Is this year's keynote speaker.
Vocational Safety and Well Being: Monitoring Worker Fatigue with Wearable Devices and Sensors
Automation, robotics and sensor technologies are rapidly changing the vocational monitoring, training and assessment practices involving work safety in manufacturing, transportation, healthcare and other industries. In particular, the combination of wearable devices, sensors and the application of advanced machine learning, provide new capabilities for objective and continuous monitoring to predict and prevent accidents and injuries in the workplace, thus revolutionizing the market by offering solutions aimed at increasing worker safety and productivity.
Cognitive assessment is especially important when dealing with automated workplace settings, where a worker has to remain attentive for long periods of time, maintain productivity despite high cognitive load, have the flexibility to switch tasks/materials on demand, and rely on good working memory to avoid mishaps. Cognitive fatigue, which is related but different from physical fatigue, is an invisible safety risk in numerous occupational domains and, if undetected and untreated, it can cause injuries, accidents and even death. In this talk, we describe ongoing work involving the design and implementation of an intelligent human multi-sensing system, called CogBeacon, that detects, monitors and manages cognitive fatigue during an individual’s daily life work activities, in real time. CogBeacon works by recognizing significant changes and performance variations while the user is engaged in structured (task-based) or unstructured daily activities. This is a joint project between U. Texas Arlington and the Kessler Foundation. It combines expertise in neurocognitive science and computer science and uses behavioral user studies and brain imaging studies to train and develop this human-centric work-safety system.
Fillia Makedon's website
Is this year's keynote speaker.
Digital Cognitive Tests - From Idea to Startup & Medical Product
Apart from individual suffering, dementia, or in general neurodegenerative diseases are the most expensive health issue in the world today, larger than cardiovascular diseases and cancer together. The demand for early detection and prevention has been recognised by the society and the need for solutions preventing and early detect these diseases has produced a wide range of R&D opportunities. Through one such opportunity, we researched, developed and finally certified a system that digitises speech- and pen-based cognitive tests. These tests are as of today administered the same way as 50 years ago: with pen, paper. The system targets neuropsychologists who perform these tests in order to diagnose persons who may have dementia-related diseases. In the talk, I will cover interdisciplinary research, user-centred design and development, experiences with startup, marketing and sales. Finally, I will demonstrate how the technology can be used to diagnose other diseases and syndromes, such as apathy and depression.
The work has partly been funded by EIT Digital and involves a number of different partners including the German Research Center for Artificial Intelligence (DFKI GmbH) (Saarbrücken, Germany), Innovation Alzheimer (Nice, France), Saarland University Medical Centre (Germany), and a number of European clinics as well as pharmaceutical companies.
Jan's website Jan's LinkedIn KI-Elements