The ChronoPilot project is revolutionizing an approach to modulating human time perception by harnessing Extended Reality (XR) technologies and machine learning techniques, to enhance well-being, optimize decision-making, and improve overall performance in both individual and collaborative settings.
Funded under the European Union’s Horizon 2020 FET Open research program, the project unites five universities from four EU countries, promoting an interdisciplinary collaboration that is unlocking new possibilities in time perception research.
Sahar Niknam is a PhD researcher at the University of Luxembourg and a key figure in the ChronoPilot project, with a background that spans robotics engineering and philosophy of science in Iran, to cognitive science in Germany, she has built her expertise around artificial intelligence. Her journey to Luxembourg was somewhat unexpected, but she embraces it wholeheartedly.
As a woman in research, Sahar envisions a future where gender is no longer a defining factor in the scientific field. She believes true equality will come when we no longer feel the need to specify “female scientist” or “male scientist,” but instead recognize individuals for their expertise and contributions. “If I cannot think about myself as a female, just as a person who is interested in science, there wouldn’t be any problem,” said Niknam.
Her perspective highlights the ongoing struggle for true gender equity in research, and her own journey stands as proof of resilience, ambition, and the drive to push past barriers. “If I want to be a successful researcher, I have to learn to work with other people with different perspectives. Even when you don’t like what they are doing or think you can do better, it’s important to listen, because you can always learn,” said Niknam.
“Landing a job in research has always been my dream.”
Sahar Niknam, PhD researcher, University of Luxembourg
The science behind time perception
At its core, ChronoPilot seeks to modulate subjective time experience by analyzing a range of physiological signals and environmental factors. Researchers from the University of Luxembourg, for instance, utilize electroencephalogram (EEG) data, biosignals, and eye-tracking technology to understand how virtual environments influence time perception. By identifying sensory and cognitive factors that impact the way we perceive time, ChronoPilot can design immersive applications that subtly alter our perception of time’s passage.
Unlike sensory modalities such as vision or hearing, time perception lacks a clearly defined neural mechanism. Scientists do not yet fully understand how the brain processes time, making it a unique challenge for research. As a result, ChronoPilot adopts a “black box” approach, leveraging machine learning models to map physiological and psychological data to subjective time states.
These models not only predict an individual’s perception of time but also personalize the modulation process, ensuring that the intervention adapts dynamically to the user’s personality, mood, and situational context.
The role of extended reality (XR)
Extended reality plays a crucial role in ChronoPilot’s mission. XR provides an immersive and controlled environment where researchers can manipulate variables that influence time perception in ways that would be impossible in a traditional laboratory setting. “The time loss phenomenon observed in virtual reality games, where users lose track of time to an unprecedented degree, demonstrates how potent XR can be as a tool for studying and modulating time perception,” said Niknam.
Beyond research, XR serves as the primary platform for implementing time perception modulation. In a future where ChronoPilot is widely adopted, individuals could use XR headsets or glasses to modify their time experience, slowing it down during stressful situations or speeding it up during monotonous tasks. By integrating time modulation techniques directly into virtual environments, ChronoPilot has the potential to revolutionize how people manage their daily schedules and interactions.
“The adaptivity of a ChronoPilot device as a final product is only possible with machine learning […]”
Sahar Niknam, PhD researcher, University of Luxembourg
While still in the prototype phase, ChronoPilot’s potential applications span several industries. In healthcare, time perception modulation could help individuals with neurological conditions mitigate the side effects of distorted time perception. Psychological and mental health interventions could also benefit, providing tools to help patients cope with anxiety or depressive disorders.
In industrial and manufacturing settings, ChronoPilot explores ways to synchronize human workers with robotic collaborators, improving efficiency and coordination in automated environments. In precision farming scenarios, time modulation can enhance concentration and decision-making when operating drones or other autonomous systems. Meanwhile, in entertainment and creative sectors, controlling time perception can intensify storytelling impact, deepening audience engagement or subtly shifting emotional responses.
Challenges of time perception research
One of the greatest challenges ChronoPilot faces is the lack of a concrete understanding of the neural and sensory mechanisms underlying time perception. “Time remains an enigmatic construct with diverse interpretations across disciplines,” said Niknam. The project’s machine learning-driven approach offers a promising way to navigate this uncertainty, allowing researchers to develop effective interventions without needing a definitive physiological model of time perception.
As the ChronoPilot project nears completion, its focus shifts toward refining its functioning prototype and engaging with industry stakeholders. By demonstrating its applicability beyond academic research, ChronoPilot aims to establish itself as an innovative and beneficial tool that merges science, technology, and human experience. The project is not only a testament to European research excellence but also an ambitious step toward reshaping how we experience and control time in our everyday lives.
“The adaptivity of a ChronoPilot device as a final product is only possible with machine learning, something that can learn from the user’s behavior and personalize their perception of time. This is not just research, it’s a step toward redefining how we experience time itself,” said Niknam.
