The assessment of signal quality has been a research topic since the late 1970s, as it is mainly related to the problem of false alarms in bedside monitors in the intensive care unit (ICU), the incidence of which can be as high as 90 %, leading to alarm fatigue and a drop in the overall level of nurses and clinicians attention. The development of efficient algorithms for the quality control of long diagnostic electrocardiographic (ECG) recordings, both single- and multi-lead, and of the arterial blood pressure (ABP) signal is therefore essential for the enhancement of care quality. The ECG signal is often corrupted by noise, which can be within the frequency band of interest and can manifest similar morphologies as the ECG itself. Similarly to ECG, also the ABP signal is often corrupted by non-Gaussian, nonlinear and non-stationary noise and artifacts, especially in ICU recordings. Moreover, the reliability of several important parameters derived from ABP such as systolic blood pressure or pulse pressure is strongly affected by the quality of the ABP waveform. In this work, several up-to-date algorithms for the quality scoring of a single- or multi-lead ECG recording, based on time-domain approaches, frequency-domain approaches or a combination of the two will be reviewed, as well as methods for the quality assessment of ABP. Additionally, algorithms exploiting the relationship between ECG and pulsatile signals, such as ABP and photoplethysmographic recordings, for the reduction in the false alarm rate will be presented. Finally, some considerations will be drawn taking into account the large heterogeneity of clinical settings, applications and goals that the reviewed algorithms have to deal with.
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This research was supported by the Shockomics Grant (FP7 EU Project No 602706).
Conflict of interest
The authors declare that there are no conflicts of interest.
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Gambarotta, N., Aletti, F., Baselli, G. et al. A review of methods for the signal quality assessment to improve reliability of heart rate and blood pressures derived parameters. Med Biol Eng Comput 54, 1025–1035 (2016). https://doi.org/10.1007/s11517-016-1453-5
- False alarm detection
- Signal quality
- Arterial blood pressure
- Heart rate