Sensing Beyond Signals: From Biology to Human Insight

Join us for an engaging breakfast session at IEEE INERTIAL 2026 hosted by the WiSe Committee of the IEEE Sensors Council, where cutting-edge ideas meet informal conversation.

This dynamic hour will feature short pitches from Anna Radovic and Naama Mashiach, exploring how biosensor innovation and inertial data are reshaping our understanding of biological systems and human mental states. From interdisciplinary collaboration inspired by nature to predictive insights into stress and performance, the session highlights how sensing technologies are moving beyond measurement toward meaning.

The event will conclude with an open discussion, over coffee and breakfast, offering a relaxed space to exchange ideas, connect, and reflect on the future of sensing.

  • Biological systems offer profound inspiration for information transfer, energy usage, and sustainability. While engineering translates these concepts into practical models, progress in the 21st century depends upon collaboration between these two fields.

    In contrast to biological systems that operate internally, human-engineered systems are simpler and can be produced at scale. Their performance is easily measured, monitored, adjusted, and their results can be readily shared.

    Here I would like to briefly address the nature of current state and projected future of biosensor technology as well as share several examples of personal collaborative research between biological sciences, physics, and engineering

  • We have spent decades optimizing inertial sensors to measure motion with extreme precision - but precision alone is no longer the bottleneck.
    The real opportunity lies in decoding human state from these signals: identifying mental stress, behavioral shifts, and performance degradation before they are consciously perceived.
    With the right data processing, it becomes possible to predict a mental crisis days before it unfolds. At Buzzy Platform, we turn raw sensor data into accurate, real-time predictions of mental state - come see how.