Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor.

Journal: IEEE journal of biomedical and health informatics

PMID: 30040664

Abstract

OBJECTIVE: Utilizing passive radio frequency identification (RFID) tags embedded in knitted smart-garment devices, we wirelessly detect the respiratory state of a subject using an ensemble-based learning approach over an augmented Kalman-filtered time series of RF properties.

Authors

Sayandeep Acharya
William M Mongan

Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA 19426, USA.
Ilhaan Rasheed
Yuqiao Liu
Endla Anday
Genevieve Dion
Adam Fontecchio
Timothy Kurzweg
Kapil R Dandekar

Electrical and Computer Engineering, Drexel University, Philadelphia, PA 19104 USA.

Keywords

Algorithms Humans Infant Machine Learning Monitoring, Physiologic Radio Frequency Identification Device Respiratory Rate Signal Processing, Computer-Assisted Wearable Electronic Devices

External Resources

View on PubMed Access via DOI PubMed (30040664)

Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor.

Abstract

Authors

Keywords

External Resources

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