Mahsa Shoaran

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Related publications (53)

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An application-based taxonomy for brain–computer interfaces

José del Rocio Millán Ruiz, Mahsa Shoaran, Nicolas Vachicouras

The term 'brain-computer interface' (BCI) is widely used. However, even among experts, its meaning can sometimes be unclear 1-3. Lack of clarity from the term has real-world implications: it can muddle regulatory guidelines, it may confuse investors, it ca ...

Springer Science and Business Media LLC2024

A 0.21-ps FOM Capacitor-Less Analog LDO with Dual-Range Load Current for Biomedical Applications

Yasemin Engür, Mahsa Shoaran

This paper presents an output capacitor-less low-dropout regulator (LDO) with a bias switching scheme for biomedical applications with dual-range load currents. Power optimization is crucial for systems with multiple activation modes such as neural interfa ...

ArXiv2023

Structured Sampling and Recovery of iEEG Signals

Yusuf Leblebici, Volkan Cevher, Mahsa Shoaran, Cosimo Aprile, Luca Baldassarre

Wireless implantable devices capable of monitoring the electrical activity of the brain are becoming an important tool for understanding, and potentially treating, mental diseases such as epilepsy and depression. Compressive sensing (CS) is emerging as a p ...

2015

Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques

Mahsa Shoaran, Bingzhao Zhu

Objective. Accurate decoding of individual finger movements is crucial for advanced prosthetic control. In this work, we introduce the use of Riemannian-space features and temporal dynamics of electrocorticography (ECoG) signal combined with modern machine ...

IOP Publishing Ltd2022

A 49.8-mm 2 IR-UWB Transmitter With Co-Designed Power Amplifier and Antenna for Neural Implants With Extended Transmission Range

Anja Skrivervik, Mahsa Shoaran, Mingxiang Gao, Cong Ding

This work presents an implantable impulse-radio ultrawideband transmitter (IR-UWB TX) optimized for high-density neural recording. To address the tradeoffs between data rate, transmission range, implant size, and power consumption, we propose a novel co-de ...

Institute of Electrical and Electronics Engineers (IEEE)2025

Tutorial: Intelligent Neural Interfaces: Fundamentals and Future Directions

Mahsa Shoaran

In the past decade, there has been growing interest in developing AI-enabled neural interfaces for various neurological disorders and emerging brain-machine interface (BMI) applications. The focus has shifted from raw signal acquisition and data compressio ...

IEEE2025

An 8.7 mu J/class. FFT accelerator and DNN-based configurable SoC for Multi-Class Chronic Neurological Disorder Detection

Mahsa Shoaran, Bingzhao Zhu

IEEE2021

Editorial overview: Tissue, cell and pathway engineering: bioinspired, biomimetic and hybrid neural interfaces

Stéphanie Lacour, Mahsa Shoaran

CURRENT BIOLOGY LTD2021

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

Mahsa Shoaran, Bingzhao Zhu, Uisub Shin

A closed-loop neuromodulation system, including an electrode array that is implantable to a brain of a subject, analog front-end device (AFD) for selectively selecting and reading a plurality of channels from electrode array, a finite impulse response (FIR ...

2023

Next-Generation Closed-Loop Neural Interfaces: Circuit and AI-driven innovations

Mahsa Shoaran

Next-Generation Closed-Loop Neural Interfaces: Circuit and AI-driven innovations ...

IEEE Solid-State Circuits Magazine ( Volume: 15, Issue: 4, Fall 2023)2023

A 32-Channel 196-μW Logarithmic SoC for Brain Network Connectivity Extraction and Adaptive Psychiatric Symptom Classification

Mahsa Shoaran, Uisub Shin, Jinhan Liu, Amitabh Yadav, Arshia Afzal

This paper presents a 32-channel brain-computer interface SoC for closed-loop deep-brain stimulation in psychiatric disorders. The SoC integrates a 32-channel analog front-end, an efficient logarithmic feature extraction engine, a neural additive model cla ...

IEEE2025

Compact low-power recording architecture for multichannel acquisition of biological signals and method for compressing said biological signal data

Alexandre Schmid, Mahsa Shoaran, Mahdad Hosseini Kamal

The present invention relates to a method for compressing signal data of a plurality of biological signals captured by a plurality of implanted measurement devices. The present invention further relates to an implantable sensor configured to carry out said ...

2016

In-Vivo Validation of a Compact Inductively-Powered Neural Recording Interface

Alexandre Schmid, Catherine Dehollain, Mahsa Shoaran, Gürkan Yilmaz

2014