Publications by 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, Uisub Shin, 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 ...

2025

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

Silvestro Micera, Mahsa Shoaran, Solaiman Shokur, 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, 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 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