Wireless ECG monitoring system

Šimunić, Dina; Tomac, Slaven; Vrdoljak, Ivan

doi:10.1109/wirelessvitae.2009.5172426

Cited by 19 publications

(8 citation statements)

References 3 publications

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“…By beat (Peak) detector co-work with tendency detector, we can check if there is a desired high slope and acute amplitude change base on low frequency tendency signal. The tendency detector is used to detect the baseline of the ECG signal, and can be represented by , (1) where i represents sample index, and Q[i], S[i] represent the magnitude of Q, S points of sample i. We can average N samples to obtain more accurate value.…”

Section: B Mobile Hubmentioning

confidence: 99%

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Energy efficient diagnostic grade mobile ECG monitoring

Chan

Chou

Chen

et al. 2012

10th IEEE International NEWCAS Conference

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An energy efficient prototype for diagnostic grade mobile ECG monitoring is developed. The prototype is developed with commercial discrete components to demo a patient centric medical environment. The prototype uses a mobile phone as a gateway to transmit the measured ECG data back to the medical cloud: Bluetooth for ECG sensor to the mobile phone, while 3G/WiFi for the mobile phone to the medical cloud. Therefore, the patients are not tied to the hospital or home, and can go outside for common life. The prototype can calculate on the mobile phone the RR intervals. More accurate RR, QRS interval can be obtained from server. The platform can also analyze the non-linear analysis of heart rate variability in patients with congestive heart failure based on multi-scale entropy. The size of the developed ECG sensor node is 75mm x 35mm x 20mm which is smaller than a credit card in area. The noise density of the amplifier is 22nV/√ Hz, and the total power of the sensor frontend is below 100uA. For wireless transmission, the Bluetooth module with a micro controller consumes current less than 110mA. The prototype can monitor ECG continuously for over 24 hours or with 3 weeks standby time.

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Section: B Mobile Hubmentioning

confidence: 99%

“…Recently, many researches focused on the development wireless or mobile ECG monitoring devices [1,2,3,4] and have many achievements. Many of the systems used the body area network solutions.…”

Section: Introductionmentioning

confidence: 99%

Energy efficient diagnostic grade mobile ECG monitoring

Chan

Chou

Chen

et al. 2012

10th IEEE International NEWCAS Conference

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“…Basically, there are three types of ECG monitoring [5]. In particular, ambulatory electrocardiography is an effective diagnostic tool to deal with heart crises related to daily activities such as exercise, eating, stress, or even sleeping [6].…”

Section: A Ecg Monitoringmentioning

confidence: 99%

“…1, the wireless transmission of ECG data goes through two heterogeneous links. Hence, the average transmission delay T e consists of two parts: where S e is the average transmission delay over the cellular link, which can be evaluated by (5), and Q e is the average transmission delay over the first Bluetooth link. As an ECG monitoring device is expected to be of low power and low cost, a lightweight design is preferable for its wireless communication module.…”

Section: Context-aware Packetization and Prioritized Transmissionmentioning

confidence: 99%

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Heterogeneous Multi-Hop Transmission of Compressed ECG Data from Wireless Body Area Network

Song

2011

2011 IEEE International Conference on Communications (ICC)

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Nowadays, the healthcare market keeps growing with an increasing aging population. As a promising technology, a body area network (BAN) consisting of biomedical sensors across a human body can gather vital life signals such as electrocardiogram (ECG), pulse, and blood pressure to facilitate effective diagnosis. The BAN can be further integrated with existing wireless infrastructure to offer mHealth services. In this paper, we analyze the transmission performance of compressed ECG data over a heterogeneous multi-hop wireless channel. The ECG data from a BAN are compressed and sent through a Bluetooth-enabled ECG monitor to a smart phone and thereafter to a cellular base station. Due to potentially life-threatening situations, timely delivery of ECG data is an essential requirement. Exploiting the inherent heartbeat pattern in ECG traffic, we introduce a context-aware packetization for ECG transmission. Further, a non-preemptive priority rule is applied to mitigate the impact of background traffic and prioritize the transmission of critical ECG data. Then, we analytically evaluate the overall transmission delay of ECG packets.Index Terms-Wireless heterogeneous networking, ECG data transmission, wireless body area networks.

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