Abstract: Falling has been one of the major concerns and threats
to the independence of the elderly in their daily lives. With the
worldwide significant growth of the aging population, it is essential
to have a promising solution of fall detection which is able to operate
at high accuracy in real-time and supports large scale implementation
using multiple cameras. Field Programmable Gate Array (FPGA) is a
highly promising tool to be used as a hardware accelerator in many
emerging embedded vision based system. Thus, it is the main
objective of this paper to present an FPGA-based solution of visual
based fall detection to meet stringent real-time requirements with
high accuracy. The hardware architecture of visual based fall
detection which utilizes the pixel locality to reduce memory accesses
is proposed. By exploiting the parallel and pipeline architecture of
FPGA, our hardware implementation of visual based fall detection
using FGPA is able to achieve a performance of 60fps for a series of
video analytical functions at VGA resolutions (640x480). The results
of this work show that FPGA has great potentials and impacts in
enabling large scale vision system in the future healthcare industry
due to its flexibility and scalability.
Abstract: Hemodialysis patients might suffer from unhealthy
care behaviors or long-term dialysis treatments. Ultimately they need
to be hospitalized. If the hospitalization rate of a hemodialysis center
is high, its quality of service would be low. Therefore, how to decrease
hospitalization rate is a crucial problem for health care. In this study
we combined temporal abstraction with data mining techniques for
analyzing the dialysis patients' biochemical data to develop a decision
support system. The mined temporal patterns are helpful for clinicians
to predict hospitalization of hemodialysis patients and to suggest them
some treatments immediately to avoid hospitalization.
Abstract: TELMES project aims to develop a securized
multimedia system devoted to medical consultation teleservices. It
will be finalized with a pilot system for a regional telecenters
network that connects local telecenters, having as support
multimedia platforms. This network will enable the implementation
of complex medical teleservices (teleconsulations, telemonitoring,
homecare, urgency medicine, etc.) for a broader range of patients
and medical professionals, mainly for family doctors and those
people living in rural or isolated regions. Thus, a multimedia,
scalable network, based on modern IT&C paradigms, will result. It
will gather two inter-connected regional telecenters, in Iaşi and
Piteşti, Romania, each of them also permitting local connections of
hospitals, diagnostic and treatment centers, as well as local networks
of family doctors, patients, even educational entities. As
communications infrastructure, we aim to develop a combined fixmobile-
internet (broadband) links. Other possible communication
environments will be GSM/GPRS/3G and radio waves. The
electrocardiogram (ECG) acquisition, internet transmission and
local analysis, using embedded technologies, was already
successfully done for patients- telemonitoring.
Abstract: The aged are faced with increasing risk for falls. The
aged have the easily fragile bones than others. When falls have
occurred, it is important to detect this emergency state because such
events often lead to more serious illness or even death. A
implementation of PDA system, for detection of emergency situation,
was developed using 3-axis accelerometer in this paper as follows.
The signals were acquired from the 3-axis accelerometer, and then
transmitted to the PDA through Bluetooth module. This system can
classify the human activity, and also detect the emergency state like
falls. When the fall occurs, the system generates the alarm on the
PDA. If a subject does not respond to the alarm, the system determines
whether the current situation is an emergency state or not, and then
sends some information to the emergency center in the case of urgent
situation. Three different studies were conducted on 12 experimental
subjects, with results indicating a good accuracy. The first study was
performed to detect the posture change of human daily activity. The
second study was performed to detect the correct direction of fall. The
third study was conducted to check the classification of the daily
physical activity. Each test was lasted at least 1 min. in third study.
The output of acceleration signal was compared and evaluated by
changing a various posture after attaching a 3-axis accelerometer
module on the chest. The newly developed system has some important
features such as portability, convenience and low cost. One of the
main advantages of this system is that it is available at home
healthcare environment. Another important feature lies in low cost to
manufacture device. The implemented system can detect the fall
accurately, so will be widely used in emergency situation.
Abstract: The hospital and the health-care center of a
community, as a place for people-s life-care and health-care settings,
must provide more and better services for patients or residents. After
Establishing Electronic Medical Record (EMR) system -which is a
necessity- in the hospital, providing pervasive services is a further
step. Our objective in this paper is to use pervasive computing in a
case study of healthcare, based on EMR database that coordinates
application services over network to form a service environment for
medical and health-care. Our method also categorizes the hospital
spaces into 3 spaces: Public spaces, Private spaces and Isolated
spaces. Although, there are many projects about using pervasive
computing in healthcare, but all of them concentrate on the disease
recognition, designing smart cloths, or provide services only for
patient. The proposed method is implemented in a hospital. The
obtained results show that it is suitable for our purpose.
Abstract: This paper presents an exploration into the structure of the corporate governance network and interlocking directorates in the Czech Republic. First a literature overview and a basic terminology of the network theory is presented. Further in the text, statistics and other calculations relevant to corporate governance networks are presented. For this purpose an empirical data set consisting of 2 906 joint stock companies in the Czech Republic was examined. Industries with the highest average number of interlocks per company were healthcare, and energy and utilities. There is no observable link between the financial performance of the company and the number of its interlocks. Also interlocks with financial companies are very rare.
Abstract: The Siemens Healthcare Sector is one of the world's
largest suppliers to the healthcare industry and a trendsetter in
medical imaging and therapy, laboratory diagnostics, medical
information technology, and hearing aids.
Siemens offers its customers products and solutions for the entire
range of patient care from a single source – from prevention and
early detection to diagnosis, and on to treatment and aftercare. By
optimizing clinical workflows for the most common diseases,
Siemens also makes healthcare faster, better, and more cost effective.
The optimization of clinical workflows requires a
multidisciplinary focus and a collaborative approach of e.g. medical
advisors, researchers and scientists as well as healthcare economists.
This new form of collaboration brings together experts with deep
technical experience, physicians with specialized medical knowledge
as well as people with comprehensive knowledge about health
economics.
As Charles Darwin is often quoted as saying, “It is neither the
strongest of the species that survive, nor the most intelligent, but the
one most responsive to change," We believe that those who can
successfully manage this change will emerge as winners, with
valuable competitive advantage.
Current medical information and knowledge are some of the core
assets in the healthcare industry. The main issue is to connect
knowledge holders and knowledge recipients from various
disciplines efficiently in order to spread and distribute knowledge.
Abstract: Radio Frequency Identification (RFID) initially introduced
during WW-II, has revolutionized the world with its numerous
benefits and plethora of implementations in diverse areas ranging
from manufacturing to agriculture to healthcare to hotel management.
This work reviews the current research in this area with emphasis
on applications for supply chain management and to develop a
taxonomic framework to classify literature which will enable swift
and easy content analysis and also help identify areas for future
research.
Abstract: Recent advancements in sensor technologies and
Wireless Body Area Networks (WBANs) have led to the
development of cost-effective healthcare devices which can be used
to monitor and analyse a person-s physiological parameters from
remote locations. These advancements provides a unique opportunity
to overcome current healthcare challenges of low quality service
provisioning, lack of easy accessibility to service varieties, high costs
of services and increasing population of the elderly experienced
globally. This paper reports on a prototype implementation of an
architecture that seamlessly integrates Wireless Body Area Network
(WBAN) with Web services (WS) to proactively collect
physiological data of remote patients to recommend diagnostic
services. Technologies based upon WBAN and WS can provide
ubiquitous accessibility to a variety of services by allowing
distributed healthcare resources to be massively reused to provide
cost-effective services without individuals physically moving to the
locations of those resources. In addition, these technologies can
reduce costs of healthcare services by allowing individuals to access
services to support their healthcare. The prototype uses WBAN body
sensors implemented on arduino fio platforms to be worn by the
patient and an android smart phone as a personal server. The
physiological data are collected and uploaded through GPRS/internet
to the Medical Health Server (MHS) to be analysed. The prototype
monitors the activities, location and physiological parameters such as
SpO2 and Heart Rate of the elderly and patients in rehabilitation.
Medical practitioners would have real time access to the uploaded
information through a web application.
Abstract: Within the healthcare system, training and continued professional development although essential, can be effected by cost and logistical restraints due to the nature of healthcare provision e.g employee shift patterns, access to expertise, cost factors in releasing staff to attend training etc. The use of multimedia technology for the development of e-learning applications is also a major cost consideration for healthcare management staff, and this type of media whether optical or on line requires careful planning in order to remain inclusive of all staff with potentially varied access to multimedia computing. This paper discusses a project in which the use of DVD authoring technology has been successfully implemented to meet the needs of distance learning and user considerations, and is based on film production techniques and reduced product turnaround deadlines.
Abstract: Main goal of preventive healthcare problems are at
decreasing the likelihood and severity of potentially life-threatening
illnesses by protection and early detection. The levels of
establishment and staffing costs along with summation of the travel
and waiting time that clients spent are considered as objectives
functions of the proposed nonlinear integer programming model. In
this paper, we have proposed a bi-objective mathematical model for
designing a network of preventive healthcare facilities so as to
minimize aforementioned objectives, simultaneously. Moreover, each
facility acts as M/M/1 queuing system. The number of facilities to be
established, the location of each facility, and the level of technology
for each facility to be chosen are provided as the main determinants
of a healthcare facility network. Finally, to demonstrate performance
of the proposed model, four multi-objective decision making
techniques are presented to solve the model.
Abstract: This paper explores the knowledge and attitude of
women and men in decision making on pap smear screening. This
qualitative study recruited 52 respondents with 44 women and 8 men,
using the purposive sampling with snowballing technique through indepth
interviews. This study demonstrates several key findings:
Female respondents have better knowledge compared to male. Most
of the women perceived that pap smear screening is beneficial and
important, but to proceed with the test is still doubtful. Male
respondents were supportive in terms of sending their spouses to the
health facilities or give more freedom to their wives to choose and
making decision on their own health due to prominent reason that
women know best on their own health. It is expected that the results
from this study will provide useful guideline for healthcare providers
to prepare any action/intervention to provide an extensive education
to improve people-s knowledge and attitude towards pap smear.
Abstract: The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.
Abstract: In this paper we used data mining techniques to
identify outlier patients who are using large amount of drugs over a
long period of time. Any healthcare or health insurance system
should deal with the quantities of drugs utilized by chronic diseases
patients. In Kingdom of Bahrain, about 20% of health budget is spent
on medications. For the managers of healthcare systems, there is no
enough information about the ways of drug utilization by chronic
diseases patients, is there any misuse or is there outliers patients. In
this work, which has been done in cooperation with information
department in the Bahrain Defence Force hospital; we select the data
for Cardiac patients in the period starting from 1/1/2008 to
December 31/12/2008 to be the data for the model in this paper. We
used three techniques for finding the drug utilization for cardiac
patients. First we applied a clustering technique, followed by
measuring of clustering validity, and finally we applied a decision
tree as classification algorithm. The clustering results is divided into
three clusters according to the drug utilization, for 1603 patients, who
received 15,806 prescriptions during this period can be partitioned
into three groups, where 23 patients (2.59%) who received 1316
prescriptions (8.32%) are classified to be outliers. The classification
algorithm shows that the use of average drug utilization and the age,
and the gender of the patient can be considered to be the main
predictive factors in the induced model.
Abstract: The incidence of oral cancer in Taiwan increased year
by year. It replaced the nasopharyngeal as the top incurrence among
head and neck cancers since 1994. Early examination and earlier
identification for earlier treatment is the most effective medical
treatment for these cancers. Although the government fully subsidized
the expenses with tremendous promotion program for oral cancer
screening, the citizen-s participation remained low. Purpose of this
study is to understand the factors affecting the citizens- behavior
intensions of taking an oral cancer screening. Based on the Theory of
Planned Behavior, this study adopted four distinctive variables in
explaining the captioned behavior intentions.700 questionnaires were
dispatched with 500 valid responses or 71.4% returned by the citizens
with an age 30 or above from the eastern counties of Taiwan. Test
results has shown that attitude toward, subjective norms of, and
perceived behavioral control over the oral cancer screening varied
from some demographic factors to another. The study proofed that
attitude toward, subjective norms of, and perceived behavioral control
over the oral cancer screening had positive impacts on the
corresponding behavior intention. The test concluded that the theory
of planned behavior was appropriate as a theoretical framework in
explaining the influencing factors of intentions of taking oral cancer
screening. This study suggested the healthcare professional should
provide high accessibility of screening services other than just
delivering knowledge on oral cancer to promote the citizens-
intentions of taking the captioned screening. This research also
provided a practical implication to the healthcare professionals when
formulating and implementing promotion instruments for lifting the
screening rate of oral cancer.
Abstract: In this work, the surgical theater of a local hospital in
KSA was analyzed using simulation. The focus was on attempting to
answer questions related to how many Operating Rooms (ORs) to
open and to analyze the performance of the surgical theater in
general and mainly the Post Anesthesia Care Unit (PACU) to assist
making decisions regarding PACU staffing. The surgical theater
consists of ten operating rooms and the PACU unit which has a
maximum capacity of fifteen beds. Different sequencing rules to
sequence the surgical cases were tested and the Longest Case First
(LCF) were superior to others. The results of the different
alternatives developed and tested can be used by the manager as a
tool to plan and manage the OR and PACU
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.
Abstract: The study was conducted to investigate the profile of
hepatitis in Kingdom of Saudi Arabia, and to determine which age
group hepatitis viruses most commonly infect. The epidemiology of
viral hepatitis in Saudi Arabia has undergone major changes,
concurrent with major socioeconomic developments over the last two
to three decades. This disease represents a major public health
problem in Saudi Arabia resulting in the need for considerable
healthcare resources. A retrospective cross sectional analysis of the
reported cases of viral hepatitis was conducted based on the reports
of The Ministry of Health in Saudi Arabia about Hepatitis A, B and C
infections in all regions from the period of January 2006 to December
2010. The study demonstrated that incidence of viral Hepatitis is
decreasing, except for Hepatitis B that showed minimal increase. Of
hepatitis A, B, and C, Hepatitis B virus (HBV) was the most
predominant type, accounting for (53%) of the cases, followed by
Hepatitis C virus (HCV) (30%) and HAV (17%). HAV infection
predominates in children (5–14 years) with 60% of viral hepatitis
cases, HBV in young adults (15–44 years) with 69% of viral hepatitis
cases, and HCV in older adults (>45 years) with 59% of viral
hepatitis cases. Despite significant changes in the prevalence of viral
hepatitis A, B and C, it remains a major public health problem in
Saudi Arabia; however, it showed a significant decline in the last two
decades that could be attributed to the vaccination programs and the
improved health facilities. Further researches are needed to identify
the risk factors making a specific age group or a specific region in
Saudi Arabia targeted for a specific type of hepatitis viruses.
Abstract: In this study, we explore the use of information for inventory decision in the healthcare organization (HO). We consider the scenario when the HO can make use of the information collected from some correlated products to enhance its inventory planning. Motivated by our real world observations that HOs adopt RFID and bar-coding system for information collection purpose, we examine the effectiveness of these systems for inventory planning with Bayesian information updating. We derive the optimal ordering decision and study the issue of Pareto improvement in the supply chain. Our analysis demonstrates that RFID system will outperform the bar-coding system when the RFID system installation cost and the tag cost reduce to a level that is comparable with that of the barcoding system. We also show how an appropriately set wholesale pricing contract can achieve Pareto improvement in the HO supply chain.