End-to-end design of wearable sensors
Wearable devices provide an alternative pathway to clinical diagnostics by exploiting
various physical, chemical and biological sensors to mine physiological (biophysical and/or …
various physical, chemical and biological sensors to mine physiological (biophysical and/or …
Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities
Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …
ageing global population to the current COVID-19 pandemic. In a world where we have …
Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by
infrequent seizures based on patient or caregiver reports and limited duration clinical …
infrequent seizures based on patient or caregiver reports and limited duration clinical …
Data quality evaluation in wearable monitoring
Wearable recordings of neurophysiological signals captured from the wrist offer enormous
potential for seizure monitoring. Yet, data quality remains one of the most challenging factors …
potential for seizure monitoring. Yet, data quality remains one of the most challenging factors …
Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning
The ability to forecast seizures minutes to hours in advance of an event has been verified
using invasive EEG devices, but has not been previously demonstrated using noninvasive …
using invasive EEG devices, but has not been previously demonstrated using noninvasive …
Automated seizure detection with noninvasive wearable devices: a systematic review and meta‐analysis
Objective This study was undertaken to review the reported performance of noninvasive
wearable devices in detecting epileptic seizures and psychogenic nonepileptic seizures …
wearable devices in detecting epileptic seizures and psychogenic nonepileptic seizures …
Transfer learning for non-image data in clinical research: a scoping review
A Ebbehoj, MØ Thunbo, OE Andersen… - PLOS Digital …, 2022 - journals.plos.org
Background Transfer learning is a form of machine learning where a pre-trained model
trained on a specific task is reused as a starting point and tailored to another task in a …
trained on a specific task is reused as a starting point and tailored to another task in a …
[HTML][HTML] Recent advancements in machine learning enabled portable and wearable biosensors
Recent advances in noninvasive portable and wearable biosensors have attracted
significant attention due to their capability to offer continual physiological information for …
significant attention due to their capability to offer continual physiological information for …
Wearable epileptic seizure Prediction System based on machine learning techniques using ECG, PPG and EEG signals
D Zambrana-Vinaroz, JM Vicente-Samper… - Sensors, 2022 - mdpi.com
Epileptic seizures have a great impact on the quality of life of people who suffer from them
and further limit their independence. For this reason, a device that would be able to monitor …
and further limit their independence. For this reason, a device that would be able to monitor …
Artificial intelligence‐enhanced epileptic seizure detection by wearables
Objective Wrist‐or ankle‐worn devices are less intrusive than the widely used
electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom …
electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom …