Intelligent monitoring systems and affective computing applications have emerged in recent years to improve healthcare. Examples of these applications include intelligent monitoring of physiological changes and sedation states, assessment of affective states such as pain and depression, and detection of neurological and developmental disorders. However, insufficient attention has been paid to the integration of contextual, personalized, uncertainty, and multimodal information into healthcare applications of vulnerable populations. This information paired with transparency and explainability can lead to the development of reliable and responsible applications for automated monitoring, detection, and prediction of affective states and health conditions in vulnerable populations. Such applications can deliver tailored and prompt interventions.
CAIHA workshop focuses on using Computer Vision, Pattern Recognition, and Affective Computing methods to enhance healthcare of vulnerable populations. It gathers researchers working on Computer Vision, Pattern Recognition, Affective Science and Computing, Behavioral Sciences, Mental and Physical Health, Neuroscience, Robotics, and other disciplines. It will expose current applications and datasets, and provide an interdisciplinary forum for the exchange of ideas on novel applications, new datasets, current challenges, and future directions.
Topics of interest include, but are not limited to:
- Novel approaches to model affective and sedation states, health conditions and disorders of vulnerable populations; e.g., infants, children, elderly, functionally or verbally impaired people.
- Novel approches to measure satisfaction of vulnerable patients from different modalities; e.g., text, visual, vocal, etc.
- Personalized, context-aware, and predictive modeling in intelligent and affective healthcare applications.
- Multimodal modeling in intelligent and affective healthcare applications.
- Explainability and uncertainty in intelligent and affective healthcare applications.
- Novel approaches to handle missing and noisy data in real-world environment.
- Design/development of methods/system for real-time healthcare applications and limited-resource computing devices.
- Applications of virtual reality to enhance health of vulnerable populations.
- Benchmark datasets relevant to the workshop topics.
Please check publicly and non-publicly available datasets here.
Submissions that do not demonstrate an existing or potential application of computational and affective computing in healthcare for vulnerable populations are not topics of interest for this workshop. Submissions should be original with no substantial overlap with any other paper already submitted or published.
October 17, 2020 (Anywhere on Earth)
Decision to Authors:
November 10, 2020
November 15, 2020