Predictive ECG coding using linear time-invariant models | Zendy

Aleksandar Bošković | Zendy; Miroslav Despotović | Zendy; Dragana Bajić | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Predictive ECG coding using linear time-invariant models

Author(s) -

Aleksandar Bošković,

Miroslav Despotović,

Dragana Bajić

Publication year - 2004

Publication title -

archive of oncology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.104

H-Index - 13

eISSN - 1450-9520

pISSN - 0354-7310

DOI - 10.2298/aoo0403152b

Subject(s) - lossless compression , predictive coding , computer science , lti system theory , data compression , invariant (physics) , compression ratio , linear prediction , artificial intelligence , coding (social sciences) , pattern recognition (psychology) , algorithm , mathematics , statistics , linear system , engineering , mathematical analysis , automotive engineering , mathematical physics , internal combustion engine

Electrocardiogram (ECG) signal compression suffers of lack of standards for analogue-digital conversion. Results of this study have shown that 8 bits/sample, although frequently in use, does not satisfy quality criteria for medical doctors. This paper also presents predictive technique for lossless ECG compression using linear time-invariant models. Tests on clinically measured ECG signals confirm a very good performance in terms of compression ratio

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research