Triboelectric Incontinence Sensor

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Triboelectric Incontinence Sensor

ISEF Category: Biomedical Engineering

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Subcategory: Biomedical Devices  ·  Difficulty: Advanced  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

Pelvic floor dysfunction affects millions of women but most go undiagnosed. A self-powered sensor that detects both wetness and pressure inside a regular panty-liner could screen people years earlier. Aluminum foil, Velostat, and a PVDF film harvest the energy themselves and beam alerts to a phone over Bluetooth.

What Is It?

Triboelectric generators produce small voltages when two materials separate and contact. PVDF is a piezoelectric polymer that adds pressure sensitivity. Velostat is a conductive foam used as a pressure layer.

The combined sensor sits inside a panty-liner. When pressure changes (cough, sneeze, leak), the sensor produces voltage spikes whose pattern differs from baseline. A small ESP32 reads the signal and transmits over BLE.

The fusion of wetness (capacitance change) and pressure (triboelectric spikes) gives a screening signal for stress incontinence and pelvic-floor weakness. Real diagnosis still requires a clinician.

Why This Is a Good Topic

Self-powered wearable sensors are a growing field. Materials are cheap and the use case is real. You will learn material physics, low-noise sensor design, and embedded BLE.

Research Questions

  • How does layer thickness change triboelectric voltage amplitude?
  • What is the effect of fluid volume on capacitance shift?
  • Does the fused signal outperform single-modality baselines?
  • To what extent does fabric backing affect output?
  • Which event type triggers the largest fusion spike?
  • How does body motion noise contaminate the signal?
  • What is the effect of BLE transmit interval on battery life?

Basic Materials

  • Aluminum foil.
  • Velostat conductive foam.
  • PVDF film (small online sample).
  • ESP32 with low-power mode.
  • Coin-cell or LiPo battery.
  • Simulated fluid (saline) and test rig.
  • Informed-consent form.

Advanced Materials

  • Polished PVDF or PTFE sheets.
  • Lab-grade capacitance meter.
  • Anechoic shielding chamber.
  • Clinical mentor.

Software & Tools

  • Arduino IDE or PlatformIO: Programs the ESP32.
  • Python (NumPy): Processes the captured signal traces.
  • nRF Connect: Verifies BLE transmissions.
  • Matplotlib: Plots event-classification confusion matrices.

Experiment Steps

  1. Build a controlled fluid-volume rig before any wear test.
  2. Decide layer stack-up and lock dimensions.
  3. Calibrate output voltage vs. known pressure events.
  4. Plan controls (no fluid, no pressure) and randomized order.
  5. Combine modalities in software and tune fusion thresholds.
  6. Report detection accuracy under motion noise.

Common Pitfalls

  • Mixing layer materials between trials.
  • Letting humidity drift, which changes triboelectric output.
  • Ignoring electromagnetic interference from phones.
  • Treating one test cycle as full data.
  • Skipping a safety review for body-contact materials.

What Makes This Competitive

A competitive project shows a clear signal-to-noise comparison against a single-modality baseline, calibrates voltage signatures with a benchtop fluid setup, and reports detection accuracy under realistic body-motion noise. Informed-consent and material-safety reviews are essential.

Project Variations

  • Replace PVDF with a homemade nanofiber mat.
  • Add a thermistor for warmth-related leakage detection.
  • Test the sensor under simulated diaper-pad geometry instead.

Learn More

  • PubMed: Search triboelectric wearable health sensor reviews.
  • NIH PubMed Central: Open-access incontinence screening papers.
  • Espressif ESP32 documentation: Free hardware guides.
  • ASTM International: Standards on absorbent garment testing.
  • MIT OpenCourseWare: Course 6.S191 Introduction to Deep Learning.
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