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Generic vs custom; analogue vs digital: on the implementation of an online EEG signal processing algorithm
Alexander J Casson1, Esther Rodriguez-Villegas
1Department of Electrical and Electronic Engineering, Imperial College London, SW7 2AZ, UK. acasson@imperial.ac.uk
Summary
This study compares custom and generic hardware for Body Area Network signal processing. Analogue signal processing offers a promising solution for enhancing power performance in these critical applications.
Area of Science:
- Biomedical Engineering
- Computer Engineering
- Signal Processing
Background:
- Body Area Networks (BANs) are crucial for remote health monitoring.
- Efficient signal processing is essential for BAN performance.
- Hardware implementation choices significantly impact BAN capabilities.
Purpose of the Study:
- To quantify performance differences between custom and generic hardware for BAN signal processing.
- To highlight implementation challenges in BANs.
- To explore analogue signal processing for power efficiency.
Main Methods:
- Comparative analysis of custom vs. generic hardware.
- Performance evaluation of algorithm implementations.
- Demonstration of analogue signal processing techniques.
Main Results:
- Significant performance variations exist between custom and generic hardware.
- Specific challenges identified in BAN signal processing implementations.
- Analogue signal processing shows potential for improved power efficiency.
Conclusions:
- Hardware selection critically affects BAN performance.
- Addressing implementation challenges is key for BAN advancement.
- Analogue signal processing presents a viable path for power-optimized BANs.
