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[HTML][HTML] Energy-efficient deep neural networks for EEG signal noise reduction in next-generation green wireless networks and industrial IoT applications
Wireless electroencephalography (EEG) has emerged as a critical interface between human
cognitive processes and machine learning technologies in the burgeoning field of sensor …
cognitive processes and machine learning technologies in the burgeoning field of sensor …
BrainFuseNet: Enhancing Wearable Seizure Detection through EEG-PPG-accelerometer Sensor Fusion and Efficient Edge Deployment
This paper introduces BrainFuseNet, a novel lightweight seizure detection network based on
the sensor fusion of electroencephalography (EEG) with photoplethysmography (PPG) and …
the sensor fusion of electroencephalography (EEG) with photoplethysmography (PPG) and …
GAPses: Versatile smart glasses for comfortable and fully-dry acquisition and parallel ultra-low-power processing of EEG and EOG
Recent advancements in head-mounted wearable technology are revolutionizing the field of
biopotential measurement, but the integration of these technologies into practical, user …
biopotential measurement, but the integration of these technologies into practical, user …
An adaptive dynamic mixing model for sEMG real-time ICA on an ultra-low power processor
Blind Source Separation (BSS) has shown promise in enhancing the interpretability and
usability of surface electromyography (sEMG) signals for Human-Machine Interfaces (HMIs) …
usability of surface electromyography (sEMG) signals for Human-Machine Interfaces (HMIs) …
Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables
In wearable sensors, energy efficiency is crucial, particularly during phases where devices
are not processing, but rather acquiring biosignals for subsequent analysis. This study …
are not processing, but rather acquiring biosignals for subsequent analysis. This study …
A muscle pennation angle estimation framework from raw ultrasound data for wearable biomedical instrumentation
Measurement of muscle activity via wearable instrumentation is of great interest for medical
and sport science applications: examples include the control of prostheses, robotics, or …
and sport science applications: examples include the control of prostheses, robotics, or …
An Ultra-Low Power Wearable BMI System with Continual Learning Capabilities
Driven by the progress in efficient embedded processing, there is an accelerating trend
toward running machine learning models directly on wearable Brain-Machine Interfaces …
toward running machine learning models directly on wearable Brain-Machine Interfaces …
A wearable ultra-low-power semg-triggered ultrasound system for long-term muscle activity monitoring
Surface electromyography (sEMG) is a well-established approach to monitor muscular
activity on wearable and resource-constrained devices. However, when measuring deeper …
activity on wearable and resource-constrained devices. However, when measuring deeper …
Real-Time Motor Unit Tracking from sEMG Signals with Adaptive ICA on a Parallel Ultra-Low Power Processor
Spike extraction by blind source separation (BSS) algorithms can successfully extract
physiologically meaningful information from the sEMG signal, as they are able to identify …
physiologically meaningful information from the sEMG signal, as they are able to identify …
Wearable, Real-time Drowsiness Detection based on EEG-PPG Sensor Fusion at the Edge
Drowsiness and fatigue pose significant risks across various industries, causing 15-20% of
severe road crashes in the driving industry alone. Wearable devices are a promising …
severe road crashes in the driving industry alone. Wearable devices are a promising …