Name
Title | ||
|---|---|---|
On the Design of a Physiological Signal Feature Extraction and Segmentation Digital Subsystem |
Abstract | ||
|---|---|---|
Real-time and compact algorithms are desired for wearable physiologic monitoring devices. We present a QRS waveform detection algorithm, inspired by the Stockwell time-frequency transform and targeted to embedded architectures. The proposed QRS detector uses a complex filter for feature extraction and efficient estimations to achieve minimal computations and limited digital hardware resources. The QRS detector algorithm is demonstrated to reduce the computational cost and maintain accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACSSC.2018.8645139 | 2018 52nd Asilomar Conference on Signals, Systems, and Computers |
Keywords | Field | DocType |
Detectors,Feature extraction,Optimization,Transforms,Sensitivity,Entropy,Biomedical monitoring | Computer vision,Segmentation,Computer science,Wearable computer,Waveform,Feature extraction,Electronic engineering,Artificial intelligence,QRS complex,Complex filter,Detector,Computation | Conference |
ISSN | ISBN | Citations |
1058-6393 | 978-1-5386-9218-9 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christopher L. Felton | 1 | 0 | 0.34 |
| Barry K. Gilbert | 2 | 30 | 9.12 |
| David R Holmes | 3 | 42 | 20.31 |
| clifton r haider | 4 | 2 | 2.74 |