Grant: Discovery Grants Program - Individual

Alzheimer's Disease (AD) affects millions of people worldwide every year. Despite the significance of the disease, there is no effective pharmacological treatment available yet, which has led to a shift towards non-pharmacological solutions to alleviate the symptoms. Patients' cognitive performances are directly influenced by their emotions. Physiological sensors, such as electroencephalogram (EEG), allow monitoring these emotions in real time. Moreover, virtual reality (VR) offers an immersion in the virtual environment and isolation from any external visual distractions, which enhances the accuracy of emotion measurement. Furthermore, the combination of artificial intelligence with VR and emotion detection allows the development of intelligent adaptive systems designed to improve patients' cognitive performance. The first research challenge concerns the measurement of emotions, as it serves as the input that enables the computer to understand what the patient is feeling. The use of EEG provides accurate measurements, but remains problematic, since these sensors are intrusive and their use can disturb AD patients, thereby affecting the accuracy of the measured data. The challenge, therefore, lies in measuring with other non-intrusive sensors, while maintaining measurement accuracy. The second challenge concerns the exploration of new non-pharmacological approaches for AD. For instance, relaxing environments have been proven to be effective in improving the cognitive performance of AD patients, but their effect varies from one patient to another. The third challenge concerns system adaptation for non-pharmacological approaches for AD patients. Since each patient may a have different perception about these interventions, their emotional reactions will vary. Therefore, my long-term objective is to create an intelligent platform for AD patients, which includes multiple non-pharmacological approaches that are personalized and optimized for each patient, considering their emotions and cognitive performances. For the next five years, my short-term objectives are, first of all, to explore new emotion measurement tools by combining physiological sensors and artificial intelligence to create new emotion prediction models. I plan to use four physiological sensors (EEG, Eye Tracking, Heart Rate, and Electrodermal Activity) simultaneously to train models that utilize non-intrusive sensors while maintaining detection accuracy. Second, design an intelligent adaptation system capable of adapting VR environments using emotion measurement tools. Finally, my third short-term objective is to explore two adaptive non-pharmacological approaches for AD using VR. The first approach involves is relaxing adaptable VR environment which aims to maximize patients' positive emotions. The second approach entails a serious adaptable game aiming to improve various cognitive abilities.