Related Experiment Video
Updated: May 28, 2026
07:02
Investigating the Potential of Singly Curved Thin Piezoelectric Transducers for Energy Harvesting and Structural Health Monitoring
Published on: November 14, 2025
Dynamical and Stochastic Analysis of a Piezoelectric Neuron Model for Intelligent Sensing Applications.
Atef Abdelkader1, Haiqa Ehsan2,3, Adil Jhangeer2,4,5
1College of Humanities and Sciences, Ajman University, Ajman P.O. Box 346, United Arab Emirates.
Sensors (Basel, Switzerland)
|May 27, 2026
Summary
This study explores a piezoelectric neuron model for sensing applications. The model exhibits nonlinear sensitivity and altered firing patterns under deterministic and stochastic conditions, crucial for neuromorphic sensor design.
Area of Science:
- Neuroscience
- Materials Science
- Physics
Background:
- Piezoelectric neuron models are essential for developing advanced sensing systems.
- Understanding their behavior under various perturbations is key for neuromorphic engineering.
Purpose of the Study:
- To investigate the dynamics of a piezoelectric neuron model under deterministic perturbations and stochastic forcing.
- To assess its suitability for mechanically driven sensing and neuromorphic sensor design.
Main Methods:
- Phase-space reconstruction, basin of attraction mapping, return map analysis, and sensitivity analysis for deterministic dynamics.
- Euler-Maruyama scheme for numerical simulation of stochastic forcing.
- Time-series statistics, phase portraits, and recurrence quantification analysis for ensemble dynamics.
Main Results:
- The model displays stable limit-cycle oscillations and high nonlinear sensitivity, beneficial for high-resolution sensing.
- Stochastic forcing introduces variability and reduces predictability, altering firing patterns and recurrence structures.
- Noise intensity significantly impacts the model's dynamic behavior and signal processing capabilities.
Conclusions:
- The piezoelectric neuron model demonstrates potential for high-resolution sensing and signal amplification due to its nonlinear properties.
- Noise effects must be carefully considered in designing neuromorphic sensors based on this model.
- The study provides insights into the complex interplay between deterministic dynamics and stochastic influences in excitable systems.
