Emotion-aware assistive technologies in rehabilitation and healthcare

点击翻译按钮获取中文摘要

There is a growing need for technologies to help care for Canada's increasing disabled & aging populations. One limitation of current technologies is that they cannot recognize or respond to emotions like human caregivers do. Emotion-awareness would enhance the ability of assistive technologies to interpret & adapt to user needs. For example, detection of acute fear could improve the accuracy of fall detectors for elders living alone; awareness of frustration or engagement could be used to optimize computer games for virtual learning & rehabilitation; alertness to clinically important emotions could facilitate self-management of chronic conditions (e.g. depression). Many studies have shown that emotions can be detected by observing multiple physiological signals like heart rate & respiration in laboratory conditions. However, scientific & engineering advancements are needed before emotions can be reliably detected by everyday consumer products. The objectives of this research are:(1) To develop emotion detectors that can accommodate diverse physiological & emotional responses of different people; (2) To improve detection accuracy by combining physiological, contextual (e.g. time of day) & psychological (e.g. personality traits) indicators of emotions, & (3) To create a prototype emotion-aware computer learning game and compare user performance and enjoyment of the game with and without emotion-awareness. To achieve these objectives, we will collect emotional, physiological, psychological, & contextual data from participants as they engage in computer games that vary in difficulty & duration. We will elicit positive (engagement, enjoyment) & negative (frustration, anxiety) emotions related to the learning experience. We will develop models to classify the emotions experienced using the collected data. We will test the accuracy of our models for different people at different times. This research will eventually lead to the development of computer learning games for autistic children to improve access to and reduce costs of intensive therapies associated with their care. Our research is widely applicable with commercial opportunities in workplace stress management, smart homes & health monitoring.