EEG for early detection of ASD in infants. Early diagnosis of autism spectrum disorders (ASD) is crucial for effective intervention. Studies show that newborns with ASD have noticeably different preferences for certain social stimuli. An EEG-based index of face processing could be used as a biomarker for prediction, but its measure requires the infant's EEG to be recorded in laboratory settings.
You are here
WBAN and Wearables for Health, Sports and Wellbeing
"De kracht van het onbewuste leren 2.0" - "The Power of Implicit Motor Learning 2.0" is a RAAK PRO project funded by SIA (Netherlands). Its objective is to improve gait and walking abilities in people with cognitive impairments after stroke by using implicit motor learning strategies and innovative technologies.
E3DA cooperates with Motorialab on its work to make sport more safe and entertaining by adding wearable technologies and sensors to equipment and to the end-user. E3DA works having in mind energy efficiency to ease technology mantainance in terms of lifetime, but also we help Motorialab in make technology smarter and smarter and capable to connect wirelessly to any device. Using Motorialab platform we connect wearable/sensor to mobile devices to achieve apps and collect data on user behavior, performance, etc.
A generic platform for movement tracking analysis will be developed which supports a range of stationary and mobile/wearable sensors and serves as a base technology for third party providers to create tailored solutions upon. The platform will provide functionality such as data collection, feedback delivery, data analysis, and publish APIs for sensors and actuators to connect to it.
From 2014 E3DA cooperates with CoRehab Srl to optimize and enrich their products. We are transferring our expertise in inertial sensing, motion tracking and rehabilitation to the company. At the same time the use of the advanced technologies developed at CoRehab are increasing our knowledge in functional assessment in sport and recovery from injuries.
This project focuses on the challenges of natural interaction modalities for EMG-powered hand prosthesis. In particular, we are invetigating on an implementation suitable for an embedded system, based on Support Vector Machine (SVM). The work falls within a cooperation with INAIL, Prosthetic center in Vigorso (Budrio, BO, Italy), one of the main prosthetic centres in Europe.