Publications de Mahsa Shoaran | EPFL Graph Search

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

Integrating Neural Interfaces with Machine Learning: Enabling Self-Sufficient and Ubiquitous Prosthetic and Diagnostic Devices

Mahsa Shoaran, Mohammad Ali Shaeri

Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integratin ...

IEEE2025

Machine-Learning-Powered Neural Interfaces for Smart Prosthetics and Diagnostics

Mahsa Shoaran, Mohammad Ali Shaeri

Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integratin ...

Institute of Electrical and Electronics Engineers2025

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

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

Mahsa Shoaran, Amitabh Yadav, Uisub Shin, 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 ...

2025

A Hardware-Efficient EMG Decoder with an Attractor-based Neural Network for Next-Generation Hand Prostheses

Solaiman Shokur, Mahsa Shoaran, Silvestro Micera, Vincent Alexandre Mendez, Mohammad Ali Shaeri

Advancements in neural engineering have enabled the development of Robotic Prosthetic Hands (RPHs) aimed at restoring hand functionality. Current commercial RPHs offer limited control through basic on/off commands. Recent progresses in machine learning ena ...

IEEE2024

Intelligent Neural Interfaces: An Emerging Era in Neurotechnology

Mahsa Shoaran, Uisub Shin, Mohammad Ali Shaeri

Over the past decade, there has been a growing interest in the development of intelligent neural interface systems-on-chip (SoCs) for a range of neurological disorders and emerging brain-machine interface (BMI) applications. The shift toward creating intel ...

IEEE2024

Intelligent Neural Interfaces: An Emerging Era in Neurotechnology

Mahsa Shoaran, Uisub Shin, Mohammad Ali Shaeri

Integrating smart algorithms on neural devices presents significant opportunities for various brain disorders. In this paper, we review the latest advancements in the development of three categories of intelligent neural prostheses featuring embedded signa ...

2024 IEEE Custom Integrated Circuits Conference (CICC)2024

An application-based taxonomy for brain–computer interfaces

José del Rocio Millán Ruiz, Nicolas Vachicouras, Mahsa Shoaran

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 Systematic Design Flow for Compact and Efficient Analog Front-Ends in Closed-Loop Neuromodulation Systems

Mahsa Shoaran

In the growing field of closed-loop neuromodulation, designing power-and area-efficient analog front-ends (AFEs) for neural recording poses a significant challenge. Thus, an effective design flow is needed to ensure system's hardware efficiency and to auto ...

IEEE2024

A 2.46-mm2 Miniaturized Brain-Machine Interface (MiBMI) Enabling 31-Class Brain-to-Text Decoding

Mahsa Shoaran, Amitabh Yadav, Uisub Shin, Mohammad Ali Shaeri

Recent advancements in brain-machine interface (BMI) technology offer groundbreaking solutions for individuals with motor impairments, potentially extending to speech synthesis and handwriting assistance. However, current BMIs rely on cumbersome benchtop s ...

2024

REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates

Volkan Cevher, Mahsa Shoaran, Grigorios Chrysos, Arshia Afzal

EEG-based seizure detection models face challenges in terms of inference speed and memory efficiency, limiting their real-time implementation in clinical devices. This paper introduces a novel graph-based residual state update mechanism (REST) for real-tim ...

2024

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Gregor Rainer, Mahsa Shoaran, Amitabh Yadav, Uisub Shin, Mohammad Ali Shaeri

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

IEEE2024

Neural decoding and feature selection methods for closed-loop control of avoidance behavior

Mahsa Shoaran

Objective. Many psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local fi ...

IOP Publishing2024

A 3 mm2, Energy-Efficient, Multi-Data-Rate, FDMA Transmitter with On-Chip Antenna for Next-Generation Neural Implants

Anja Skrivervik, Mahsa Shoaran, Mingxiang Gao, Cong Ding

This paper presents a versatile energy-efficient wireless transmitter (TX) for neural implants with high/ultrahigh channel counts. The TX supports a wide range of data transmission rates, from 50Mb/s to 1.2 Gb/s, through a novel dual-modulation approach. O ...

IEEE2024

A 49.8mm2 Fully Integrated, 1.5m Transmission-Range, High-Data-Rate IR-UWB Transmitter for Brain Implants

Anja Skrivervik, Mahsa Shoaran, Mingxiang Gao, Cong Ding

Implantable neural interfaces hold great potential to restore function in individuals impaired by paralysis, limb amputations, or various neurological conditions. The need for precise mapping of neuronal activity across various brain regions and enhancing ...

IEEE2024

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

Mahsa Shoaran, Uisub Shin, Bingzhao Zhu

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

Enhancing Epileptic Seizure Detection with EEG Feature Embeddings

Mahsa Shoaran, Bingzhao Zhu, Arman Zarei

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering neurostimulation to r ...

ArXiv2023

From basic sciences and engineering to epileptology: A translational approach

Mahsa Shoaran

Collaborative efforts between basic scientists, engineers, and clinicians are enabling translational epileptology. In this article, we summarize the recent advances presented at the International Conference for Technology and Analysis of Seizures (ICTALS 2 ...

WILEY2023