Current Issue : July - September Volume : 2017 Issue Number : 3 Articles : 5 Articles
In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically,\nwe address the architecture of a CDSS by characterizing it fromthree layers and discuss the algorithms in each layer.Alsowe address\nthe applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when\nusing multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the\nother design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other\ndesigns, while ensuring a high level of system accuracy....
Security has been an issue of contention in healthcare. The lack of familiarity and poor\nimplementation of security in healthcare leave the patients� data vulnerable to attackers. The main\nissue is assessing how we can provide security in an RPM infrastructure. The findings in literature\nshow there is little empirical evidence on proper implementation of security. Therefore, there\nis an urgent need in addressing cybersecurity issues in medical devices. Through the review of\nrelevant literature in remote patient monitoring and use of a Microsoft threat modelling tool, we\nidentify and explore current vulnerabilities and threats in IEEE 11073 standard devices to propose\na new security framework for remote patient monitoring devices. Additionally, current RPM\ndevices have a limitation on the number of people who can share a single device, therefore, we\npropose the use of NFC for identification in Remote Patient Monitoring (RPM) devices for multi-user\nenvironments where we have multiple people sharing a single device to reduce errors associated\nwith incorrect user identification. We finally show how several techniques have been used to build\nthe proposed framework....
Phonocardiogram (PCG) monitoring on newborns is one of the most important and\nchallenging tasks in the heart assessment in the early ages of life. In this paper, we present a novel\napproach for cardiac monitoring applied in PCG data. This basic system coupled with denoising,\nsegmentation, cardiac cycle selection and classification of heart sound can be used widely for a large\nnumber of the data. This paper describes the problems and additional advantages of the PCG\nmethod including the possibility of recording heart sound at home, removing unwanted noises\nand data reduction on a mobile device, and an intelligent system to diagnose heart diseases on\nthe cloud server. A wide range of physiological features from various analysis domains, including\nmodeling, time/frequency domain analysis, an algorithm, etc., is proposed in order to extract features\nwhich will be considered as inputs for the classifier. In order to record the PCG data set from multiple\nsubjects over one year, an electronic stethoscope was used for collecting data that was connected to\na mobile device. In this study, we used different types of classifiers in order to distinguish between\nhealthy and pathological heart sounds, and a comparison on the performances revealed that support\nvector machine (SVM) provides 92.2% accuracy and AUC = 0.98 in a time of 1.14 seconds for training,\non a dataset of 116 samples....
Falls are common and dangerous for survivors of stroke at all stages of recovery. The widespread need to assess fall risk in real\ntime for individuals after stroke has generated emerging requests for a reliable, inexpensive, quantifiable, and remote clinical\nmeasure/tool. In order to meet these requests, we explore the Functional Reach Test (FRT) for real-time fall risk assessment and\nimplement the FRT function in mStroke, a real-time and automaticmobile health systemfor poststroke recovery and rehabilitation.\nmStroke is designed, developed, and delivered as an Application (App) running on a hardware platform consisting of an iPad and\none or two wireless body motion sensors based on different mobile health functions. The FRT function in mStroke is extensively\ntested on healthy human subjects to verify its concept and feasibility. Preliminary performance will be presented to justify the\nfurther exploration of the FRT function in mStroke through clinical trials on individuals after stroke,whichmay guide its ubiquitous\nexploitation in the near future....
Background: Patient-centered design that addresses patientsââ?¬â?¢ preferences and needs is considered an important aim for improving\nhealth care systems. At present, within the field of pain rehabilitation, patientsââ?¬â?¢ preferences regarding telerehabilitation remain\nscarcely explored and little is known about the optimal combination between human and electronic contact from the patientsââ?¬â?¢\nperspective. In addition, limited evidence is available about the best way to explore patientsââ?¬â?¢ preferences. Therefore, the assessment\nof patientsââ?¬â?¢ preferences regarding telemedicine is an important step toward the design of effective patient-centered care.\nObjective: To identify which telerehabilitation treatment options patients with chronic pain are most likely to accept as alternatives\nto conventional rehabilitation and assess which treatment attributes are most important to them.\nMethods: A discrete choice experiment with 15 choice tasks, combining 6 telerehabilitation treatment characteristics, was\ndesigned. Each choice task consisted of 2 hypothetical treatment scenarios and 1 opt-out scenario. Relative attribute importance\nwas estimated using a bivariate probit regression analysis. One hundred and thirty surveys were received, of which 104 were\nusable questionnaires; thus, resulting in a total of 1547 observations.\nResults: Physician communication mode, the use of feedback and monitoring technology (FMT), and exercise location were\nkey drivers of patientsââ?¬â?¢ treatment preferences (P<.001). Patients were willing to accept less frequent physician consultation offered\nmainly through video communication, provided that they were offered FMT and some face-to-face consultation and could exercise\noutside their home environment at flexible exercise hours. Home-based telerehabilitation scenarios with minimal physician\nsupervision were the least preferred. A reduction in health care premiums would make these telerehabilitation scenarios as attractive\nas conventional clinic-based rehabilitation.\nConclusions: ââ?¬Å?Intermediateââ?¬Â telerehabilitation treatments offering FMT, some face-to-face consulting, and a gym-based exercise\nlocation should be pursued as promising alternatives to conventional chronic pain rehabilitation. Further research is necessary to\nexplore whether strategies other than health care premium reductions could also increase the value of home telerehabilitation\ntreatment....
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