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Journal of Medical Systems

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https://www.readbyqxmd.com/read/30406503/a-novel-vision-enhancing-technology-for-low-vision-impairments
#1
Carmelo Lodato, Patrizia Ribino
Ocular disorders such as vitreoretinal pathologies are widespread, especially in older adults. In particular, degenerative diseases of the retina such as macular senile degenerations are on the rise and affect millions of people with hundreds of thousands of new cases each year. These diseases can cause profoundly disabling visual impairments, in some cases severely compromising the central and/or the peripheral vision in one or both eyes. In this paper, we present a novel vision aids technology that allows for correcting or attenuating the perception of visual field defects due to ocular pathologies of diverse origins or traumas by using techniques of 3D visualisation, eye tracking, and image processing...
November 7, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30406430/a-novel-methodology-for-extracting-and-evaluating-therapeutic-movements-in-game-based-motion-capture-rehabilitation-systems
#2
Zhichao Yang, Mohammad H Rafiei, Alexis Hall, Caroline Thomas, Hali A Midtlien, Alexander Hasselbach, Hojjat Adeli, Lynne V Gauthier
Virtual rehabilitation yields outcomes that are at least as good as traditional care for improving upper limb function and the capacity to carry out activities of daily living. Due to the advent of low-cost gaming systems and patient preference for game-based therapies, video game technology will likely be increasingly utilized in physical therapy practice in the coming years. Gaming systems that incorporate low-cost motion capture technology often generate large datasets of therapeutic movements performed over the course of rehabilitation...
November 7, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30406316/importance-of-compliance-audits-for-a-pediatric-complicated-appendicitis-clinical-practice-guideline
#3
Mehul V Raval, Alan B Kwan, Curtis D Travers, Kurt F Heiss
Clinical practice guidelines (CPG) have been shown to decrease practice variation, reduce resource use, and improve patient outcomes. The purpose of this study was to audit compliance of a pediatric complicated appendicitis CPG to identify areas for continued improvement. A comprehensive complicated appendicitis CPG was implemented in a children's hospital system. Outcomes were compared for 48 months pre- (01/2012 to 12/2015) and 28 months post-implementation (01/2016 to 04/2018). A detailed compliance audit was nested within the post-implementation period in 60 consecutive patients from 11/2017 to 03/2018...
November 7, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30402801/an-automatic-channel-selection-approach-for-ica-based-motor-imagery-brain-computer-interface
#4
Jing Ruan, Xiaopei Wu, Bangyan Zhou, Xiaojing Guo, Zhao Lv
Independent component analysis (ICA) is a potential spatial filtering method for the implementation of motor imagery brain-computer interface (MIBCI). However, ICA-based MIBCI (ICA-MIBCI) is sensitive to electroencephalogram (EEG) channels and the quality of the training data, which are two crucial factors affecting the stability and classification performance of ICA-MIBCI. To address these problems, this paper is mainly focused on the investigation of EEG channel optimization. As a reference, we constructed a single-trial-based ICA-MIBCI system with commonly used channels and common spatial pattern-based MIBCI (CSP-MIBCI)...
November 6, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30402781/patient-satisfaction-with-mobile-health-mhealth-application-for-exercise-intervention-in-breast-cancer-survivors
#5
Hannah Lee, Kyeong Eun Uhm, In Yae Cheong, Ji Sung Yoo, Seung Hyun Chung, Yong Hyun Park, Ji Youl Lee, Ji Hye Hwang
This study aimed to assess user satisfaction with mobile health (mHealth) application in breast cancer survivors after a 12-week exercise program and provide developers with reference points for mHealth applications from the perspective of patients and physicians. This is a retrospective review of prospectively collected multicenter data of 88 breast cancer survivors who carried out a 12-week exercise program via smartphone application with pedometer. Personalized programs including aerobic and resistance exercise were prescribed by physiatrists...
November 6, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30397730/deep-deterministic-learning-for-pattern-recognition-of-different-cardiac-diseases-through-the-internet-of-medical-things
#6
Uzair Iqbal, Teh Ying Wah, Muhammad Habib Ur Rehman, Ghulam Mujtaba, Muhammad Imran, Muhammad Shoaib
Electrocardiography (ECG) sensors play a vital role in the Internet of Medical Things, and these sensors help in monitoring the electrical activity of the heart. ECG signal analysis can improve human life in many ways, from diagnosing diseases among cardiac patients to managing the lifestyles of diabetic patients. Abnormalities in heart activities lead to different cardiac diseases and arrhythmia. However, some cardiac diseases, such as myocardial infarction (MI) and atrial fibrillation (Af), require special attention due to their direct impact on human life...
November 5, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30392052/mixture-model-segmentation-system-for-parasagittal-meningioma-brain-tumor-classification-based-on-hybrid-feature-vector
#7
L Arokia Jesu Prabhu, A Jayachandran
Meningioma is the one of the most common type of brain tumor, it as arises from the meninges and encloses the spine and the brain inside the skull. It accounts for 30% of all types of brain tumor. Meningioma's can occur in many parts of the brain and accordingly it is named. In this paper, a mixture model based classification of meningioma brain tumor using MRI image is developed. The proposed method consists of four stages. In the first stage, with respect to the cells' boundary, it is necessary to further processing, which ensures the boundary of some cells is a discrete region...
November 3, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30390162/a-deep-automated-skeletal-bone-age-assessment-model-with-heterogeneous-features-learning
#8
Chao Tong, Baoyu Liang, Jun Li, Zhigao Zheng
Skeletal bone age assessment is a widely used standard procedure in both disease detection and growth prediction for children in endocrinology. Conventional manual assessment methods mainly rely on personal experience in observing X-ray images of left hand and wrist to calculate bone age, which show some intrinsic limitations from low efficiency to unstable accuracy. To address these problems, some automated methods based on image processing or machine learning have been proposed, while their performances are not satisfying enough yet in assessment accuracy...
November 3, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30390144/privacy-protection-for-point-of-care-using-chaotic-maps-based-authentication-and-key-agreement
#9
Liping Zhang, He Luo, Lanchao Zhao, Yixin Zhang
Recently, remote points-of-care as a novel medical model has emerged and received considerable attention due to its convenient medical services such as efficient real-time monitoring and prompt information feedback. Although the points-of-care has more attractive advantages compared with traditional health care systems, some important issues still require a serious consideration such as privacy protection and the security of the transmitted biomedical signals. In this study, we propose a novel authentication and key agreement mechanism that ensures privacy preservation and provides biomedical signals protection during the communication process by negotiating a shared key to encrypt/decrypt sensitive information...
November 3, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30390142/design-of-an-algorithm-for-automated-computer-guided-pasi-measurements-by-digital-image-analysis
#10
Christine Fink, Tobias Fuchs, Alexander Enk, Holger A Haenssle
The Psoriasis Area and Severity Index (PASI) is the most accepted method for psoriasis severity scoring. However, a prominent level of subjectivity and a low intra- and inter-rater reproducibility was reported. Therefore, an accurate and reproducible measure of psoriasis severity is needed, especially in the setting of registration studies for systemic anti-psoriatic drugs. Herein we describe a robust, user-friendly, computer-guided technology that allows for automated PASI measurements after total body imaging and digital image analysis...
November 3, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30382410/diabetic-retinopathy-diagnosis-from-retinal-images-using-modified-hopfield-neural-network
#11
D Jude Hemanth, J Anitha, Le Hoang Son, Mamta Mittal
Disease diagnosis from medical images has become increasingly important in medical science. Abnormality identification in retinal images has become a challenging task in medical science. Effective machine learning and soft computing methods should be used to facilitate Diabetic Retinopathy Diagnosis from Retinal Images. Artificial Neural Networks are widely preferred for Diabetic Retinopathy Diagnosis from Retinal Images. It was observed that the conventional neural networks especially the Hopfield Neural Network (HNN) may be inaccurate due to the weight values are not adjusted in the training process...
October 31, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30374695/patient-tailored-augmented-reality-games-for-assessing-upper-extremity-motor-impairments-in-parkinson-s-disease-and-stroke
#12
Paulina J M Bank, Marina A Cidota, P Elma W Ouwehand, Stephan G Lukosch
In clinical practice, upper extremity motor impairments are commonly assessed with disease-specific, subjectively scored and low-resolution rating scales that often do not consider the variations in tasks and environment that are essential aspects of daily life. Augmented reality (AR) systems with contactless tracking of the hand and upper body offer opportunities for objective quantification of motor (dys)function in a challenging, engaging and patient-tailored environment. In this study, we explore the potential of AR for evaluating 1) speed and goal-directedness of movements within the individually determined interaction space, 2) adaptation of hand opening to objects of different sizes, and 3) obstacle avoidance in healthy individuals (N = 10) and two highly prevalent neurological conditions (N = 10 patients with Parkinson's Disease and N = 10 stroke patients)...
October 30, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30374820/real-time-medical-systems-based-on-human-biometric-steganography-a-systematic-review
#13
REVIEW
A H Mohsin, A A Zaidan, B B Zaidan, Shamsul Arrieya Bin Ariffin, O S Albahri, A S Albahri, M A Alsalem, K I Mohammed, M Hashim
In real-time medical systems, the role of biometric technology is significant in authentication systems because it is used in verifying the identity of people through their biometric features. The biometric technology provides crucial properties for biometric features that can support the process of personal identification. The storage of biometric template within a central database makes it vulnerable to attack which can also occur during data transmission. Therefore, an alternative mechanism of protection becomes important to develop...
October 29, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30374669/design-of-nirs-probe-based-on-computational-model-to-find-out-the-optimal-location-for-non-invasive-brain-stimulation
#14
Gaurav Sharma, Shubhajit Roy Chowdhury
The paper presents a computational model to analyse the electric field distribution on the cerebral cortex during high definition transcranial direct current stimulation (HD-tDCS) technique. The current research aims to improve the focality in term of magnitude of electric field (norm [E]) and magnitude of current density (norm [J]) in the gyri and sulci of white matter. The proposed computational model is used to predict the magnitude of current density and magnitude of electric field distribution generated across the target region of cerebral cortex for specific small size 1 × 1 cm2 multi-electrode HD-tDCS configurations...
October 29, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30368611/machine-learning-for-predicting-cognitive-diseases-methods-data-sources-and-risk-factors
#15
REVIEW
Brankica Bratić, Vladimir Kurbalija, Mirjana Ivanović, Iztok Oder, Zoran Bosnić
Machine learning and data mining approaches are being successfully applied to different fields of life sciences for the past 20 years. Medicine is one of the most suitable application domains for these techniques since they help model diagnostic information based on causal and/or statistical data and therefore reveal hidden dependencies between symptoms and illnesses. In this paper we give a detailed overview of the recent machine learning research and its applications for predicting cognitive diseases, especially the Alzheimer's disease, mild cognitive impairment and the Parkinson's disease...
October 27, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30338399/using-the-collective-system-design-methodology-to-improve-a-medical-center-emergency-room-performance
#16
David Cochran, Joseph Swartz, Behin Elahi, Joseph Smith
Emergency Room (ER) crowding is one of the more complex issues in the healthcare system worldwide. Crowding gives rise to long ER waiting times, patient dissatisfaction, and negative effects on a healthcare systems' performance. This paper focuses on the utilization of the Collective System Design (CSD) methodology to optimize the performance of an ER, which is of principal importance both from a life-threatening and an economic standpoint. The CSD technique is applied to detect areas of deficiency and to identify the functional requirements of the system to address those issues...
October 18, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30334106/ecg-signal-classification-using-various-machine-learning-techniques
#17
S Celin, K Vasanth
Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes and detects small electrical changes for each heat rate. It is used to investigate some types of abnormal heart function including arrhythmias and conduction disturbance. In this paper the proposed method is used to classify the ECG signal by using classification technique. First the Input signal is preprocessed by using filtering method such as low pass, high pass and butter worth filter to remove the high frequency noise...
October 18, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30334104/vehicular-cloud-for-smart-driving-using-internet-of-things
#18
S Vijayarangam, J Megalai, Sivakumar Krishnan, Sivakumar Nagarajan, M Ramya Devi, S Lokesh
The vehicular cloud can be made more reliable by having minimum number of vehicles and their accessibility of the vehicles in the given lane; in addition reliability can also be made using the function called movement of vehicles. The number of vehicles present in the area determines the task that can be accessed in the area and with the help of travelling time of the vehicles the validity of the lane can be determined. In this paper, a research is carried based on the stochastic investigation on the some of attributes of traffic with the help of cloud in street portion to accept the necessary attribute prototypes...
October 18, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30328518/an-extended-hackathon-model-for-collaborative-education-in-medical-innovation
#19
Jason K Wang, Ravinder D Pamnani, Robson Capasso, Robert T Chang
To support the next generation of healthcare innovators - whether they be engineers, designers, clinicians, or business experts by training - education in the emerging field of medical innovation should be made easily and widely accessible to undergraduate students, graduate students, and young professionals, early in their careers. Currently, medical innovation curricula are taught through semester-long courses or year-long fellowships at a handful of universities, reaching only a limited demographic of participants...
October 17, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/30327955/information-system-maturity-models-in-healthcare
#20
REVIEW
Jorge Gomes, Mário Romão
The use of information systems in healthcare (HIS) has been recognised as having crucial importance in improving the efficiency, cost-effectiveness, quality, and safety of medical care delivery. HIS has the potential to improve individuals' health and providers' performance by producing better quality, cost savings, and greater patient involvement in their own health. There have been two major drivers for the HIS investments in healthcare: The ever-increasing burden from chronic disease with costs growing significantly faster and the recognition of the need for greatly improved quality and safety in health delivery...
October 16, 2018: Journal of Medical Systems
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