Virtual Spirometry and Activity Monitoring Using Multichannel Electrical Impedance Plethysmographs in Ambulatory Settings

Hassan Aqeel Khan, Amit Gore, Jeffrey Ashe, Shantanu Chakrabartty

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Continuous monitoring of respiratory patterns and physical activity levels can be useful for remote health management of patients with conditions such as heart disease and chronic obstructive pulmonary disease. In a clinical setting, spirometers serve as the gold standard for monitoring respiratory patterns such as breathing rate and changes in lung volume. However, direct measurements using a spirometer requires placement of a sensor in the patient's airway and is thus infeasible for continuous monitoring in nonclinical, ambulatory settings. Under these conditions, indirect respiration monitoring using electrical impedance plethysmographs (EIP) is more suitable but are susceptible to motion artifacts. In this paper, we investigate whether multichannel EIP can be used to perform virtual spirometry under ambulatory settings. The experiments presented in this paper are based on preliminary data collected from 19 adult human subjects under realistic ambulatory and nonambulatory settings. We first highlight the salient features of the signal acquired from a standard spirometer. We then compare the performance of different biosignal processing algorithms in estimating the spirometer signal using multiple EIP sensors and in the presence of motion artifacts and real-world interferences. We demonstrate that in addition to reliably determining different respiratory patterns and states, multichannel EIP could also be used to reliably extract information regarding different patient physical activity states like bending or stretching.

Original languageEnglish
Article number7933008
Pages (from-to)832-848
Number of pages17
JournalIEEE Transactions on Biomedical Circuits and Systems
Issue number4
StatePublished - Aug 2017


  • Amplitude modulation
  • Gaussian mixture regression (GMR)
  • electrical impedance plethysomgraphy (EIS)
  • lung volume
  • physical activity monitoring
  • remote health monitoring systems
  • respiration rate
  • spirometry
  • support vector regression


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