Self-Aware Machine Learning for Chronic Pathology Monitoring on Wearable Devices

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A user’s benefit from the energy stored in a battery over its lifetime depends on the time-varying characteristics of the battery, which are in turn affected by the chosen usage behavior. Both the capacity shrinkage and the number of lifetime cycles are st ...

Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-perfor ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized S ...

In an era where portable electronic devices are indispensable for a wide range of activities, the need for displays that provide both long-lasting battery life and excellent visibility in different lighting conditions is increasingly important. Emissive di ...

Integrating smart algorithms on neural devices presents significant opportunities for various brain disorders. In this paper, we review the latest advancements in the development of three categories of intelligent neural prostheses featuring embedded signa ...

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions ...

This thesis introduces spectroscopy-free Raman biosensing, which may find increasing use in the next generation of wearable devices for preventive healthcare. While wearables have made substantial advancements in detecting physical biomarkers, they have ye ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Systems and apparatus are provided for using a non-invasively monitored uncalibrated pressure signal from a patient to compute cardiac output and other cardio-vascular parameters, thereby providing safe, effective, reliable and low cost monitoring of patie ...

Polymer optical fibre (POFs) based wearable sensors have attracted a lot of attention in the field of healthcare and biomedical applications. They are in particular envision as the next generation of sensors for the continuous, real-time n ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

The terminology of neurological disorders encompasses a range of serious illnesses (e.g., epilepsy, Alzheimer's disease) leading to morbidity, disability, and stigma. Epilepsy alone affects over 50 million people worldwide, and these figures are rising as ...

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all state-of-the-art systems are still built upon th ...

Predictive health assessment is of vital importance for smarter battery management to ensure optimal and safe operations and thus make the most use of battery life. This paper proposes a general framework for battery aging prognostics in order to provide t ...

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

The current study evaluates integrating fuel cell technology into the batteries as an alternative for internal combustion engines (ICEs) for Unmanned Aerial Vehicles (UAV). To further improve the performance of the UAV, a turbocharger is also integrated to ...

Self-Aware Machine Learning for Chronic Pathology Monitoring on Wearable Devices

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