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Asynchronous brain machine interface-based control of a wheelchair

Hema CR, Paulraj MP, Yaacob S, Adom AH, Nagarajan R

Adv Exp Med Biol, 2011;696:565-72.
PMID: 21431597 DOI: 10.1007/978-1-4419-7046-6_57

A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is based on only two electrodes and operated by motor imagery of four states. A recurrent neural classifier is proposed for the classification of the four mental states. The real-time experiment results of four subjects are reported and problems emerging from asynchronous control are discussed.

Matched MeSH terms: Computer Systems
Fulltext Real-time ultrasound-guided paramedian spinal anaesthesia: evaluation of the efficacy and the success rate of single needle pass

Chong SE, Mohd Nikman A, Saedah A, Wan Mohd Nazaruddin WH, Kueh YC, Lim JA, et al.

Br J Anaesth, 2017 05 01;118(5):799-801.
PMID: 28510752 DOI: 10.1093/bja/aex108
Matched MeSH terms: Computer Systems
Fulltext Multiple adaptive neuro-fuzzy inference system with automatic features extraction algorithm for cervical cancer recognition

Al-batah MS, Isa NA, Klaib MF, Al-Betar MA

Comput Math Methods Med, 2014;2014:181245.
PMID: 24707316 DOI: 10.1155/2014/181245

To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE) algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy.

Matched MeSH terms: Computer Systems
Fulltext A Comparative Performance Analysis of Computational Intelligence Techniques to Solve the Asymmetric Travelling Salesman Problem

Odili JB, Noraziah A, Zarina M

Comput Intell Neurosci, 2021;2021:6625438.
PMID: 33986793 DOI: 10.1155/2021/6625438

This paper presents a comparative performance analysis of some metaheuristics such as the African Buffalo Optimization algorithm (ABO), Improved Extremal Optimization (IEO), Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO), Max-Min Ant System (MMAS), Cooperative Genetic Ant System (CGAS), and the heuristic, Randomized Insertion Algorithm (RAI) to solve the asymmetric Travelling Salesman Problem (ATSP). Quite unlike the symmetric Travelling Salesman Problem, there is a paucity of research studies on the asymmetric counterpart. This is quite disturbing because most real-life applications are actually asymmetric in nature. These six algorithms were chosen for their performance comparison because they have posted some of the best results in literature and they employ different search schemes in attempting solutions to the ATSP. The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp-Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. After a number of experiments on the popular but difficult 15 out of the 19 ATSP instances in TSPLIB, the results show that the African Buffalo Optimization algorithm slightly outperformed the other algorithms in obtaining the optimal results and at a much faster speed.

Matched MeSH terms: Computer Systems
Fulltext Intelligent Malaysian Sign Language Translation System Using Convolutional-Based Attention Module with Residual Network

Khan RU, Khattak H, Wong WS, AlSalman H, Mosleh MAA, Mizanur Rahman SM

Comput Intell Neurosci, 2021;2021:9023010.
PMID: 34925497 DOI: 10.1155/2021/9023010

The deaf-mutes population always feels helpless when they are not understood by others and vice versa. This is a big humanitarian problem and needs localised solution. To solve this problem, this study implements a convolutional neural network (CNN), convolutional-based attention module (CBAM) to recognise Malaysian Sign Language (MSL) from images. Two different experiments were conducted for MSL signs, using CBAM-2DResNet (2-Dimensional Residual Network) implementing "Within Blocks" and "Before Classifier" methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time are recorded to evaluate the models' efficiency. The experimental results showed that CBAM-ResNet models achieved a good performance in MSL signs recognition tasks, with accuracy rates of over 90% through a little of variations. The CBAM-ResNet "Before Classifier" models are more efficient than "Within Blocks" CBAM-ResNet models. Thus, the best trained model of CBAM-2DResNet is chosen to develop a real-time sign recognition system for translating from sign language to text and from text to sign language in an easy way of communication between deaf-mutes and other people. All experiment results indicated that the "Before Classifier" of CBAMResNet models is more efficient in recognising MSL and it is worth for future research.

Matched MeSH terms: Computer Systems
Fulltext Big Data acquired by Internet of Things-enabled industrial multichannel wireless sensors networks for active monitoring and control in the smart grid Industry 4.0

Faheem M, Fizza G, Ashraf MW, Butt RA, Ngadi MA, Gungor VC

Data Brief, 2021 Apr;35:106854.
PMID: 33659599 DOI: 10.1016/j.dib.2021.106854

Smart Grid Industry 4.0 (SGI4.0) defines a new paradigm to provide high-quality electricity at a low cost by reacting quickly and effectively to changing energy demands in the highly volatile global markets. However, in SGI4.0, the reliable and efficient gathering and transmission of the observed information from the Internet of Things (IoT)-enabled Cyber-physical systems, such as sensors located in remote places to the control center is the biggest challenge for the Industrial Multichannel Wireless Sensors Networks (IMWSNs). This is due to the harsh nature of the smart grid environment that causes high noise, signal fading, multipath effects, heat, and electromagnetic interference, which reduces the transmission quality and trigger errors in the IMWSNs. Thus, an efficient monitoring and real-time control of unexpected changes in the power generation and distribution processes is essential to guarantee the quality of service (QoS) requirements in the smart grid. In this context, this paper describes the dataset contains measurements acquired by the IMWSNs during events monitoring and control in the smart grid. This work provides an updated detail comparison of our proposed work, including channel detection, channel assignment, and packets forwarding algorithms, collectively called CARP [1] with existing G-RPL [2] and EQSHC [3] schemes in the smart grid. The experimental outcomes show that the dataset and is useful for the design, development, testing, and validation of algorithms for real-time events monitoring and control applications in the smart grid.

Matched MeSH terms: Computer Systems
Fulltext PRESIMS: Requirements and design for Preschool Management System using usability theory

Nor Hasnul Azirah Abdul Hamid, Normalina Ibrahim@Mat, Nurul Najihah Mustopa

ESTEEM Academic Journal, 2020;16(2):51-64.
MyJurnal

Student Information Management System (SIMS) is a computerized system for education that can be used to manage student information and data. PASTI An-Nur is chosen as a case study in developing the system. Thus, several problems are identified that PASTI An-Nur faces due to the
implementation of a manual system in the admission process. The first problem is the paper-based registration form that is prone to lose, misplaced and less secure. As for the payment process, arise a problem in term of higher error rate when checking and calculating the payments. The biggest downfall for PASTI An-Nur is the amount of space used to store all the students' files.
These problems bring inefficiency since the world is changing to computerized, where data management become one of the most significant issues nowadays. So, the aim of developing the Preschool Management System (PRESIMS) is for helping the staffs and teachers in managing the
students' information. The Adapter Waterfall model was used in developing this system. Additionally, usability heuristics was used also as a theory to guide the development of this system. The system has been tested with the four (4) users and two (2) experts. The testing method is the ISO/IEC 9126- 4 approach to measure usability metrics, including efficiency, effectiveness, and satisfaction. Whereas, for the experts, heuristic evaluation is used to bring six (6) usability principles into implementation for testing. The result of the testing is very satisfying, which shows 75.5% of efficiency, 83.33% of effectiveness and three (3) out of four (4) users very satisfied with the system. The result of heuristic evaluation also shows a successful implementation of the system. The details of the result are discussed in this paper and expected to meet the users' specification and it is ready to go live.

Matched MeSH terms: Computer Systems
Modified recurrent equation-based cubic spline interpolation for missing data recovery in phasor measurement unit (PMU)

Thangaraj S, Goh VT, Yap TTV

F1000Res, 2022;11:246.
PMID: 38152076 DOI: 10.12688/f1000research.73182.3

BACKGROUND: Smart grid systems require high-quality Phasor Measurement Unit (PMU) data for proper operation, control, and decision-making. Missing PMU data may lead to improper actions or even blackouts. While the conventional cubic interpolation methods based on the solution of a set of linear equations to solve for the cubic spline coefficients have been applied by many researchers for interpolation of missing data, the computational complexity increases non-linearly with increasing data size.
METHODS: In this work, a modified recurrent equation-based cubic spline interpolation procedure for recovering missing PMU data is proposed. The recurrent equation-based method makes the computations of spline constants simpler. Using PMU data from the State Load Despatch Center (SLDC) in Madhya Pradesh, India, a comparison of the root mean square error (RMSE) values and time of calculation (ToC) is calculated for both methods.
RESULTS: The modified recurrent relation method could retrieve missing values 10 times faster when compared to the conventional cubic interpolation method based on the solution of a set of linear equations. The RMSE values have shown the proposed method is effective even for special cases of missing values (edges, continuous missing values).
CONCLUSIONS: The proposed method can retrieve any number of missing values at any location using observed data with a minimal number of calculations.

Matched MeSH terms: Computer Systems*
Fulltext Real-time acquisition of transendothelial electrical resistance in an all-human, in vitro, 3-dimensional, blood-brain barrier model exemplifies tight-junction integrity

Maherally Z, Fillmore HL, Tan SL, Tan SF, Jassam SA, Quack FI, et al.

FASEB J, 2018 01;32(1):168-182.
PMID: 28883042 DOI: 10.1096/fj.201700162R

The blood-brain barrier (BBB) consists of endothelial cells, astrocytes, and pericytes embedded in basal lamina (BL). Most in vitro models use nonhuman, monolayer cultures for therapeutic-delivery studies, relying on transendothelial electrical resistance (TEER) measurements without other tight-junction (TJ) formation parameters. We aimed to develop reliable, reproducible, in vitro 3-dimensional (3D) models incorporating relevant human, in vivo cell types and BL proteins. The 3D BBB models were constructed with human brain endothelial cells, human astrocytes, and human brain pericytes in mono-, co-, and tricultures. TEER was measured in 3D models using a volt/ohmmeter and cellZscope. Influence of BL proteins-laminin, fibronectin, collagen type IV, agrin, and perlecan-on adhesion and TEER was assessed using an electric cell-substrate impedance-sensing system. TJ protein expression was assessed by Western blotting (WB) and immunocytochemistry (ICC). Perlecan (10 µg/ml) evoked unreportedly high, in vitro TEER values (1200 Ω) and the strongest adhesion. Coculturing endothelial cells with astrocytes yielded the greatest resistance over time. ICC and WB results correlated with resistance levels, with evidence of prominent occludin expression in cocultures. BL proteins exerted differential effects on TEER, whereas astrocytes in contact yielded higher TEER values and TJ expression.-Maherally, Z., Fillmore, H. L., Tan, S. L., Tan, S. F., Jassam, S. A., Quack, F. I., Hatherell, K. E., Pilkington, G. J. Real-time acquisition of transendothelial electrical resistance in an all-human, in vitro, 3-dimensional, blood-brain barrier model exemplifies tight-junction integrity.

Matched MeSH terms: Computer Systems
Security threats categories in healthcare information systems

Samy GN, Ahmad R, Ismail Z

Health Informatics J, 2010 Sep;16(3):201-9.
PMID: 20889850 DOI: 10.1177/1460458210377468

This article attempts to investigate the various types of threats that exist in healthcare information systems (HIS). A study has been carried out in one of the government-supported hospitals in Malaysia.The hospital has been equipped with a Total Hospital Information System (THIS). The data collected were from three different departments, namely the Information Technology Department (ITD), the Medical Record Department (MRD), and the X-Ray Department, using in-depth structured interviews. The study identified 22 types of threats according to major threat categories based on ISO/IEC 27002 (ISO 27799:2008). The results show that the most critical threat for the THIS is power failure followed by acts of human error or failure and other technological factors. This research holds significant value in terms of providing a complete taxonomy of threat categories in HIS and also an important component in the risk analysis stage.

Matched MeSH terms: Computer Systems
MIMO model of an interacting series process for Robust MPC via System Identification

Wibowo TC, Saad N

ISA Trans, 2010 Jul;49(3):335-47.
PMID: 20304404 DOI: 10.1016/j.isatra.2010.02.005

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated.

Matched MeSH terms: Computer Systems
Infrared tomography: data distribution system and software development for real-time velocity measurement

Abdul Rahim R, Pang JF, Chan KS, Leong LC, Sulaiman S, Abdul Manaf MS

ISA Trans, 2007 Apr;46(2):131-45.
PMID: 17367791

The data distribution system of this project is divided into two types, which are a Two-PC Image Reconstruction System and a Two-PC Velocity Measurement System. Each data distribution system is investigated to see whether the results' refreshing rate of the corresponding measurement can be greater than the rate obtained by using a single computer in the same measurement system for each application. Each system has its own flow control protocol for controlling how data is distributed within the system in order to speed up the data processing time. This can be done if two PCs work in parallel. The challenge of this project is to define the data flow process and critical timing during data packaging, transferring and extracting in between PCs. If a single computer is used as a data processing unit, a longer time is needed to produce a measurement result. This insufficient real-time result will cause problems in a feedback control process when applying the system in industrial plants. To increase the refreshing rate of the measurement result, an investigation on a data distribution system is performed to replace the existing data processing unit.

Matched MeSH terms: Computer Systems
Hierarchical control strategy for a three-phase 4-wire microgrid under unbalanced and nonlinear load conditions

Naderipour A, Abdul-Malek Z, Ramachandaramurthy VK, Kalam A, Miveh MR

ISA Trans, 2019 Nov;94:352-369.
PMID: 31078293 DOI: 10.1016/j.isatra.2019.04.025

This paper proposes an improved hierarchical control strategy consists of a primary and a secondary layer for a three-phase 4-wire microgrid under unbalanced and nonlinear load conditions. The primary layer is comprised of a multi-loop control strategy to provide balanced output voltages, a harmonic compensator to reduce the total harmonic distortion (THD), and a droop-based scheme to achieve an accurate power sharing. At the secondary control layer, a reactive power compensator and a frequency restoration loop are designed to improve the accuracy of reactive power sharing and to restore the frequency deviation, respectively. Simulation studies and practical performance are carried out using the DIgSILENT Power Factory software and laboratory testing, to verify the effectiveness of the control strategy in both islanded and grid-connected mode. Zero reactive power sharing error and zero frequency steady-state error have given this control strategy an edge over the conventional control scheme. Furthermore, the proposed scheme presented outstanding voltage control performance, such as fast transient response and low voltage THD. The superiority of the proposed control strategy over the conventional filter-based control scheme is confirmed by the 2 line cycles decrease in the transient response. Additionally, the voltage THDs in islanded mode are reduced from above 5.1% to lower than 2.7% with the proposed control strategy under nonlinear load conditions. The current THD is also reduced from above 21% to lower than 2.4% in the connection point of the microgrid with the offered control scheme in the grid-connected mode.

Matched MeSH terms: Computer Systems
Fulltext An examination of medical imaging literature in Malaysian Citation Index (MyCite)

Nurul Husna Kamarudin, Nor Azlina Ab Rahman, Zainul Ibrahim Zainuddin

International Medical Journal Malaysia, 2017;16(11):12-12.
MyJurnal

The Medical imaging service in Malaysia is expanding. The presence of
imaging technologies needs to be supported by homegrown research to optimize their
use. This study investigated the contribution of researches by Malaysian practitioners to
the field of Medical imaging in the Malaysian Citation index (MyCite) database. (Copied from article).

Matched MeSH terms: Computer Systems
Waste in health information systems: a systematic review

Awang Kalong N, Yusof M

Int J Health Care Qual Assur, 2017 May 08;30(4):341-357.
PMID: 28470137 DOI: 10.1108/IJHCQA-06-2016-0082

Purpose The purpose of this paper is to discuss a systematic review on waste identification related to health information systems (HIS) in Lean transformation. Design/methodology/approach A systematic review was conducted on 19 studies to evaluate Lean transformation and tools used to remove waste related to HIS in clinical settings. Findings Ten waste categories were identified, along with their relationships and applications of Lean tool types related to HIS. Different Lean tools were used at the early and final stages of Lean transformation; the tool selection depended on the waste characteristic. Nine studies reported a positive impact from Lean transformation in improving daily work processes. The selection of Lean tools should be made based on the timing, purpose and characteristics of waste to be removed. Research limitations/implications Overview of waste and its category within HIS and its analysis from socio-technical perspectives enabled the identification of its root cause in a holistic and rigorous manner. Practical implications Understanding waste types, their root cause and review of Lean tools could subsequently lead to the identification of mitigation approach to prevent future error occurrence. Originality/value Specific waste models for HIS settings are yet to be developed. Hence, the identification of the waste categories could guide future implementation of Lean transformations in HIS settings.

Matched MeSH terms: Computer Systems
Fulltext Association Between Residual Inhibition and Neural Activity in Patients with Tinnitus: Protocol for a Controlled Within- and Between-Subject Comparison Study

Hu S, Anschuetz L, Huth ME, Sznitman R, Blaser D, Kompis M, et al.

JMIR Res Protoc, 2019 Jan 09;8(1):e12270.
PMID: 30626571 DOI: 10.2196/12270

BACKGROUND: Electroencephalography (EEG) studies indicate possible associations between tinnitus and changes in the neural activity. However, inconsistent results require further investigation to better understand such heterogeneity and inform the interpretation of previous findings.
OBJECTIVE: This study aims to investigate the feasibility of EEG measurements as an objective indicator for the identification of tinnitus-associated neural activities.
METHODS: To reduce heterogeneity, participants served as their own control using residual inhibition (RI) to modulate the tinnitus perception in a within-subject EEG study design with a tinnitus group. In addition, comparison with a nontinnitus control group allowed for a between-subjects comparison. We will apply RI stimulation to generate tinnitus and nontinnitus conditions in the same subject. Furthermore, high-frequency audiometry (up to 13 kHz) and tinnitometry will be performed.
RESULTS: This work was funded by the Infrastructure Grant of the University of Bern, Bern, Switzerland and Bernafon AG, Bern, Switzerland. Enrollment for the study described in this protocol commenced in February 2018. Data analysis is currently under way and the first results are expected to be submitted for publication in 2019.
CONCLUSIONS: This study design helps in comparing the neural activity between conditions in the same individual, thereby addressing a notable limitation of previous EEG tinnitus studies. In addition, the high-frequency assessment will help to analyze and classify tinnitus symptoms beyond the conventional clinical standard.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/12270.

Matched MeSH terms: Computer Systems
Real-time human respiration carbon dioxide measurement device for cardiorespiratory assessment

Singh OP, Howe TA, Malarvili MB

J Breath Res, 2018 01 04;12(2):026003.
PMID: 28928295 DOI: 10.1088/1752-7163/aa8dbd

The development of a human respiration carbon dioxide (CO2) measurement device to evaluate cardiorespiratory status inside and outside a hospital setting has proven to be a challenging area of research over the few last decades. Hence, we report a real-time, user operable CO2 measurement device using an infrared CO2 sensor (Arduino Mega2560) and a thin film transistor (TFT, 3.5″), incorporated with low pass (cut-off frequency, 10 Hz) and moving average (span, 8) filters. The proposed device measures features such as partial end-tidal carbon dioxide (EtCO2), respiratory rate (RR), inspired carbon dioxide (ICO2), and a newly proposed feature-Hjorth activity-that annotates data with the date and time from a real-time clock, and is stored onto a secure digital (SD) card. Further, it was tested on 22 healthy subjects and the performance (reliability, validity and relationship) of each feature was established using (1) an intraclass correlation coefficient (ICC), (2) standard error measurement (SEM), (3) smallest detectable difference (SDD), (4) Bland-Altman plot, and (5) Pearson's correlation (r). The SEM, SDD, and ICC values for inter- and intra-rater reliability were less than 5% and more than 0.8, respectively. Further, the Bland-Altman plot demonstrates that mean differences ± standard deviations for a set limit were 0.30 ± 0.77 mmHg, -0.34 ± 1.41 mmHg and 0.21 ± 0.64 breath per minute (bpm) for CO2, EtCO2 and RR. The findings revealed that the developed device is highly reliable, providing valid measurements for CO2, EtCO2, ICO2 and RR, and can be used in clinical settings for cardiorespiratory assessment. This research also demonstrates that EtCO2 and RR (r, -0.696) are negatively correlated while EtCO2 and activity (r, 0.846) are positively correlated. Thus, simultaneous measurement of these features may possibly assist physicians in understanding the subject's cardiopulmonary status. In future, the proposed device will be tested with asthmatic patients for use as an early screening tool outside a hospital setting.

Matched MeSH terms: Computer Systems*
Multi-sources data fusion framework for remote triage prioritization in telehealth

Salman OH, Rasid MF, Saripan MI, Subramaniam SK

J Med Syst, 2014 Sep;38(9):103.
PMID: 25047520 DOI: 10.1007/s10916-014-0103-4

The healthcare industry is streamlining processes to offer more timely and effective services to all patients. Computerized software algorithm and smart devices can streamline the relation between users and doctors by providing more services inside the healthcare telemonitoring systems. This paper proposes a multi-sources framework to support advanced healthcare applications. The proposed framework named Multi Sources Healthcare Architecture (MSHA) considers multi-sources: sensors (ECG, SpO2 and Blood Pressure) and text-based inputs from wireless and pervasive devices of Wireless Body Area Network. The proposed framework is used to improve the healthcare scalability efficiency by enhancing the remote triaging and remote prioritization processes for the patients. The proposed framework is also used to provide intelligent services over telemonitoring healthcare services systems by using data fusion method and prioritization technique. As telemonitoring system consists of three tiers (Sensors/ sources, Base station and Server), the simulation of the MSHA algorithm in the base station is demonstrated in this paper. The achievement of a high level of accuracy in the prioritization and triaging patients remotely, is set to be our main goal. Meanwhile, the role of multi sources data fusion in the telemonitoring healthcare services systems has been demonstrated. In addition to that, we discuss how the proposed framework can be applied in a healthcare telemonitoring scenario. Simulation results, for different symptoms relate to different emergency levels of heart chronic diseases, demonstrate the superiority of our algorithm compared with conventional algorithms in terms of classify and prioritize the patients remotely.

Matched MeSH terms: Computer Systems
Design and develop a video conferencing framework for real-time telemedicine applications using secure group-based communication architecture

Mat Kiah ML, Al-Bakri SH, Zaidan AA, Zaidan BB, Hussain M

J Med Syst, 2014 Oct;38(10):133.
PMID: 25199651 DOI: 10.1007/s10916-014-0133-y

One of the applications of modern technology in telemedicine is video conferencing. An alternative to traveling to attend a conference or meeting, video conferencing is becoming increasingly popular among hospitals. By using this technology, doctors can help patients who are unable to physically visit hospitals. Video conferencing particularly benefits patients from rural areas, where good doctors are not always available. Telemedicine has proven to be a blessing to patients who have no access to the best treatment. A telemedicine system consists of customized hardware and software at two locations, namely, at the patient's and the doctor's end. In such cases, the video streams of the conferencing parties may contain highly sensitive information. Thus, real-time data security is one of the most important requirements when designing video conferencing systems. This study proposes a secure framework for video conferencing systems and a complete management solution for secure video conferencing groups. Java Media Framework Application Programming Interface classes are used to design and test the proposed secure framework. Real-time Transport Protocol over User Datagram Protocol is used to transmit the encrypted audio and video streams, and RSA and AES algorithms are used to provide the required security services. Results show that the encryption algorithm insignificantly increases the video conferencing computation time.

Matched MeSH terms: Computer Systems*
Computer assisted diagnostic system in tumor radiography

Faisal A, Parveen S, Badsha S, Sarwar H, Reza AW

J Med Syst, 2013 Jun;37(3):9938.
PMID: 23504472 DOI: 10.1007/s10916-013-9938-3

An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.

Matched MeSH terms: Computer Systems

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