TY - GEN
T1 - Efficient implementation of Stockwell Transform for real-time embedded processing of physiologic signals
AU - Holmes, David
AU - Pinto, Samuel Cerqueira
AU - Felton, Christopher
AU - Smital, Lukas
AU - Leinveber, Pavel
AU - Jurak, Pavel
AU - Gilbert, Barry
AU - Haider, Clifton
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/13
Y1 - 2017/9/13
N2 - Physiologic monitoring enables scientists and physicians to study both normal and pathologic signals of the body. While wearable technologies are available today, many of these technologies are limited to data collection only. Embedded processors have minimal computational capabilities. We propose an efficient implementation of the Stockwell Transform which can enable real-time time-frequency analysis of biological signals in a microcontroller. The method is built upon the fact that the Stockwell Transform can be implemented as a compact filter bank with pre-computed filter taps. Additionally, due to the long tails of the gaussian windowing function, low amplitude filter taps can be removed. The method was implemented on a TI MSP430 processor. Simulated ECG data was fed into the processor to demonstrate performance and evaluate computational efficiency.
AB - Physiologic monitoring enables scientists and physicians to study both normal and pathologic signals of the body. While wearable technologies are available today, many of these technologies are limited to data collection only. Embedded processors have minimal computational capabilities. We propose an efficient implementation of the Stockwell Transform which can enable real-time time-frequency analysis of biological signals in a microcontroller. The method is built upon the fact that the Stockwell Transform can be implemented as a compact filter bank with pre-computed filter taps. Additionally, due to the long tails of the gaussian windowing function, low amplitude filter taps can be removed. The method was implemented on a TI MSP430 processor. Simulated ECG data was fed into the processor to demonstrate performance and evaluate computational efficiency.
UR - http://www.scopus.com/inward/record.url?scp=85032177627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032177627&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2017.8037389
DO - 10.1109/EMBC.2017.8037389
M3 - Conference contribution
C2 - 29060431
AN - SCOPUS:85032177627
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2598
EP - 2601
BT - 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Y2 - 11 July 2017 through 15 July 2017
ER -