General Purpose Adaptive Biosignal Acquisition System Combining FPGA and FPAA

Mou, Pedro Antonio; Chen, Chang Hao; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I

doi:10.1007/978-3-540-92841-6_8

Cited by 4 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The node was designed and implemented using two instrumentation amplifiers, two fourth order Sallen-Key filters, a two channel A/D converter, an Actel's Flash based FPGA and additional communication circuitry. The paper described in [10], introduces a general purpose, dynamically reconfigurable, adaptive biosignal acquisition system, for processing various biosignals like ECG, EMG and EEG, etc., using FPGA. An FPGA based implementation of adaptive noise canceller (50/60 -Hz) in electrocardiography has been addressed in [11].…”

Section: Introductionmentioning

confidence: 99%

Real time electrocardiogram wave peak detection algorithm and its implementation on FPGA

Chatterjee¹,

Gupta

Mitra

2014

Proceedings of the 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC)

View full text Add to dashboard Cite

A real time Electrocardiogram wave peak detection algorithm with low latency has been developed. It can detect different component wave peaks, viz., P, Q, R, S and T from digitized samples. The algorithm has been implemented using Xilinx Spartan-III xc3s400tq144-5 FPGA module. For the purpose of detection of ECG wave peaks, during a training period of 6 second, a slope and polarity based signature is learned from the incoming ECG signal, which is sampled at 1 kHz frequency. These detected signatures of individual wave peaks of the concerned are then used for detection of subsequent individual component wave peaks. R, T and P waves are detected with 98.8%, 97.98% and 97.75% respectively using ptbdb and mitdb data from Physionet. The design consumed 35% resources of FPGA.

show abstract

Section: Introductionmentioning

confidence: 99%