Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review

Area of Science:

• Neuroscience
• Computer Engineering
• Signal Processing

Background:

• The nervous system efficiently processes sensory information using event-based mechanisms.
• Traditional sensing relies on periodic sampling, which is less efficient than event-driven methods.
• Neuromorphic engineering seeks to replicate the brain's efficient information processing in artificial systems.

Purpose of the Study:

• To highlight the advantages and challenges of event-based sensing and signal processing.
• To provide a comprehensive literature survey of neuromorphic sensing across visual, auditory, and olfactory domains.
• To facilitate future research by outlining conceptual benefits, progress, and challenges.

Main Methods:

• Literature review of neuromorphic sensing and signal processing.
• Analysis of event-driven sensing principles.
• Comparative study of traditional vs. event-based sampling.

Main Results:

• Event-based sensing offers advantages over periodic sampling by responding to stimulus changes.
• Significant research exists in neuromorphic sensing for visual, auditory, and olfactory modalities.
• Key challenges include hardware implementation and algorithm development for event-based systems.

Conclusions:

• Neuromorphic sensing, mimicking neural processing, offers a more efficient paradigm for signal processing.
• Event-based approaches are promising for visual, auditory, and olfactory sensing applications.
• Further research is needed to overcome current challenges and fully realize the potential of neuromorphic sensing.