TY - GEN
T1 - Effects of non-uniform quantization on ECG acquired using compressed sensing
AU - Craven, Darren
AU - McGinley, Brian
AU - Kilmartin, Liam
AU - Glavin, Martin
AU - Jones, Edward
N1 - Publisher Copyright:
© 2014 ICST.
PY - 2015/1/20
Y1 - 2015/1/20
N2 - This paper analyzes the effects of quantization on Compressed Sensing (CS) measurements applied to Electrocardiogram (ECG) signals. Two methods of quantization are proposed in this paper: uniform and non-uniform. Reconstruction is performed using a dictionary based on the Mexican Hat wavelet. A distortion-based performance metric Percent Root-mean-squared Difference (PRD) will be monitored at various Compression Ratios (CR) to quantify the impact of quantization. The energy cost of transmission is also evaluated for different levels of quantization and compared, at certain PRD levels. The results demonstrate that non-uniform quantization outperforms the uniform approach and that employing nonuniform quantization improves implementation efficiency for applications with acceptable PRDs above 6.75%. Results show that utilizing non-uniform quantization can increase the CR from 9.8 to 14.1 for a PRD of 30%. Furthermore, this amounts to a 28.91% reduction in wireless transmission per frame from 37.7 μJ to 26.8 μJ considering Bluetooth Low Energy (BLE) as a target wireless communication protocol.
AB - This paper analyzes the effects of quantization on Compressed Sensing (CS) measurements applied to Electrocardiogram (ECG) signals. Two methods of quantization are proposed in this paper: uniform and non-uniform. Reconstruction is performed using a dictionary based on the Mexican Hat wavelet. A distortion-based performance metric Percent Root-mean-squared Difference (PRD) will be monitored at various Compression Ratios (CR) to quantify the impact of quantization. The energy cost of transmission is also evaluated for different levels of quantization and compared, at certain PRD levels. The results demonstrate that non-uniform quantization outperforms the uniform approach and that employing nonuniform quantization improves implementation efficiency for applications with acceptable PRDs above 6.75%. Results show that utilizing non-uniform quantization can increase the CR from 9.8 to 14.1 for a PRD of 30%. Furthermore, this amounts to a 28.91% reduction in wireless transmission per frame from 37.7 μJ to 26.8 μJ considering Bluetooth Low Energy (BLE) as a target wireless communication protocol.
KW - Ambulatory monitoring
KW - Biomedical signal compression
KW - Compressed sensing (CS)
KW - Electrocardiogram (ECG)
KW - Quantization
UR - https://www.scopus.com/pages/publications/84925355831
U2 - 10.1109/MOBIHEALTH.2014.7015914
DO - 10.1109/MOBIHEALTH.2014.7015914
M3 - Conference Publication
AN - SCOPUS:84925355831
T3 - Proceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming Healthcare Through Innovations in Mobile and Wireless Technologies", MOBIHEALTH 2014
SP - 79
EP - 82
BT - Proceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming Healthcare Through Innovations in Mobile and Wireless Technologies", MOBIHEALTH 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Wireless Mobile Communication and Healthcare, MOBIHEALTH 2014
Y2 - 3 November 2014 through 5 November 2014
ER -