NeuroWearXfor Empowered
Co-Intelligence.

Introducing NeuroWearX and the questions shaping empowered human–machine co-intelligence.

Talk abstract and session details will be available soon.

BCI, eye-tracking, and physiological signals in neuro-rehabilitation and assistive technology development.

Traditional approaches to monitoring aging and health rely on brief, infrequent assessments that often miss meaningful changes occurring in everyday life. Advances in wearable devices, ambient sensors, and intelligent environments are enabling a new paradigm in which health, function, and behavior can be measured continuously and unobtrusively in real-world settings. This presentation will explore how longitudinal digital biomarkers derived from passive sensing can reveal early changes in mobility, sleep, daily activities, physiology, and cognition, often years before they become apparent through conventional assessments. Drawing on work from the Oregon Center for Aging & Technology (ORCATECH), Dr. Beattie will highlight an in-home sensing platform, examples of novel digital biomarkers, and findings from long-term studies of cognitive aging and neurodegenerative disease. He will discuss how increasingly intelligent and low-burden technologies can support healthy aging by quietly identifying meaningful changes in everyday function.

Networking, refreshments, and informal discussion.

As digital technologies grow ever more capable, how might we design them to extend human intellect rather than replace it? In this talk, Ast. Prof. Samantha Chan shares her research exploring cognitive interfaces: systems that augment human memory, attention, learning, and critical thinking through both digital and neurophysiological means. She will reflect on how her work has evolved from early experiments in sensing cognitive and emotional states, to developing systems that model and complement human cognitive processes, and more recently, to integrating large language models, extended reality and multisensory stimuli for cognitive augmentation. Through these projects, Dr. Chan illustrates how design and engineering can converge to create technologies that work with our minds rather than for them. The talk concludes by asking: What might the next generation of cognitive interfaces look like if they were designed to truly empower human potential? How could such systems reshape how we think, learn, and live alongside intelligent machines?

Wearable computing increasingly demands cybernetic systems that move beyond rigid devices toward technologies that conform to the body, disappear into everyday materials, and operate across multiple spatial scales. This talk presents a series of soft, flexible, stretchable, and textile-based sensing platforms and distributed systems that explore how computation can be embedded within garments, across the body, and throughout interactive environments. Such soft technologies could provide a foundation for intelligent soft wearables and future physiological and embodied computing systems capable of inferring human state, movement, and interaction, while ultimately enabling closed-loop sensing and actuation for more adaptive, intimate, and immersive forms of human–machine collaboration.

As intelligent technologies become increasingly capable of sensing, interpreting, and responding to human states and contexts, the future of human–machine interaction may extend far beyond conventional interfaces. This panel explores the emerging vision of human-centered co-intelligence, where humans and intelligent systems continuously understand, adapt to, and complement one another while preserving human agency, trust, and well-being. Bringing together perspectives across wearable technologies, neurotechnology, AI, digital health, and intelligent environments, the discussion will examine what truly human-centered co-intelligence should mean, the key scientific and technological barriers that remain, the principles that should guide its development, and the research priorities needed to move from intelligent interfaces toward meaningful and empowering human–machine partnerships.