Category: health
epiPhone – discretely monitoring brain activity
We are proud to present epiPhone, a discreet headset which can monitor brain activity and transmit the data in real time. Today, epilepsy is one of the most common chronic diseases affecting more than 65 million people worldwide. However, no reliable wearable device currently exists for real-time epileptic seizure detection. One of the main challenges (…)
Sensemodi and Nespresso challenge presented at Engineering Industry Day
Jérôme Thevenot, Matteo Feo and David Atienza participated in the EPFL Engineering Industry Day at the SwissTech on Thursday, 8th March. Jérôme presented ESL spin-off Sensemodi, featuring an in-motion, knee diagnosis platform. David and Matteo presented the Nespresso challenge, where ESL addressed the need to use Machine Learning enabled Artificial Intelligence to identify coffee capsules (…)
Understanding tech will shape the sports leaders of tomorrow
ESL has been featured by Sport Business The opportunities afforded by cutting-edge technology in sport have filtered into all aspects of the industry in recent years, from broadcasting to fan experience and athlete training. Such a trend has been highlighted by AISTS’s decision to redesign its flagship Master of Advanced Studies (MAS) in Sport Management (…)
The nervous system as an IoT: David Atienza on brain-inspired healthcare wearables
CHF 150,000 for smart wearables invented in Switzerland
EPFL spin-off Sensemodi, focusing on monitoring joint health, wins the final stage of Venture Kick. Congratulations to the team of founders Tomás Teijeiro Campo, Jerome Thevenot, and David Atienza! Sensemodi is developing a smart wearable device that can analyse thermal, acoustic and kinematic data for fast joint health assessment at any Point of Care. The (…)
DIGIPREDICT — Digital Twins for predicting disease progression and need for early intervention
Best student paper award for Lara Orlandic
Lara Orlandic received a Best student paper award at the 34th IEEE CBMS International Symposium on Computer-Based Medical Systems. The paper is a study of how a person’s perception of the passage of time can be monitored and assessed, as a continuous evaluation of their mental health. Co-authors on the paper were Prof. (…)
Full Presentation: Self-aware anomaly detection for epilepsy monitoring
Farnaz Forooghifar presents our research on self-aware anomaly detection for epilepsy monitoring on low-power, wearable electrocardiographic devices.
Coughvid on Al Arabiya
Tomas Teijeiro is interviewed by Al Arabiya news about the Coughvid, in its last stages of testing. Subtitles provided by Halima Najibi (click on CC)
Digipredict digital twin will predict the evolution of Covid-19
Under a cross-disciplinary program spearheaded by EPFL, scientists will develop an AI-based system that can predict whether Covid-19 patients will develop severe cardiovascular complications and, in the longer term, detect the likely onset of inflammatory disease. Covid-19 comes with a range of symptoms – from a sore throat and the loss of taste to more (…)