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Unobtrusive, Through-Clothing ECG and Bioimpedance Monitoring in Sleep Apnea Patients

Conference Paper (2020)
Authors

Ivan Castro (IMEC-Solliance)

Aakash Patel (IMEC-Solliance)

Margot Deviaene (Katholieke Universiteit Leuven)

Dorien Huysmans (Katholieke Universiteit Leuven)

Pascal Borzée (Katholieke Universiteit Leuven)

Bertien Buyse (Katholieke Universiteit Leuven)

Dries Testelmans (Katholieke Universiteit Leuven)

Sabine Van Huffel (Katholieke Universiteit Leuven)

Carolina Varon (TU Delft - Signal Processing Systems, Katholieke Universiteit Leuven)

Tom Torfs (IMEC-Solliance)

Research Group
Signal Processing Systems
Copyright
© 2020 Ivan Castro, Aakash Patel, Margot Deviaene, Dorien Huysmans, Pascal Borzee, Bertien Buyse, Dries Testelmans, Sabine Van Huffel, Carolina Varon, Tom Torfs
To reference this document use:
https://doi.org/10.22489/CinC.2020.191
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Ivan Castro, Aakash Patel, Margot Deviaene, Dorien Huysmans, Pascal Borzee, Bertien Buyse, Dries Testelmans, Sabine Van Huffel, Carolina Varon, Tom Torfs
Research Group
Signal Processing Systems
ISBN (electronic)
9781728173825
DOI:
https://doi.org/10.22489/CinC.2020.191
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Abstract

A real-life validation of a system for simultaneous acquisition of capacitively-coupled ECG (ccECG) and capacitively-coupled bioimpedance (ccBioz) is presented. The heart rate (HR) and respiration rate (RR) estimation performance was evaluated using polysomnography (PSG) signals as ground-truth, in recordings from 28 patients with suspected obstructive sleep apnea (OSA). A ccECG beat detection sensitivity of 98.4% and an R-R interval mean absolute error (MAE) of 17.1 ms were achieved when applying quality-based algorithms. RR MAE values of 3.48 and 6.37 breaths per minute were also achieved when using two different RR extraction methods. High similarity between unobtrusive signals and PSG ground-truth was observed, with a correlation between ccECG and psgECG of 91.5% and a correlation between ccBioz and PSG thoracic belt (TB) of 89.5%. Even in episodes containing OSA events, the characteristic respiration behavior of TB signals was also observed in the ccBioz signals. This shows the potential of ccECG and ccBioz for use in long-term monitoring without adding discomfort to the patient or user. Sleep-related applications as well as more generic cardiorespiratory monitoring in (patient) beds are obvious applications, but also other daily life monitoring can be done using a similar approach (e.g. in seats).