# Strain Plethysmography Using a Hermetically Sealed MEMS Strain Sensor

**Authors:** Xinyu Jiang, Brian Sang, Haoran Wen, Gregory Junek, Jin-Woo Park, Farrokh Ayazi

PMC · DOI: 10.3390/bios15050325 · Biosensors · 2025-05-20

## TL;DR

A new MEMS strain sensor is developed for high-quality strain plethysmography, enabling accurate heart rate and blood pressure monitoring.

## Contribution

A hermetically sealed MEMS strain sensor with high sensitivity and linearity for SPG signal acquisition is introduced.

## Key findings

- The MEMS strain sensor achieves a gauge factor of 35 and a strain sensing resolution of 1.26 µε.
- SPG signals captured at the fingertip and wrist show high signal quality and preserve PPG features.
- Heart rate and variability are estimated with over 99% accuracy using SPG signals from the sensor.

## Abstract

We present a hermetically sealed capacitive microelectromechanical system (MEMS) strain sensor designed for arterial pulse waveform extraction using the strain plethysmography (SPG) modality. The MEMS strain sensor features a small form factor of 3.3 mm × 3.3 mm × 1 mm, leverages a nano-gap fabrication process to improve the sensitivity, and uses a differential sensing mechanism to improve the linearity and remove the common mode drift. The MEMS strain sensor is interfaced with an application-specific integrated circuit (ASIC) to form a compact strain sensing system. This system exhibits a high strain sensitivity of 316 aF/µε, a gauge factor (GF) of 35, and a strain sensing resolution of 1.26 µε, while maintaining a linear range exceeding 700 µε. SPG signals have been reliably captured at both the fingertip and wrist using the MEMS strain sensor with high signal quality, preserving various photoplethysmography (PPG) features. Experimental results demonstrate that heart rate (HR) and heart rate variability (HRV) can be estimated from the SPG signal collected at the fingertip and wrist using the sensor with an accuracy of over 99%. Pulse arrival time (PAT) and pulse transit time (PTT) have been successfully extracted using the sensor together with a MEMS seismometer, showcasing its potential for ambulatory BP monitoring (ABPM) application.

## Full-text entities

- **Genes:** SPG16 (spastic paraplegia 16 (complicated, X-linked recessive)) [NCBI Gene 57760] {aka SPG}
- **Diseases:** MEMS (MESH:D015619), BPM (MESH:D005117), cardiovascular diseases (MESH:D002318), myocardial deformation (MESH:D009140), injury to (MESH:D014947)
- **Chemicals:** metal (MESH:D008670), Si (MESH:D012825), epoxy (MESH:D004853), mercury (MESH:D008628), Au (MESH:D006046), Oxide (MESH:D010087), PCB (-), hydrogen fluoride (MESH:D006858), SiO2 (MESH:D012822), TEOS (MESH:C040733)
- **Species:** Homo sapiens (human, species) [taxon 9606]
- **Mutations:** E4980A

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12110129/full.md

## Figures

17 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12110129/full.md

## References

26 references — full list in the complete paper: https://tomesphere.com/paper/PMC12110129/full.md

---
Source: https://tomesphere.com/paper/PMC12110129