Smartphone Speckle Imaging for Finger Perfusion

ISEF Category: Physics and Astronomy

Subcategory: Biological Physics  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

Your blood flow leaves a pattern of tiny bright and dark grains called speckle. That graininess changes when blood moves faster or slower. With the right setup, your phone can turn that change into a map of perfusion. This project sits right between physics, biology, and real medical sensing.

What Is It?

Laser-speckle contrast imaging uses a laser and a camera to measure motion in tissue. When coherent light, like laser light, hits skin, it creates a speckle pattern, which looks noisy. If blood cells move under the surface, the pattern blurs from frame to frame. More blur usually means faster flow.

Think of it like watching traffic through a rainy window. If the cars are parked, the view stays sharp. If the cars move, the image smears more quickly. Speckle contrast works the same way, but the moving parts are red blood cells in tiny vessels. A cold-pressor test, where you place a finger in cold water, can trigger a clear change in blood flow, so you can compare baseline and stress conditions.

Why This Is a Good Topic

This makes a strong science fair topic because you can test a real physical signal and turn it into a number. You can change one condition, measure how the speckle pattern shifts, and compare flow before, during, and after cold stress. The project connects to blood perfusion, microcirculation, and noninvasive medical sensing. You can also learn image analysis, calibration, and model fitting, which are useful skills for ISEF-level work.

Research Questions

• How does finger perfusion change before, during, and after a cold-pressor test? ?
• What is the effect of skin temperature on speckle contrast in fingertip images? ?
• Does the measured decorrelation time differ between the index finger, middle finger, and thumb? ?
• To what extent does ambient room light affect speckle contrast measurements from a smartphone camera? ?
• Which image-processing method gives the most stable estimate of capillary flow velocity from speckle data? ?
• How does hand position relative to the camera change the repeatability of perfusion maps? ?

Basic Materials

• Smartphone with manual camera controls.
• Low-power laser diode or laser pointer with stable mount.
• Diffuser or safety-rated beam-spreading material.
• Tripod or phone clamp.
• Finger rest or foam support to keep position fixed.
• Disposable gloves or finger covers for hygiene.
• Ice water bath container for cold-pressor test.
• Timer or stopwatch.
• Ruler or calibration target.
• Dark cloth or blackout box to reduce stray light.
• Laptop for image analysis.
• Basic safety goggles matched to the laser wavelength.

Advanced Materials

• Scientific-grade camera or machine-vision camera.
• Stable laser source with known wavelength and beam profile.
• Optical filters matched to the laser wavelength.
• Translation stage or optical breadboard.
• Polarizers for testing polarization effects.
• Infrared thermometer or skin temperature probe.
• Pulse oximeter for comparison with physiological signals.
• Phantom materials that mimic tissue scattering.
• Microcontroller for synchronized timing and acquisition.
• Biomedical optics safety equipment.
• Access to validation tools for flow or motion measurement.

Software & Tools

• ImageJ: Measures speckle contrast, tracks regions of interest, and compares frame-by-frame changes.
• Python: Automates preprocessing, calibration, and statistical analysis of contrast metrics.
• NumPy: Handles arrays of image data for quick numerical calculations.
• SciPy: Fits models and tests whether decorrelation time changes with condition.
• Jupyter Notebook: Keeps code, graphs, and notes together in one place.

Experiment Steps

1. Define the physiological signal you want to measure, then decide whether your main output will be contrast, decorrelation time, or a derived flow index.
2. Design a fixed imaging geometry that keeps laser angle, camera distance, and finger position consistent across trials.
3. Plan a calibration strategy that links image contrast to a known motion standard before you test human fingers.
4. Choose controls that separate true blood-flow changes from lighting, motion, and skin-surface artifacts.
5. Build an analysis pipeline that turns raw frames into repeatable summary metrics for each trial.
6. Set up a comparison plan for baseline, cold exposure, and recovery so you can test your model over time.

Common Pitfalls

• Letting the finger move even a little, which adds motion blur that looks like real flow change.
• Changing camera exposure between trials, which breaks the link between contrast and decorrelation time.
• Using uncontrolled room light, which shifts image brightness and corrupts speckle measurements.
• Skipping a calibration step, which leaves you with contrast values that cannot be compared across sessions.
• Treating skin color, pressure, and temperature as if they do not matter, which can hide the true perfusion signal.

What Makes This Competitive

A strong version of this project goes beyond pretty images. You would build a calibration curve, test error sources, and compare more than one model for turning speckle contrast into flow velocity. You could also validate your results against a second measure, like skin temperature or pulse changes, to check whether the signal really tracks perfusion. Careful statistics and repeat trials would make the work much stronger than a one-off demo.

Project Variations

• Test how speckle contrast changes across different fingers, then compare which finger gives the cleanest perfusion signal.
• Compare a smartphone camera with a higher-end camera to see how sensor quality changes model accuracy.
• Add a skin-temperature measurement and test whether combining temperature and speckle data improves flow estimates.

Learn More

• PubMed: Search for review articles on laser speckle contrast imaging, perfusion, and microcirculation.
• NIH PubMed Central: Read full-text papers on noninvasive blood flow imaging and optical methods.
• NASA ImageJ resources: Learn basic image analysis workflows and region-of-interest measurements by searching for ImageJ tutorials.
• MIT OpenCourseWare, Biomedical Optics: Find lecture notes on light scattering, imaging, and tissue optics.
• Biomedical Optics Express: Search recent papers on speckle imaging methods and validation studies.
• NOAA educational optics materials: Look for free resources on light, imaging, and measurement basics.