Identifiability of patient effort respiratory mechanics model

Jen Zhen Chee, Yeong Shiong Chiew, Chee Pin Tan, Ganesaramachandran Arunachalam

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

3 Citations (Scopus)


Respiratory mechanics models were developed as a non-invasive method to diagnose patient-specific respiratory mechanics to guide mechanical ventilation treatment. However, patient induced effort causes anomalies in the model that can lead to erroneous identification of patient respiratory mechanics. The polynomial model was developed as a model that considers patient effort. However, patient effort is inconsistent as it varies from patient-to-patient and breath-to-breath, causing the model to be unstable. Thus, in this paper, a thorough investigation has been conducted by simulating a myriad of patient effort conditions to determine the stability of the polynomial model. The findings revealed that the polynomial model is practically nonidentifiable due to erratic patient efforts. Following that, it was also found that early or long patient effort would result in erroneous identification of respiratory mechanics. We introduced a one-second end of inspiration pause during simulation, and found that it provided consistent and accurate identification of patient elastance which is significant in creating optimal patient-specific ventilator setting. However, the inspiration pause is an additional procedure and it also limit the patient’s air supply. Future research can be conducted to determine the optimum duration for inspiration pause while maintaining patient comfort.

Original languageEnglish
Title of host publication2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781538624715
Publication statusPublished - 2019
EventIEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2018 - Sarawak, Malaysia
Duration: 3 Dec 20186 Dec 2018 (Proceedings)


ConferenceIEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2018
Abbreviated titleIECBES 2018
Internet address


  • Mechanical ventilation
  • Respiratory mechanics model
  • Reverse triggering

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