Asynchronous ECG time sampling: Saving bits with Golomb-Rice encoding

Marisa, Thanks; Niederhauser, Thomas; Häberlin, Andreas; Goette, J.; Jacomet, M.; Vogel, Rolf (9 September 2012). Asynchronous ECG time sampling: Saving bits with Golomb-Rice encoding. In: Computing in Cardiology (CinC), 2012. Krakow. 09-12 Sept. 2012.

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We present a technique for online compression of ECG signals using the Golomb-Rice encoding algorithm. This is facilitated by a novel time encoding asynchronous analog-to-digital converter targeted for low-power, implantable, long-term bio-medical sensing applications. In contrast to capturing the actual signal (voltage) values the asynchronous time encoder captures and encodes the time information at which predefined changes occur in the signal thereby minimizing the sensor's energy use and the number of bits we store to represent the information by not capturing unnecessary samples. The time encoder transforms the ECG signal data to pure time information that has a geometric distribution such that the Golomb-Rice encoding algorithm can be used to further compress the data. An overall online compression rate of about 6 times is achievable without the usual computations associated with most compression methods.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Cardiovascular Engineering (CVE)
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Cardiovascular Engineering (CVE) > ARTORG Center - Cardiovascular Engineering (Blood Vessel)

UniBE Contributor:

Marisa, Thanks, Niederhauser, Thomas, Häberlin, Andreas David Heinrich, Vogel, Rolf

Subjects:

600 Technology > 620 Engineering

ISSN:

2325-8861

Language:

English

Submitter:

Thomas Niederhauser

Date Deposited:

20 Jun 2014 13:30

Last Modified:

05 Dec 2022 14:33

Related URLs:

Uncontrolled Keywords:

analogue-digital conversion, data compression, electrocardiography, encoding, medical signal processing, signal sampling, Golomb-Rice encoding algorithm, actual signal voltage values, asynchronous ECG time sampling, asynchronous time encoder capturing, data compression, geometric distribution, low-power implantable long-term biomedical sensing applications, novel time encoding asynchronous analog-to-digital converter, online ECG signal compression, online compression rate, sensor energy use, time information, Educational institutions, Electrocardiography, Encoding, Heart beat, Memory management, Signal resolution, Surface waves

URI:

https://boris.unibe.ch/id/eprint/50991

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