Prostheses provide a means for individuals with amputations to regain some of the lost
functions of their amputated limb. Human-machine interfaces (HMIs), used for controlling …

Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to
unlock an entirely new class of smart applications. However, continued progress is limited …

Deep learning has achieved great success in the past few years. However, the performance
of deep learning is likely to impede in face of non-IID situations. Domain generalization (DG) …

Abstract Recently, Convolutional Neural Networks (CNNs) have been used for the
classification of hand activities from surface Electromyography (sEMG) signals. However …

Time series anomaly detection plays a critical role in automated monitoring systems. Most
previous deep learning efforts related to time series anomaly detection were based on …

This article presents a rehabilitation technique based on a lower-limb exoskeleton
integrated with a human–machine interface (HMI). HMI is used to record and process …

Biosignal-based technology has been increasingly available in our daily life, being a critical
information source. Wearable biosensors have been widely applied in, among others …

In practice, it is very challenging and sometimes impossible to collect datasets of labelled
data large enough to successfully train a machine learning model, and one possible solution …

Time series remains one of the most challenging modalities in machine learning research.
Out-of-distribution (OOD) detection and generalization on time series often face difficulties …

Over the last few years, there has been significant growth in neurological diseases which
drastically affect a person's ability to perform everyday tasks, reducing their overall well …