Article ; Online: Wearable Respiration Monitoring: Interpretable Inference With Context and Sensor Biomarkers.
IEEE journal of biomedical and health informatics
2021 Volume 25, Issue 6, Page(s) 1938–1948
Abstract: Continuous monitoring of breathing rate (BR), minute ventilation (VE), and other respiratory parameters could transform care for and empower patients with chronic cardio-pulmonary conditions, such as asthma. However, the clinical standard for measuring ... ...
| Abstract | Continuous monitoring of breathing rate (BR), minute ventilation (VE), and other respiratory parameters could transform care for and empower patients with chronic cardio-pulmonary conditions, such as asthma. However, the clinical standard for measuring respiration, namely Spirometry, is hardly suitable for continuous use. Wearables can track many physiological signals, like ECG and motion, yet respiration tracking faces many challenges. In this work, we infer respiratory parameters from wearable ECG and wrist motion signals. We propose a modular and generalizable classification-regression pipeline to utilize available context information, such as physical activity, in learning context-conditioned inference models. Novel morphological and power domain features from the wearable ECG are extracted to use with these models. Exploratory feature selection methods are incorporated in this pipeline to discover application-driven interpretable biomarkers. Using data from 15 subjects, we evaluate two implementations of the proposed inference pipeline: for BR and VE. Each implementation compares generalized linear model, random forest, support vector machine, Gaussian process regression, and neighborhood component analysis as regression models. Permutation, regularization, and relevance determination methods are used to rank the ECG features to identify robust ECG biomarkers across models and activities. This work demonstrates the potential of wearable sensors not only in continuous monitoring, but also in designing biomarker-driven preventive measures. |
|---|---|
| MeSH term(s) | Biomarkers ; Humans ; Monitoring, Physiologic ; Respiration ; Respiratory Rate ; Wearable Electronic Devices ; Wrist |
| Chemical Substances | Biomarkers |
| Language | English |
| Publishing date | 2021-06-04 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S. |
| ZDB-ID | 2695320-1 |
| ISSN | 2168-2208 ; 2168-2194 |
| ISSN (online) | 2168-2208 |
| ISSN | 2168-2194 |
| DOI | 10.1109/JBHI.2020.3035776 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
More links
Kategorien
In stock of ZB MED Cologne/Königswinter
| Zs.A 5483: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
Order via subito
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.