Efficient Haar Wavelet Transform for Detecting Saccades and Blinks in Real-Time EOG Signal

In this study, we present an efficient Haar discrete wavelet transform architecture using Radix- 2 r multiplier and 4:2 compressor. The functionality of this architecture is verified using real-time electrooculogram signal. This architecture is useful for saccade identification and blink detection,...

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Bibliographic Details
Published in:SN computer science 2021-05, Vol.2 (3), p.156, Article 156
Main Authors: Gundugonti, Kishore Kumar, Narayanam, Balaji
Format: Article
Language:English
Subjects:
Algorithms
Computer Imaging
Computer Science
Computer Systems Organization and Communication Networks
Data Science and Communication
Data Structures and Information Theory
Discrete Wavelet Transform
Epilepsy
Eye movements
Field programmable gate arrays
Information Systems and Communication Service
Multiplication & division
Multipliers
Number systems
Original Research
Pattern Recognition and Graphics
Power consumption
Real time
Signal processing
Software Engineering/Programming and Operating Systems
Vision
Wavelet transforms
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Summary:In this study, we present an efficient Haar discrete wavelet transform architecture using Radix- 2 r multiplier and 4:2 compressor. The functionality of this architecture is verified using real-time electrooculogram signal. This architecture is useful for saccade identification and blink detection, as well as for recognizing human eye activity while reading. The standard Haar wavelet structure includes an adder, subtracter, and multiplier. The Haar structure is synthesized the use of the Cadence RTL compiler. The synthesis outcomes display that the proposed structure has much less latency and lower power consumption.
ISSN:2662-995X
2661-8907
DOI:10.1007/s42979-021-00553-4