Validation of a New Ankle Brachial Index Measurement System Using Pulse Wave Velocity.

Peripheral artery disease (PAD) is a common circulatory disorder characterized by the accumulation of fats, cholesterol, and other substances in the arteries that restrict blood flow to the extremities, especially the legs. The ankle brachial index (ABI) is a highly reliable and valid non-invasive test for diagnosing PAD. However, the traditional method has limitations.

Augmented Reality Holographic Visualization System for Surgery Auxiliary Visualization: Proof of Concept for Surgical Training.

An Augmented Reality (AR) system based on the holographic projection of the relevant anatomic structures is proposed for auxiliary visualization during surgeries. The current two-dimensional visualization systems require the surgeons to mentally extract the associated three-dimensional information during the interventions, which entails risks and complications. This work shows an AR holographic projection system for real-time three-dimensional representation of the relevant surgical information, thus overcoming this problem.

Enhancing surgeons' gaze strategies in endoscopic surgery during simulated surgical emergency situations thanks to computer vision.

Deficient visualization in minimally invasive surgery often causes misperceptions, which can lead to an increase of iatrogenic lesions and complications. This is especially critical for novice surgeons, who are prone to adopt inadequate switching gaze strategies, thereby increasing the chance of unforeseen complications. In this paper the use of an additional computer-aided vision system was tested for improvement of the reaction of the surgeons to unforeseen complications.

Wearable Epileptic Seizure Prediction System Based on Machine Learning Techniques Using ECG, PPG and EEG Signals.

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 patients' health status and warn them for a possible epileptic seizure would improve their quality of life. With this aim, this article proposes the first seizure predictive model based on Ear EEG, ECG and PPG signals obtained by means of a device that can be used in a static and outpatient setting.