management, their efficiency in clinical settings is still debatable. This paper presents a review of smart health monitoring systems and an overview of their design and modeling. Furthermore, a critical analysis of the efficiency, clinical acceptability, strategies and recommendations on improving current health monitoring systems will be presented. The main aim is to review current state of the art monitoring systems and to perform extensive and an in-depth analysis of the findings in the area of smart health monitoring systems. In order to achieve this, over fifty different monitoring systems have been selected, categorized, classified and compared. Finally, major advances in the system design level have been discussed, current issues facing health care providers, as well as the potential challenges to health monitoring field will be identified and compared to other similar systems.
Citations
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Journal ArticleDOI
17 Dec 2013-Sensors
TL;DR: A recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services and a number of key challenges have been outlined for data mining methods in health monitoring systems.
Abstract: The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems.

373 citations


Cites background from "Smart health monitoring systems: an..."

  • ...Based on the literature, most monitoring applications which consider home settings or remote monitoring deal predominantly with prediction and anomaly detection whereas the applications in clinical settings are typically focused on diagnosis [10,21]....

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  • ...diseases, posture and motion control, rehabilitation, Parkinson’s disease, stress, neurological disorders, Alzheimer’s disease and dementia [10]....

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  • ...Most notably, are works such as [10,17] which focus on the needs to have wearable sensors and overcoming important bottlenecks for the use of wearable sensors such as the clinical acceptability and interoperability in health records....

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  • ...However, in real time analysis of sensor data while considering mobile health monitoring systems, the time of data analysis and resources for data processing is important as it is presented in [10]....

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  • ...Studies on health monitoring systems include wearable, mobile and remote systems [10]....

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Proceedings Article
01 Jan 2003
TL;DR: Three hardware platforms that addresses the needs of wireless sensor netwoks are presented that produces Operating system concepts for refining concurrency mechanisms and the full realization of the general architecture is represented.
Abstract: The Wireless sensor network play a vital role in collecting a Real – Time data, monitoring environmental conditions based on technology adoption. These sensor network is the combination of sensing, computation, and communication through a single tiny device. Here many tiny nodes assemble and configure themselves. It also controls actuators that extend control from cyberspace into the physical world. Here the sensor nodes communicate with the local peers rather than the high – power control tower or base station. Instead, of relying on a predeployed infrastructure, each individual sensor or actuator become part of the overall infrastructure. Here we have three hardware platforms that addresses the needs of wireless sensor netwoks. The operating system here uses an event based execution to support concurrency. The platform serves as a baseline and does not contain any hardware accelerators. . First platform serves as a baseline and it produces Operating system concepts for refining concurrency mechanisms. The second node validates the architectural designs and improve the communicational rates. The third node represents the full realization of the general architecture. Keywords— node, platform, concurrency.

371 citations

Journal ArticleDOI
26 Jun 2019
TL;DR: Although the technology is not yet mature, it is anticipated that in the near future, accurate, continuous BP measurements may be available from mobile and wearable devices given their vast potential.
Abstract: The measurement of blood pressure (BP) is critical to the treatment and management of many medical conditions. High blood pressure is associated with many chronic disease conditions, and is a major source of mortality and morbidity around the world. For outpatient care as well as general health monitoring, there is great interest in being able to accurately and frequently measure BP outside of a clinical setting, using mobile or wearable devices. One possible solution is photoplethysmography (PPG), which is most commonly used in pulse oximetry in clinical settings for measuring oxygen saturation. PPG technology is becoming more readily available, inexpensive, convenient, and easily integrated into portable devices. Recent advances include the development of smartphones and wearable devices that collect pulse oximeter signals. In this article, we review (i) the state-of-the-art and the literature related to PPG signals collected by pulse oximeters, (ii) various theoretical approaches that have been adopted in PPG BP measurement studies, and (iii) the potential of PPG measurement devices as a wearable application. Past studies on changes in PPG signals and BP are highlighted, and the correlation between PPG signals and BP are discussed. We also review the combined use of features extracted from PPG and other physiological signals in estimating BP. Although the technology is not yet mature, it is anticipated that in the near future, accurate, continuous BP measurements may be available from mobile and wearable devices given their vast potential.

327 citations


Cites methods from "Smart health monitoring systems: an..."

  • ...Adding the estimation of SBP and DBP is logical and expected.(38) A list of wearable BP estimation devices, as well as descriptions of the devices and their functions, is presented in Table 1....

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Journal ArticleDOI
TL;DR: This study provides a review of the recent advances in remote healthcare and monitoring in both with-contact and contactless methods and discusses some issues available in most systems.
Abstract: Healthcare is a field that is rapidly developing in technology and services. A recent development in this area is remote monitoring of patients which has many advantages in a fast aging world population with increasing health complications. With relatively simple applications to monitor patients inside hospital rooms, the technology has developed to the extent that the patient can be allowed normal daily activities at home while still being monitored with the use of modern communication and sensor technologies. Sensors for monitoring essential vital signs such as electrocardiogram reading, heart rate, respiration rate, blood pressure, temperature, blood glucose levels and neural system activity are available today. Range of remote healthcare varies from monitoring chronically ill patients, elders, premature children to victims of accidents. These new technologies can monitor patients based on the illness or based on the situation. The technology varies from sensors attached to body to ambient sensors attached to the environment and new breakthroughs show contactless monitoring which requires only the patient to be present within a few meters from the sensor. Fall detection systems and applications to monitor chronical ill patients have already become familiar to many. This study provides a review of the recent advances in remote healthcare and monitoring in both with-contact and contactless methods. With the review, the authors discuss some issues available in most systems. The paper also includes some directions for future research.

282 citations


Cites background from "Smart health monitoring systems: an..."

  • ...Baig and Gholamhosseini (2013) compare several smart health monitoring systems and discuss challenges and issues in the current systems....

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Journal ArticleDOI
TL;DR: The managerial implication of this article is that organizations can use the findings of the critical analysis to reinforce their strategic arrangement of smart systems and big data in the healthcare context, and hence better leverage them for sustainable organizational invention.
Abstract: Organized evaluation of various big data and smart system technology in healthcare context.Proposed a conceptual model on Big data enabled Smart Healthcare System Framework (BSHSF).We extract some depth information (some relevant examples) about advanced healthcare system.In depth study about state-of-the-art big data and smart healthcare system in parallel. In the era of big data, recent developments in the area of information and communication technologies (ICT) are facilitating organizations to innovate and grow. These technological developments and wide adaptation of ubiquitous computing enable numerous opportunities for government and companies to reconsider healthcare prospects. Therefore, big data and smart healthcare systems are independently attracting extensive attention from both academia and industry. The combination of both big data and smart systems can expedite the prospects of the healthcare industry. However, a thorough study of big data and smart systems together in the healthcare context is still absent from the existing literature. The key contributions of this article include an organized evaluation of various big data and smart system technologies and a critical analysis of the state-of-the-art advanced healthcare systems. We describe the three-dimensional structure of a paradigm shift. We also extract three broad technical branches (3T) contributing to the promotion of healthcare systems. More specifically, we propose a big data enabled smart healthcare system framework (BSHSF) that offers theoretical representations of an intra and inter organizational business model in the healthcare context. We also mention some examples reported in the literature, and then we contribute to pinpointing the potential opportunities and challenges of applying BSHSF to healthcare business environments. We also make five recommendations for effectively applying `BSHSF to the healthcare industry. To the best of our knowledge, this is the first in-depth study about state-of-the-art big data and smart healthcare systems in parallel. The managerial implication of this article is that organizations can use the findings of our critical analysis to reinforce their strategic arrangement of smart systems and big data in the healthcare context, and hence better leverage them for sustainable organizational invention.

233 citations

References
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Journal ArticleDOI
TL;DR: The goal for this study was to develop a measure of balance appropriate for elderly individuals and there was a high degree of internal consistency, a Cronbach's alpha of .96, which indicates the movements reflect a single underlying dimension.
Abstract: The goal for this study was to develop a measure of balance appropriate for elderly individuals. In total, 38 patients, ranging in age from 60 to 93 years, and 32 professionals, including nurses, physicians, and physical and occupational therapists were surveyed in three distinct phases to develop the content. Reliability of the measure was assessed by having physical therapists evaulate the videotaped performances of geriatric subjects at two different points in time. The intraclass correlation coefficients measuring the inter and intra rater reliability for the test as a whole were .98 and .99 respectively. The correlation coefficients for the individual items ranged from .71 to .99. In addition, there was a high degree of internal consistency, a Cronbach's alpha of .96, which indicates the movements reflect a single underlying dimension. The scale consists of 14 movements common in everyday life. It is easy to administer and score and has measurement properties that are better than expected for a new i...

2,418 citations


"Smart health monitoring systems: an..." refers methods in this paper

  • ...[59] and a Berg balance scale (BBS) [60], employs the SHIMMER sensors and Matlab for processing raw accelerometer and gyroscope data....

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  • ...System results indicated that the manual TUG test had an accuracy of 60.6 %, BBS an accuracy of 61.4 % and the mean test, an accuracy of 76.8 % when estimating falls risk in 349 older adults....

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  • ...A quantitative fall risk assessment [58] uses a timed up and go (TUG) test was developed by Mathias et al. [59] and a Berg balance scale (BBS) [60], employs the SHIMMER sensors and Matlab for processing raw accelerometer and gyroscope data....

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Journal ArticleDOI
01 Jan 2010
TL;DR: A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions and evaluate the maturity level of the top current achievements in wearable health-monitoring systems.
Abstract: The design and development of wearable biosensor systems for health monitoring has garnered lots of attention in the scientific community and the industry during the last years. Mainly motivated by increasing healthcare costs and propelled by recent technological advances in miniature biosensing devices, smart textiles, microelectronics, and wireless communications, the continuous advance of wearable sensor-based systems will potentially transform the future of healthcare by enabling proactive personal health management and ubiquitous monitoring of a patient's health condition. These systems can comprise various types of small physiological sensors, transmission modules and processing capabilities, and can thus facilitate low-cost wearable unobtrusive solutions for continuous all-day and any-place health, mental and activity status monitoring. This paper attempts to comprehensively review the current research and development on wearable biosensor systems for health monitoring. A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions. An emphasis is given to multiparameter physiological sensing system designs, providing reliable vital signs measurements and incorporating real-time decision support for early detection of symptoms or context awareness. In order to evaluate the maturity level of the top current achievements in wearable health-monitoring systems, a set of significant features, that best describe the functionality and the characteristics of the systems, has been selected to derive a thorough study. The aim of this survey is not to criticize, but to serve as a reference for researchers and developers in this scientific area and to provide direction for future research improvements.

2,051 citations


"Smart health monitoring systems: an..." refers background in this paper

  • ...Like any other technological advancement, smart health monitoring systems have both benefits and limitations and currently, there is on-going research to improve these systems [84, 92]....

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Journal Article
TL;DR: The get-up and go test proved to be a satisfactory clinical measure of balance in elderly people and had good correlation with laboratory tests.

1,504 citations

Journal ArticleDOI
TL;DR: Fall related injuries among older adults, especially among older women, are associated with substantial economic costs, and implementing effective intervention strategies could appreciably decrease the incidence and healthcare costs of these injuries.
Abstract: Objective: To estimate the incidence and direct medical costs for fatal and non-fatal fall injuries among US adults aged ⩾65 years in 2000, for three treatment settings stratified by age, sex, body region, and type of injury. Methods: Incidence data came from the 2000 National Vital Statistics System, 2001 National Electronic Injury Surveillance System-All Injury Program, 2000 Health Care Utilization Program National Inpatient Sample, and 1999 Medical Expenditure Panel Survey. Costs for fatal falls came from Incidence and economic burden of injuries in the United States; costs for non-fatal falls were based on claims from the 1998 and 1999 Medicare fee-for-service 5% Standard Analytical Files. A case crossover approach was used to compare the monthly costs before and after the fall. Results: In 2000, there were almost 10 300 fatal and 2.6 million medically treated non-fatal fall related injuries. Direct medical costs totaled $0.2 billion dollars for fatal and $19 billion dollars for non-fatal injuries. Of the non-fatal injury costs, 63% ($12 billion) were for hospitalizations, 21% ($4 billion) were for emergency department visits, and 16% ($3 billion) were for treatment in outpatient settings. Medical expenditures for women, who comprised 58% of the older adult population, were 2–3 times higher than for men for all medical treatment settings. Fractures accounted for just 35% of non-fatal injuries but 61% of costs. Conclusions: Fall related injuries among older adults, especially among older women, are associated with substantial economic costs. Implementing effective intervention strategies could appreciably decrease the incidence and healthcare costs of these injuries.

1,463 citations


"Smart health monitoring systems: an..." refers background in this paper

  • ...[57] conducted a study to estimate the cost of fatal and non-fatal falls amongst older adults, and reported direct medical costs totalling $0....

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Journal ArticleDOI
TL;DR: This epidemiological review of falls concentrates on four main components, different ways of defining and classifying falls and fallers, and the causes and impact of falls in the older population.
Abstract: Falls in older people are a major public health concern in terms of morbidity, mortality and the cost to health and social services [1]. This epidemiological review of falls concentrates on four main components. Firstly, different ways of defining and classifying falls and fallers are outlined. The second section deals with the occurrence, including the prevalence, time and place of falls. We then examine the causes (risk factors) for falling, and finally we discuss the impact (consequences) of falls in the older population.

933 citations


"Smart health monitoring systems: an..." refers background in this paper

  • ...Incidence rates in hospitals are higher and, in residential care settings, approximately 30–50 % of people fall each year, with 40 % falling recurrently [56]....

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