Low-cost, microcontroller-based, two-channel piezoelectric bender device for somatosensory experiments

Yan, Lucy; Hallum, Luke E.

doi:10.1109/embc44109.2020.9176218

Cited by 1 publication

(1 citation statement)

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“…Its versatility, affordability, and userfriendly nature make it an accessible tool for scientists, researchers, and students interested in exploring various aspects of neuroscience. Arduino's contributions to neuroscience span a range of applications, from building experimental setups to creating innovative solutions to study and understand the complexities of the nervous system [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Open Hardware Implementation of Real-Time Phase and Amplitude Estimation for Neurophysiologic Signals

Ochoa,

Gonzalez-Burgos,

Nicolás

et al. 2023

Bioengineering

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Adaptive deep brain stimulation (aDBS) is a promising concept in the field of DBS that consists of delivering electrical stimulation in response to specific events. Dynamic adaptivity arises when stimulation targets dynamically changing states, which often calls for a reliable and fast causal estimation of the phase and amplitude of the signals. Here, we present an open-hardware implementation that exploits the concepts of resonators and Hilbert filters embedded in an open-hardware platform. To emulate real-world scenarios, we built a hardware setup that included a system to replay and process different types of physiological signals and test the accuracy of the instantaneous phase and amplitude estimates. The results show that the system can provide a precise and reliable estimation of the phase even in the challenging scenario of dealing with high-frequency oscillations (~250 Hz) in real-time. The framework might be adopted in neuromodulation studies to quickly test biomarkers in clinical and preclinical settings, supporting the advancement of aDBS.

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Section: Introductionmentioning

confidence: 99%