Physiological Computing and Artificial Intelligence

A recent report from World Intellectual Property Organization (WIPO) has introduced new emerging Assistive Technologies (ATs): self-care technologies (eg health and emotion monitoring) and brain-computer interfaces for enhanced communication and mobility [1]. At the centre of the aforementioned ATs is artificial intelligence (AI)-powered physiological computing - a rapidly growing research area on enabling technologies that help us to listen to our bodily functions and psychophysiological needs and self-regulate [2-5]. The bodily functions are measured by physiological sensors, such as wearable heart rate monitor. AI plays a pivotal role in interpreting the physiological activities into the needs. Then, captured information is fed back into us to increase the awareness of our psychophysiological states and have greater control of our body and mind, promoting positivity gradually over time.

[1] WIPO Technology Trends 2021: Assistive Technology, https://www.wipo.int/edocs/pubdocs/en/wipo_pub_1055_2021.pdf
[2] Physiological Computing and Artificial Intelligence Lab, https://youngjuncho.com/physiological-computing-artificial-intelligence/
[3] Cho, Youngjun. "Rethinking eye-blink: assessing task difficulty through physiological representation of spontaneous blinking." Proceedings of the 2021 CHI conference on human factors in computing systems. 2021.
[4] Moge, Clara, Katherine Wang, and Youngjun Cho. "Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI." CHI Conference on Human Factors in Computing Systems. 2022.
[5] Chen, S., Cho, Y., Yu, K., Ferrari, L. M., & Bremond, F. (2022). Recognizing the State of Emotion, Cognition and Action from Physiological and Behavioural Signals. Frontiers in Computer Science, 97.

Lead: Youngjun Cho
Lab webpage: https://youngjuncho.com/physiological-computing-artificial-intelligence/

* We are part of Global Disability Innovation Hub - WHO Collaborating Centre for Assistive Technology

Projects

Remote Physiological Sensing: Thermal Imaging & remote PPG

As humans are homeothermic, our internal temperature is closely linked with numerous physiological and psychological mechanisms. Given this, human thermal patterns have been explored to improve the understandings of our body for a couple of centuries (Cho, 2019). Researchers have shown that physiological signatures can be captured through non-contact thermal imaging (e.g. respiration monitoring in Cho et al. 2017). Whilst other contactless sensing methods, such as, RGB camera-based photo-plethysmography suffer from illumination and privacy issues, thermography is much less affected by those constraints (Lloyd, 2013). In addition, studies have shown that different ... Read more…

Social Biofeedback Interaction Framework

As an emerging interaction paradigm, physiological computing is increasingly being used to both measure and feed back information about our internal psychophysiological states. While most applications of physiological computing are designed for individual use, recent research has explored how biofeedback can be socially shared between multiple users to augment human-human communication. In this project, we aim to understand and formulate physio-temporal and social contextual factors surrounding physiological data sharing as well as how it can promote social-emotional competences [1]. Checkout our recent paper: [1] Moge, Clara, Katherine Wang, and Youngjun Cho. "... Read more…

Thermal Imaging

Advanced thermography technology has emerged, producing a new category of thermographic systems: mobile, low-cost thermal imaging system - which is extremely exciting! Despite the relatively low quality of their thermal imaging outputs, this technology could help bridge the gap between the findings from highly constrained laboratory environments and real-world applications in the wild. Indeed, its portability (e.g. small size and low computational resource requirement) allows it to not only be easily attached to mobile phones but also be integrated into our clothes and accessories. We explore how to bring ... Read more…

Stress, Mental Workload, Task Difficulty

Continuous assessment of stress, mental workload and task difficulty is essential in improving the usability and accessibility of interactive systems. Physiological sensing capabilities have often been investigated to achieve this ability, with reports on the limited role of standard physiological metrics. In this project, we explore new approaches to the analysis of our physiological responses for automated estimation of such psychological states. Some of our featured articles and editorial below: [1] Cho, Youngjun. "Rethinking eye-blink: assessing task difficulty through physiological representation of spontaneous blinking." Proceedings of the 2021 CHI conference ... Read more…

Brain-Computer Interfaces (BCI) & Tailored Neurofeedback to Assist Users' Meditation Habits

We are developing neurofeedback treatments using Brain-Computer Interfaces to assist users in building a meditation habit. Neurofeedback has been used in literature to assist users in understanding themselves during meditation. However, this treatment is often a one-size-fits-all. We are working on a framework that can tailor neurofeedback based on maximising user outcomes of treatment. Read more…

Comfort AI (Phase II: 2021-22)