Publications by Mohammad Ali Shaeri

Real-time, Neural Signal Processing for High-density Brain-implantable Devices

Recent advances in the development of intra-cortical neural interfacing devices show the bright horizon of having access to brain-implantable microsystems with extremely high channel counts in the not-so-distant future. With the fabrication of high-density ...

SPRINGERNATURE2025

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

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

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

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

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Mohammad Ali Shaeri

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

2023

Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs

Mahsa Shoaran, Mohammad Ali Shaeri, Arshia Afzal

Neuroscience and neurotechnology are currently being revolutionized by artificial intelligence (AI) and machine learning. AI is widely used to study and interpret neural signals (analytical applications), assist people with disabilities (prosthetic applica ...

IEEE2022

An Accurate and Hardware-Efficient Dual Spike Detector for Implantable Neural Interfaces

Mahsa Shoaran, Mohammad Ali Shaeri

Spike detection plays a central role in neural data processing and brain-machine interfaces (BMIs). A challenge for future-generation implantable BMIs is to build a spike detector that features both low hardware cost and high performance. In this work, we ...

IEEE2022