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Assessing ECG signal quality on a coronary care unit

Lookup NU author(s): Professor John AllenORCiD, Emeritus Professor Alan MurrayORCiD

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Abstract

Poor electrocardiograph (EGG) signal quality is associated with an increase in the number of false alarms, may degrade diagnostic information, and can increase the workload for coronary care unit (CCU) or other intensive care staff. It is important therefore to establish simple quantitative measures that can be used to demonstrate signal quality problems. In this study, a fixed-gain diagnostic bandwidth ECG from patients in a single CCU bed was monitored continuously for 10 weeks and measures which could relate to quality were calculated. These measures were the number of times the ECG exceeded a preset limit (out-of-range events, +/-4 mV) and the frequency content of the ECG plus superimposed noise in six different bandwidths (0.05-0.25, 0.25-10, 10-20, 20-48, 48-52, and 52-100 Hz). A computer-based data collection system calculated a 10 s average for each of the measures and logged these to memory. Following the data collection phase, good-quality baseline levels for the seven measures were calculated for each of the days studied and compared with levels during the evening-night (6 pm-6 am), which were in turn compared with levels during the day-time (6 am-6 pm). All measures were significantly lower (p < 0.001) for the selected good-quality ECGs compared with those recorded during the night, with low frequency, lower ECG bandwidth, and out-of-range events producing the greatest differences. Night-time noise levels were lower than day-time levels, and the largest reductions were found in the rate of out-of-range events (19.8 to 9.3 h(-1)) (p < 0.02), and low-frequency content less than 0.25 Hz (70 to 56 mu V) (p < 0.01). Significant reductions during the night were also found in the lower ECG bandwidth 0.25-10 Hz (111 to 98 mu V) (p < 0.01). ND significant changes were found in the higher frequencies. We conclude that the low-frequency content and rate of out-of-range events are easy to obtain and could be used as measures for evaluating signal quality.


Publication metadata

Author(s): Allen J, Murray A

Publication type: Article

Publication status: Published

Journal: Physiological Measurement

Year: 1996

Volume: 17

Issue: 4

Pages: 249-258

Print publication date: 01/11/1996

ISSN (print): 0967-3334

ISSN (electronic): 1361-6579

URL: http://dx.doi.org/10.1088/0967-3334/17/4/002

DOI: 10.1088/0967-3334/17/4/002

PubMed id: 8953623


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