42 citations · 53 across the 21 of their papers we have counts for
5 papers · 2 filters
Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces
Lan Mei, Cristian Cioflan, Thorir Mar Ingolfsson +4
Brain-machine interfaces (BMIs) are expanding beyond clinical settings thanks to advances in hardware and algorithms. However, they still face challenges in user-friendliness and s…
An Ultra-Low Power Wearable BMI System with Continual Learning Capabilities
Lan Mei, Thorir Mar Ingolfsson, Cristian Cioflan +4
Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Brain-Machine Interfaces (BMIs)…
GAPses: Versatile smart glasses for comfortable and fully-dry acquisition and parallel ultra-low-power processing of EEG and EOG
Sebastian Frey, Mattia Alberto Lucchini, Victor Kartsch +7
Recent advancements in head-mounted wearable technology are revolutionizing the field of biopotential measurement, but the integration of these technologies into practical, user-fr…
A Spiking Neural Network Decoder for Implantable Brain Machine Interfaces and its Sparsity-aware Deployment on RISC-V Microcontrollers
Jiawei Liao, Oscar Toomey, Xiaying Wang +4
Implantable Brain-machine interfaces (BMIs) are promising for motor rehabilitation and mobility augmentation, and they demand accurate and energy-efficient algorithms. In this pape…
SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms
Jonathan Dan, Una Pale, Alireza Amirshahi +9
The need for high-quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long-ter…