Mount Sinai Researchers Develop Machine Learning Model that Can Detect and Predict COVID-19 from Collected Data on Wearable Devices

Mount Sinai researchers have developed a machine learning algorithm that can determine if an individual has SARS-CoV-2 infections, the virus that causes COVID-19—with a high sensitivity and specificity—from the data collected by wearable devices.

Mount Sinai Researchers Use Wearable Devices to Identify Psychological Effects of Pandemic

Study links changes in heart rate variability with degree of resilience, as part of larger effort to understand and mitigate the effects of COVID-19 on health care workers

NUS engineers devise novel approach to wirelessly power multiple wearable devices using a single source

Researchers from NUS have come up with a way to use one single device – such as a mobile phone or smart watch – to wirelessly power up to 10 wearables on a user. This novel method uses the human body as a medium for transmitting power. Their system can also harvest unused energy from electronics in a typical home or office environment to power the wearables.

How to Make All Headphones Intelligent

How do you turn “dumb” headphones into smart ones? Rutgers engineers have invented a cheap and easy way by transforming headphones into sensors that can be plugged into smartphones, identify their users, monitor their heart rates and perform other services. Their invention, called HeadFi, is based on a small plug-in headphone adapter that turns a regular headphone into a sensing device. Unlike smart headphones, regular headphones lack sensors. HeadFi would allow users to avoid having to buy a new pair of smart headphones with embedded sensors to enjoy sensing features.

Mount Sinai Study Finds Wearable Devices Can Detect COVID-19 Symptoms and Predict Diagnosis

Wearable devices can identify COVID-19 cases earlier than traditional diagnostic methods and can help track and improve management of the disease, according to a Mount Sinai study.

Battery life for wearable electronic devices could be improved with design considerations to stress asymmetry clues in cylindrical battery cell formats

Researchers in WMG and the Department of Physics at the University of Warwick have found that asymmetric stresses within electrodes used in certain wearable electronic devices provides an important clue as to how to improve the durability and lifespan of these batteries.

Critical Transition Theory Shows Flickering in Heart Before Atrial Fibrillation

Atrial fibrillation ranks among the most common heart conditions, and episodes are difficult to predict. Researchers have proposed a way to define cardiac state and have studied the dynamics before the cardiac rhythm changes from normal sinus to AF rhythm and vice versa. The work, appearing in Chaos and based on critical transition theory, looks to provide an early warning for those with paroxysmal atrial fibrillation with potential implications for future wearable devices.