Non-invasive monitoring method for lower-leg compartment syndrome using a wireless sensor system and finite element analysis

Fuh Yu Chang*, Ping Tun Teng, Liang Chun Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a non-invasive pressure monitoring system that is portable and convenient was designed for detecting compartment syndrome. The system combines a wireless module and smartphone, which aids in the achievement of mHealth objectives, specifically, the continuous monitoring of the compartment pressure in patients. A compartment syndrome detecting method using a wireless sensor system and finite element analysis is developed and verified with an in vitro lower-leg model by rapid prototyping. The sensor system is designed to measure a five point pressure variation from the outside of the lower leg and transmit the data to a smartphone via Bluetooth. The analysis model based on the finite element method is employed to calculate the change of pressure and volume inside the four compartments of the lower leg. The in vitro experimental results show that the non-invasive detecting method can monitor the compartment pressure and provide a warning for the occurrence of compartment syndrome if the compartment pressure is higher than 30 mmHg. Furthermore, the theoretical simulation of the real lower leg shows similar trends to those of the in vitro experiments and can promptly detect the occurrence of compartment syndrome. Measured pressure values exceeding 6.3, 2.7, and 2.8 kPa for the three sensors contacting the outside centers of the superficial posterior, anterior, and lateral compartments, respectively, can indicate that each compartment contains a pressure higher than 30 mmHg. These results can provide a warning for the risk of compartment syndrome of each compartment. In addition, the measured values from the three sensors contacting the superficial posterior compartment at the outside center, close to the tibia, and close to the lateral compartment exceeding 1.8, 0.7, and 0.7 kPa, respectively, can indicate the risk of deep posterior compartment syndrome.

Original languageEnglish
Pages (from-to)346-356
Number of pages11
JournalProceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
Volume235
Issue number3
DOIs
Publication statusPublished - 2021 Mar
Externally publishedYes

Keywords

  • Compartment syndrome
  • finite element method
  • non-invasive pressure detect
  • pressure sensor
  • smartphone

ASJC Scopus subject areas

  • Mechanical Engineering

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