Congestive heart failure management in a home-care system through the CHS contact center

Maglaveras, Nicos; Lekka, Irini; Chouvarda, Ioanna; Adamidis, D.; Karvounis, Haralambos; Louridas, George; Zeevi, Benjamin; Balas, E. Andrew

doi:10.1109/cic.2003.1291122

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…In previous studies, home telecare systems using noncontinuous monitoring and telephone data transmission [3,4] have already proven effective in the management of chronic diseases such as congestive heart failure (CHF) and hypertension. Continuous monitoring would allow telecare systems to accommodate a larger number of pathologies including asymptomatic conditions like atrial fibrillation for which intermittent monitoring is not sufficient.…”

Section: Introductionmentioning

confidence: 99%

BioStream: a system architecture for real-time processing of physiological signals

Bar-Or

Healey

Kontothanassis

et al.

The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Continuous monitoring of physiological signals has the potential to greatly improve the quality of life of patients with chronic diseases. Recent advances in sensor technology make the capture of such signals possible. In this paper, we present BioStream, a real-time, and operator-based software solution for managing physiological sensor streams. It is built on top of a general-purpose stream processing software architecture. The system processes data using plug-in analysis components that can be easily composed into plans using a graphical programming environment. The architecture is scalable, allowing implementation on systems ranging from desktops to server farms. It guarantees real-time response and data persistence in a distributed environment. We apply this architecture to the problem of multipatient, real-time, physiological signal monitoring, analysis, indexing and visualization.

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Section: Introductionmentioning

confidence: 99%

BioStream: a system architecture for real-time processing of physiological signals

Bar-Or

Healey

Kontothanassis

et al.

The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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A Fusion Health Monitoring Using ECG and Accelerometer sensors for Elderly Persons at Home

Chung

Bhardwaj

Purwar

et al. 2007

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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An ECG and tri-axial accelerometer signal monitoring and analysis method for the homecare of elderly persons or patients, using wireless sensors technology was design and implemented. This paper presents a prototype of wellness monitoring system capable of recording, and analyzing continuous ECG and accelerometer data received from the human body. The system provides an application for recording activities, events and potentially important medical symptoms. The ECG features are used to detect life-threatening arrhythmias, with an emphasis on the software for analyzing the P-wave, QRS complex, and T-wave in ECG signals at server connected to base station which is receiving data from the wireless sensor on the patient body. Activity such as walking and running are detected from the body movements recorded by the accelerometer sensor. IEEE802.15.4 is used for wireless communication between sensor and base station. If any abnormality occurs at server then the alarm condition sends to the doctor' Personal Digital Assistant (PDA).

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Heart Rate Variability on 7-Day Holter Monitoring Using a Bootstrap Rhythmometric Procedure

Goya–Esteban

Mora-Jiménez

Rojo‐Álvarez

et al. 2010

IEEE Trans. Biomed. Eng.

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Heart rate variability (HRV) markers have been widely used to characterize the autonomous regulation state of the heart from 24-h Holter monitoring, but long-term evolution of HRV indexes is mostly unknown. A dataset of 7-day Holter recordings of 22 patients with congestive heart failure was studied. A rhythmometric procedure was designed to characterize the infradian, circadian, and ultradian components for each patient, as well as circadian and ultradian fluctuations. Furthermore, a bootstrap test yielded automatically the rhythmometric model for each patient. We analyzed the temporal evolution of relevant time-domain (AVNN, SDNN, and NN50), frequency-domain (LF, HF, HFn, and LF/HF), and nonlinear (alpha(1) and SampEn) HRV indexes. Circadian components were the most significant for all HRV indexes, but the infradian ones were also strongly present in NN50, HFn, LF/HF, alpha(1), and SampEn indexes. Among ultradian components that one corresponding to 12 h, was the most relevant. Long-term monitoring of HRV conveys new potentially relevant rhythmometric information, which can be analyzed by using the proposed automatic procedure.

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Congestive heart failure management in a home-care system through the CHS contact center

Abstract: The Citizen Health System (CHS) is a European Commission (CEC)

Cited by 3 publications

References 7 publications

BioStream: a system architecture for real-time processing of physiological signals

BioStream: a system architecture for real-time processing of physiological signals

A Fusion Health Monitoring Using ECG and Accelerometer sensors for Elderly Persons at Home

Heart Rate Variability on 7-Day Holter Monitoring Using a Bootstrap Rhythmometric Procedure

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