Active upper limb prostheses: A review on current state and upcoming breakthroughs
The journey of a prosthetic user is characterized by the opportunities and the limitations of a
device that should enable activities of daily living (ADL). In particular, experiencing a bionic …
device that should enable activities of daily living (ADL). In particular, experiencing a bionic …
Transformers in biosignal analysis: A review
Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …
Through outstanding performance in natural language processing and superior capability to …
Marsellus: A heterogeneous RISC-V AI-IoT end-node SoC with 2–8 b DNN acceleration and 30%-boost adaptive body biasing
Emerging artificial intelligence-enabled Internet-of-Things (AI-IoT) system-on-chip (SoC) for
augmented reality, personalized healthcare, and nanorobotics need to run many diverse …
augmented reality, personalized healthcare, and nanorobotics need to run many diverse …
Electromyography based decoding of dexterous, in-hand manipulation motions with temporal multichannel vision transformers
Electromyography (EMG) signals have been used in designing muscle-machine interfaces
(MuMIs) for various applications, ranging from entertainment (EMG controlled games) to …
(MuMIs) for various applications, ranging from entertainment (EMG controlled games) to …
Eegformer: Transformer-based epilepsy detection on raw eeg traces for low-channel-count wearable continuous monitoring devices
P Busia, A Cossettini, TM Ingolfsson… - … Circuits and Systems …, 2022 - ieeexplore.ieee.org
The development of a device for long-term and continuous monitoring of epilepsy is a very
challenging objective, due to the high accuracy standards and nearly zero false alarms …
challenging objective, due to the high accuracy standards and nearly zero false alarms …
Plinio: a user-friendly library of gradient-based methods for complexity-aware DNN optimization
Accurate yet efficient Deep Neural Networks (DNNs) are in high demand, especially for
applications that require their execution on constrained edge devices. Finding such DNNs in …
applications that require their execution on constrained edge devices. Finding such DNNs in …
Reducing false alarms in wearable seizure detection with eegformer: A compact transformer model for mcus
P Busia, A Cossettini, TM Ingolfsson… - … Circuits and Systems, 2024 - ieeexplore.ieee.org
The long-term, continuous analysis of electroencephalography (EEG) signals on wearable
devices to automatically detect seizures in epileptic patients is a high-potential application …
devices to automatically detect seizures in epileptic patients is a high-potential application …
Efficient deep learning models for privacy-preserving people counting on low-resolution infrared arrays
Ultralow-resolution infrared (IR) array sensors offer a low cost, energy efficient, and privacy-
preserving solution for people counting, with applications, such as occupancy monitoring …
preserving solution for people counting, with applications, such as occupancy monitoring …
Online transformers with spiking neurons for fast prosthetic hand control
Fast and accurate online processing is essential for smooth prosthetic hand control with
Surface Electromyography signals (sEMG). Although transformers are state-of-the-art deep …
Surface Electromyography signals (sEMG). Although transformers are state-of-the-art deep …
A Long Short-Term Memory-based interconnected architecture for classification of grasp types using surface-Electromyography signals
Reliable classification of grasp types from human limbs has become an important aspect
used by applications with humanoid robotic systems, because of their high-accuracy …
used by applications with humanoid robotic systems, because of their high-accuracy …