International Journal of Telemedicine and Clinical Practices (9 papers in press)
EPR Data Hiding in MRI Head Volumes for Telemedicine Using Rectangular Box Embedding Method
by Kalaiselvi Thiruvenkadam, Vijayalakshmi S, Somasundaram K
Abstract: Mapping of electronic patient report (EPR) text file to magnetic
resonance imaging (MRI) volumes increases burden to diagnosis over
telemedicine. In this paper, we propose a high capacity, robust technique to
select slices of interest (SOI) from a MRI volume that to embed EPR and
transfer on a network. Embedding EPR along with selected slices is used to
removal of mapping procedure at the receiver end. Initially brain extraction
algorithm (BEA) is used to focus the region and ease of pathology detection in
the slices. Then the embedding scheme uses the technique of rectangular box
mapping (RBM) where it takes care of sensitive part of medical image. EPR
data is encrypted and embedded for security purpose. Experimental results on
security and robustness have been tested against various images. The proposed
method can store longer EPR string along with better authenticity and
confidentiality properties while satisfying all the requirements of medical data
transfer and has achieved 51% reduction in bit rate than the traditional
Keywords: magnetic resonance images; head scans; biomedical imaging; data
communication; EPR hiding; telemedicine; brain extraction algorithm;
rectangular box mapping; RBM; slices of interest; SOI; region of interest; ROI.
Cell nuclei detection in multispectral histology images using K-means and Expectation- Maximization segmentations
by Mohamed BOUZID, Ali KHAFALLAH, Sana LAFI, Med Salim BOUHLEL
Abstract: Histology images contain a lot of relevant information which are useful in the diagnostic (cells, cell compartments such as nuclei). In this topic, the main goal of computer-based image analysis is to identify structures or nuclei in histology images with high accuracy and robustness. Current methods and systems based on color images give results with a lot of errors. We suggest using multispectral imaging system with a Programmable Light Source (PLS). With the new acquisition system, a 3-band color image (MS3), a 5-band multispectral image (MS5), a 10-band multispectral image (MS10) and a 25-band multispectral image (MS25) from 450 nm to 700 nm are acquired. After the acquisition, two unsupervised segmentation methods are applied: the expectation- maximization (EM) and the K-means (KM). Firstly, each band is segmented separately; secondly a fusion of bands is used. A comparison has been drawn between the two segmentation methods. The results show a small superiority of EM segmentation against KM segmentation. It is also noted that the fuse of selected bands from MS5 ensures the best F-measure of cell nuclei detection.
Keywords: Histology; nuclei detection; multispectral images; segmentation; K-means; Expectation maximization.
Some considerations of common spatial pattern for better classification in braincomputer interfaces
by Yeon-Mo Yang
Abstract: EEG-based motor imagery signal classification is very important in braincomputer interface (BCI) technology. In this work, we develop a common spatial pattern (CSP) technique for feature extraction in a BCI system. To confirm classification improvement, classification accuracy was analyzed by using four statistics, namely mean, variance, skewness, and kurtosis within the CSP paradigm. The data from the data set Ⅲ of BCI Competition Ⅱ were used and simulated using Matlab. The results show that the best classification accuracy is obtained when the CSP algorithm uses the variance statistic for feature extraction.
Keywords: Brain–computer interface (BCI); Motor imagery; Common spatial pattern (CSP); Neural signal classification; Statistical signal processing.
The feasibility of cross-sector videoconferences in discharge planning among stroke patients: A mixed-methods study scrutinizing patient and staff perspectives
by Simone Hofman Rosenkranz, Anne Argir Falster, Tina Strid Carstensen, Lone Lundbak Mathiesen, Helle Klingenberg Iversen, Charlotte Kira Kimby
Abstract: We tested the quality and effectiveness of cross-sector videoconferences in planning the discharge of stroke patients. Throughout the trial, time registration and structured patient interviews were conducted. During intervention, a self-administered questionnaire and semi-structured focus group interviews were conducted among staff. Patient and staff questionnaires revealed high satisfaction with discharge videoconferences, and substantial savings on transport was registered among municipalities. Through focus groups, detailed workflow descriptions, ongoing staff education, detailed care-plans, the availability of a super user, and a suitable conference room were important when conducting a videoconference. Additionally, interviews revealed concern among staff regarding whether communication and observation through videoconferencing is sufficient to ensure that rehabilitation meets the patients needs. This study offers opportunities to overcome geographical and economic challenges in discharge planning without compromising quality of care. Furthermore, the results create a foundation for further exploration of how discharge videoconferences affect workflow, communication, and quality of care.
Keywords: patient discharge; videoconferencing; video discharge; stroke rehabilitation; cross-sector cooperation; continued care.
Special Issue on: WIS 2016 Well-being Ecosystems
Healthcare as a Business Environment Analyzing the Finnish Health Technology Industry
by Reetta Raitoharju, Tuomas Ranti, Mikko Gronlund
Abstract: Health technology is the fastest growing field of high technology in Finland. However, developing new products, keeping up with the regulatory environment and finding new markets can be challenging in the highly regulated and rapidly changing healthcare environment. This paper presents the results of a financial analysis and a survey conducted among Finnish health technology companies. The aim is to get an overview about the current stage of the Finnish health technology industry and the challenges the Finnish health technology companies are facing.
Keywords: Health technology; financial analysis; economic performance; growth; regulatory
Towards improving shift leaders information management in intensive care units developing and testing a model for a managerial information system
by Laura-Maria Peltonen, Helja Lundgren-Laine, Sanna Salantera
Abstract: Intensive care unit (ICU) shift leaders expend much effort to seek important information as it is scattered and must be collected manually. The aims of this study were 1) to explore ICU shift leaders information management and 2) to test a model of a management information system, which was developed based on the shift leaders needs. Data were collected with a survey (n = 20) and interviews (n = 15) to explore the shift leaders information needs and the sources of important information. Based on these findings, a model for a management information system was developed and tested with six informants. Data were collected in Finland and in New Zealand. The findings showed that the shift leaders wanted an information system that can be used as a tool which provides a real-time overview of the units situation and available resources, and which can be used for planning, resource allocation and communicating information.
Keywords: information management; information system development; intensive care; management information system; nursing; shift leader.
Senior Citizens Perceived Health Self-Efficacy and Information Barriers
by Ágústa Pálsdóttir, Sigriður Björk Einarsdóttir
Abstract: The perceived health self-efficacy beliefs and perceived information barriers, among people aged 60 years and older, were examined. The data was gathered by a questionnaire survey in 2012. Total number of participants was 176. The self-efficacy beliefs were measured by the Perceived Health Competence Scale (PHCS). A scale of 13 statements was used to measure information. Difference across the age groups, as well as the effects of sex and education were examined. The results indicate that seniors with primary education need support to enhance their self-efficacy beliefs. Seniors with secondary or university education have a positive view on their abilities to control their own health, but experience information barriers that can impact their options to enhance their knowledge of healthy behaviour.
Keywords: health literacy; health self-efficacy; information barriers; media and health information literacy; senior citizens.
The digitalization of the medical value network how information asymmetries can be managed with digital innovations
by Teijo Peltoniemi
Abstract: Digitalization equalizes information asymmetries, which increases economic efficiency and transforms many lines of business. It can be argued that digitalization can do the same in the medical and healthcare market. This article conceptualizes the medical and healthcare market and its digitalization utilizing the concepts of information asymmetry and value network. Inefficiencies within the network relating to incomplete information and information asymmetry are identified. Some digital solutions to these issues are suggested, including the electronic prescription and the automatic medicine dispenser.
Keywords: Digitalization; medicine; ePrescription; electronic health record; automatic medicine dispenser; medicine demand management; information asymmetry; value network.
Special Issue on: Internet of Things and Big Data for Smart Health Services
A Framework for Predicting Malaria using Na
by Aminu Aliyu, Rajesh Prasad, Mathias Fonkam
Abstract: Malaria, a life-threatening parasite contained in the spittle of mosquitoes, is transmitted via a bite. After biting human, it takes about 45 minutes to spread into the blood stream and become infectious; then, the parasite starts attacking the bodys red blood and even liver cells, altering the cell-build structure, properties, and even the bodys biochemistry. This study designs a framework for predicting malaria using a probabilistic classifier: Na
Keywords: Malaria; Data Mining; Classification; Na.