Current Issue : July - September Volume : 2012 Issue Number : 3 Articles : 5 Articles
In wireless healthcare monitoring systems, bandwidth allocation is an efficient solution to the problem of scarce wireless bandwidth\r\nfor the monitoring of patients. However, when the central unit cannot access the exact channel state information (CSI), the\r\nefficiency of bandwidth allocation decreases, and the system performance also decreases. In this paper, we propose an algorithm\r\nto reduce the negative effects of imperfect CSI on system performance. In this algorithm, the central unit can predict the current\r\nCSI by previous CSI when the current CSI is not available. We analyze the reliability of the proposed algorithm by deducing the\r\nstandard error of estimated CSI with this algorithm. In addition, we analyze the efficiency of the proposed algorithm by discussing\r\nthe system performance with this algorithm....
E-Health services comprise a broad range of healthcare services delivered by using information and communication technology.\r\nIn order to support existing as well as emerging e-Health services over converged next generation network (NGN) architectures,\r\nthere is a need for network QoS control mechanisms that meet the often stringent requirements of such services. In this paper,\r\nwe evaluate the QoS support for e-Health services in the context of the Evolved Packet System (EPS), specified by the Third\r\nGeneration Partnership Project (3GPP) as amulti-access all-IP NGN.We classify heterogeneous e-Health services based on context\r\nand network QoS requirements and propose a mapping to existing 3GPP QoS Class Identifiers (QCIs) that serve as a basis for\r\nthe class-based QoS concept of the EPS. The proposed mapping aims to provide network operators with guidelines for meeting\r\nheterogeneous e-Health service requirements. As an example, we present the QoS requirements for a prototype e-Health service\r\nsupporting tele-consultation between a patient and a doctor and illustrate the use of the proposed mapping to QCIs in standardized\r\nQoS control procedures....
Blood pressure self-measurement (BPSM) requires patients to follow a range of recommendations in order to be considered\r\nreliable for diagnostic use. We investigated currently used BPSM interventions at four medical clinics combined with an online\r\nquestionnaire targeting BPSM users. We found that the participating healthcare personnel perceived BPSM as a relevant and\r\nuseful intervention method providing that the recommendations are followed. A total of six challenges were identified: (1) existing\r\ndevices do not guarantee that the recommendations are followed, (2) healthcare providers cannot verify whether self-monitoring\r\npatients follow the recommendations, (3) patients are not aware of all recommendations and the need to follow them, (4) risk\r\nof patient induced reporting bias, (5) risk of healthcare provider induced data-transfer bias, and (6) risk of data being registered\r\nas belonging to the wrong patient. We conclude that existing BPSM interventions could be significantly affected by user-induced\r\nbias resulting in an indeterminable quality of the measurement data. Therefore, we suggest applying context-aware technological\r\nsupport tools to better detect and quantify user errors. This may allow us to develop solutions that could overcome or compensate\r\nfor such errors in the future....
Safety-net settings across the country have grappled with providing adequate access to specialty care services. San Francisco General\r\nHospital and Trauma Center, serving as the city�s primary safety-net hospital, has also had to struggle with the same issue. With\r\nHealthy San Francisco, the City and County of San Francisco�s Universal Healthcare mandate, the increased demand for specialty\r\ncare services has placed a further strain on the system.With the recent passage of California Proposition 1D, infrastructural funds\r\nare now set aside to assist in connecting major hospitals with primary care clinics in remote areas all over the state of California,\r\nusing telemedicine. Based on a selected sample of key informant interviews with local staff physicians, this study provides further\r\ninsight into the current process of e-referral which uses electronic communication for making referrals to specialty care. It also\r\nidentifies key services for telemedicine in primary and specialty care settings within the San Francisco public health system. This\r\nstudy concludes with proposals for a framework that seek to increase collaboration between the referring primary care physician\r\nand specialist, to prioritize institution of these key services for telemedicine....
Mobile solutions for patient cardiac monitoring are viewed with growing interest, and improvements on current implementations\r\nare frequently reported, with wireless, and in particular, wearable devices promising to achieve ubiquity. However, due to\r\nunavoidable power consumption limitations, the amount of data acquired, processed, and transmitted needs to be diminished,\r\nwhich is counterproductive, regarding the quality of the information produced. Compressed sensing implementation in wireless\r\nsensor networks (WSNs) promises to bring gains not only in power savings to the devices, but also with minor impact in signal\r\nquality. Several cardiac signals have a sparse representation in some wavelet transformations. The compressed sensing paradigm\r\nstates that signals can be recovered from a few projections into another basis, incoherent with the first. This paper evaluates\r\nthe compressed sensing paradigm impact in a cardiac monitoring WSN, discussing the implications in data reliability, energy\r\nmanagement, and the improvements accomplished by in-network processing....
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