相关论文: BioGAP-Ultra: A Modular Edge-AI Platform for Weara…
Biological signals, such as electroencephalograms (EEG), play a crucial role in numerous clinical applications, exhibiting diverse data formats and quality profiles. Current deep learning models for biosignals are typically specialized for…
Fifth-generation (5G) cellular networks promise higher data rates, lower latency, and large numbers of interconnected devices. Thereby, 5G will provide important steps towards unlocking the full potential of the Internet of Things (IoT). In…
Pulse wave analysis is an important method used to gather information about the cardiovascular system. Instead of detecting the pulse wave via pressure sensors, bioimpedance measurements can be performed to acquire minuscule changes in the…
Meeting the escalating demands of data transmission and computing, driven by artificial intelligence (AI), requires not only faster optical transceivers but also advanced integration technologies that can seamlessly combine photonic and…
This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals,…
Background: The rise of mobile technology and health apps has increased the use of person-generated health data (PGHD). PGHD holds significant potential for clinical decision-making but remains challenging to manage. Objective: This study…
Wearable edge AI biomedical devices are increasingly being used for continuous patient health monitoring, enabling real-time insights and extended data collection without the need for prolonged hospital stays. These devices must be energy…
Biomedical imaging is unequivocally dependent on the ability to reconstruct interpretable and high-quality images from acquired sensor data. This reconstruction process is pivotal across many applications, spanning from magnetic resonance…
Gait recognition is an emerging biometric technology that enables non-intrusive and hard-to-spoof human identification. However, most existing methods are confined to short-range, unimodal settings and fail to generalize to long-range and…
Understanding the interaction of neural and cardiac systems during cognitive activity is critical to advancing physiological computing. Although EEG has been the gold standard for assessing mental workload, its limited portability restricts…
Heart rate (HR) estimation from photoplethysmography (PPG) signals is a key feature of modern wearable devices for health and wellness monitoring. While deep learning models show promise, their performance relies on the availability of…
Wearable exoskeletons hold transformative promise for restoring mobility across diverse users with muscular weakness or other impairments. However, their translation beyond laboratory environments remains limited by sensing systems that…
With the rapid development of artificial intelligence technology, its application in the optimization of complex computer systems is becoming more and more extensive. Edge computing is an efficient distributed computing architecture, and…
A brain--machine interface (BMI) based on motor imagery (MI) enables the control of devices using brain signals while the subject imagines performing a movement. It plays a vital role in prosthesis control and motor rehabilitation. To…
This paper describes a highly integrated, low power chip solution for ECG signal processing in wearable devices. The chip contains an instrumentation amplifier with programmable gain, a band-pass filter, a 12-bit SAR ADC, a novel QRS…
Despite the recent advancements in human-machine interfacing, contemporary assistive bionic limbs face critical challenges, including limited computational capabilities, high latency, and unintuitive control mechanisms, leading to…
This work presents the design and implementation of a wireless, wearable system that combines surface electromyography (sEMG) and inertial measurement units (IMUs) to analyze a single lower-limb functional task: the free bodyweight squat in…
Biomonitoring wearable sensors based on two-dimensional nanomaterials have lately elicited keen research interest and potential for a new range of flexible nanoelectronic devices. Practical nanomaterial-based devices suited for real-world…
Rapid advancements in collection and dissemination of multi-platform molecular and genomics data has resulted in enormous opportunities to aggregate such data in order to understand, prevent, and treat human diseases. While significant…
Photoplethysmography (PPG) is a widely adopted, non-invasive technique for monitoring cardiovascular health and physiological parameters in both consumer and clinical settings. While motion artifacts in dynamic environments have been…