Caltech Scientists Develop Technique to Detect Hidden Health Issues

New method uses tiny skin ripples to reveal details about underlying tissue properties.

Published on Mar. 5, 2026

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Caltech scientists have developed a method that detects tiny, imperceptible movements at the surface of objects to reveal details about what lies beneath. By analyzing the physics of waves traveling across the surface of an object, the new technique can determine both the stiffness and thickness of the underlying material or tissue, laying the groundwork for inexpensive, at-home health monitoring using little more than a smartphone camera.

Why it matters

This new technique, called visual surface wave elastography, could enable proactive health monitoring by allowing people to track changes in their tissue properties over time and detect potential issues like tumor growth or muscle degeneration early on. The ability to measure tissue stiffness and thickness without invasive procedures represents a significant advancement in non-destructive testing and biomedical applications.

The details

The method uses an algorithm called phase-based motion processing to detect minute changes in position across the skin caused by small-amplitude waves produced by external forces. By analyzing the propagation of these surface waves, the scientists can build a mathematical model to determine the underlying tissue properties. The technique has been validated through experiments with simulated human legs and real gelatin models, yielding results comparable to high-precision instruments.

  • The new technique was presented at the International Conference on Computer Vision in Honolulu last fall.
  • The lead authors, Alexander C. Ogren and Berthy T. Feng, completed the work while at Caltech.

The players

Katie L. Bouman

Professor of computing and mathematical sciences, electrical engineering, and astronomy at Caltech, and both a Rosenberg Scholar and a Heritage Medical Research Institute (HMRI) Investigator.

Alexander C. Ogren

PhD student at Caltech and lead author on the paper.

Berthy T. Feng

PhD student at Caltech and lead author on the paper, now a postdoctoral fellow at MIT.

Chiara Daraio

The G. Bradford Jones Professor of Mechanical Engineering and Applied Physics at Caltech and an HMRI Investigator.

Jihoon Ahn

MS student at Caltech and co-author on the paper.

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What they’re saying

“There is information scattered all around us in plain sight that we just haven't learned to tap into. Our work is trying to leverage that information to recover material properties from inside objects by studying tiny movements on the surface.”

— Katie L. Bouman, Professor of computing and mathematical sciences, electrical engineering, and astronomy at Caltech (Mirage News)

“Because we all have cameras in our pockets, we can take frequent, inexpensive measurements of our tissue properties to track our health proactively over time. We could flag concerning changes and nudge you to get it checked out.”

— Alexander C. Ogren, PhD student at Caltech (Mirage News)

“It is exciting to see how powerful computer vision can be in uncovering hidden properties below the surface. This paper shows that even in a system as complex as a human limb, the dynamic analysis of visible surface waves can reveal subsurface characteristics that are usually impossible to detect without contact.”

— Chiara Daraio, The G. Bradford Jones Professor of Mechanical Engineering and Applied Physics at Caltech (Mirage News)

What’s next

The researchers plan to continue developing the technique and exploring its potential applications in proactive health monitoring and early disease detection.

The takeaway

This new method of using tiny skin ripples to reveal hidden health issues represents a significant advancement in non-invasive biomedical technology, with the potential to enable affordable, at-home health tracking and early intervention for a variety of medical conditions.