title: A 0.83- μW QRS detection processor using quadratic spline wavelet transform for wireless ECG acquisition in 0.35- μm CMOS.
abstract: Healthcare electronics count on the effectiveness of the on-patient signal preprocessing unit to moderate the wireless data transfer for better power efficiency. In order to reduce the system power in long-time ECG acquisition, this work describes an on-patient QRS detection processor for arrhythmia monitoring. It extracts the concerned ECG part, i.e., the RR-interval between the QRS complex for evaluating the heart rate variability. The processor is structured by a scale-3 quadratic spline wavelet transform followed by a maxima modulus recognition stage. The former is implemented via a symmetric FIR filter, whereas the latter includes a number of feature extraction steps: zero-crossing detection, peak (zero-derivative) detection, threshold adjustment and two finite state machines for executing the decision rules. Fabricated in 0.35-μm CMOS the 300-Hz processor draws only 0.83 μW, which is favorably comparable with the prior arts. In the system tests, the input data is placed via an on-chip 10-bit SAR analog-to-digital converter, while the output data is emitted via an off-the-shelf wireless transmitter (TI CC2500) that is configurable by the processor for different data transmission modes: 1) QRS detection result, 2) raw ECG data or 3) both. Validated with all recordings from the MIT-BIH arrhythmia database, 99.31% sensitivity and 99.70% predictivity are achieved. Mode 1 with solely the result of QRS detection exhibits 6× reduction of system power over modes 2 and 3.
authors.affiliation: Department of Electrical and Computer Engineering, Faculty of Science and Technology,University of Macau, Taipa, Macao 999078, China. ciieong@umac.mo
authors.forename: Chio-In
authors.initials: CI
authors.lastname: Ieong
authors.forename: Pui-In
authors.initials: PI
authors.lastname: Mak
authors.forename: Chi-Pang
authors.initials: CP
authors.lastname: Lam
authors.forename: Cheng
authors.initials: C
authors.lastname: Dong
authors.forename: Mang-I
authors.initials: MI
authors.lastname: Vai
authors.forename: Peng-Un
authors.initials: PU
authors.lastname: Mak
authors.forename: Sio-Hang
authors.initials: SH
authors.lastname: Pun
authors.forename: Feng
authors.initials: F
authors.lastname: Wan
authors.forename: Rui P
authors.initials: RP
authors.lastname: Martins
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis; D001698:Biomedical Engineering; D016208:Databases, Factual; D015716:Electrocardiography, Ambulatory / Q000295:instrumentation* / Q000706:statistics & numerical data; D004867:Equipment Design; D006339:Heart Rate; D006801:Humans; D011237:Predictive Value of Tests; D012666:Semiconductors; D058067:Wavelet Analysis; D059015:Wireless Technology / Q000295:instrumentation