Flow stabilization in wearable microfluidic sensors enables noise suppression

Area of Science:

• Biomedical Engineering
• Microfluidics
• Sensor Technology

Background:

• Intraocular pressure (IOP) monitoring is crucial for glaucoma management.
• Existing IOP sensing methods face challenges with accuracy and invasiveness.
• Dilatometric strain sensors (DSS) offer a promising non-invasive approach.

Purpose of the Study:

• To investigate the use of microfluidic-based dilatometric strain sensors (DSS) for intraocular pressure (IOP) monitoring.
• To evaluate the signal-to-noise ratio improvement through microfluidic low-pass filtering.
• To develop a computational model for DSS design.

Main Methods:

• Fabrication of DSS using soft, transparent materials integrated with microfluidic channels.
• Characterization of sensor time constants (1-200 seconds) influenced by device architecture and fluid viscosity (10-866 cSt).
• Development of an equivalent circuit model to predict sensor performance.

Main Results:

• Microfluidic low-pass filtering significantly improves signal-to-noise ratio for ophthalmic applications.
• Demonstrated suppression of rapid fluctuations (e.g., ocular pulsation, blinking) by 9 dB with a 4s time constant sensor.
• The equivalent circuit model accurately represents experimental DSS data.

Conclusions:

• Microfluidic-based DSS are highly sensitive and suitable for IOP sensing.
• Low-pass filtering in microfluidics enhances signal quality for ophthalmic monitoring without electronics.
• The developed model aids in the design and optimization of microfluidic sensors.