Assessing Effect of Beat Detector on Detection Dependent Signal Quality Indices

Daluwatte, Chathuri; Johannesen, Lars; Galeotti, Loriano; Vicente, José; Strauss, David G.; Scully, Christopher G.

doi:10.22489/cinc.2016.267-273

Cited by 1 publication

(3 citation statements)

References 11 publications

(16 reference statements)

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“…This is why there is a considerable intersection between this subgroup and the “avoidance of false arrhythmia alarms” subgroup (see Section 3.3.1 ). Specifically, ( 78 – 82 , 84 , 85 , 88 , 94 ) are using SQIs and are part of the PhysioNet / CinC Challenge 2015; ( 61 , 66 ) are using SQIs and are also part of the arrhythmia subgroup although not directly associated with the PhysioNet / CinC Challenge 2015; and ( 43 , 60 , 63 ) are dealing with SQIs and do not directly aim at arrhythmia alarms.…”

Section: Resultsmentioning

confidence: 99%

“…Daluwatte et al ( 63 ) assesses the effect of the beat detector on ECG SQIs. This is relevant because some SQIs require knowledge about the heartbeat positions in the ECG recording to make an assessment.…”

Section: Resultsmentioning

confidence: 99%

“…This data set contains physiological signals preceding arrhythmia alarms which is extremely relevant in terms of alarm fatigue especially concerning the improvement of technical correctness of alarms (35). Besides the submission to the challenge described in Section 3.3.1, the following publications are also using this data set: (61)(62)(63)(64)(65)(66)(67)(68) for their decisions. Further applied explainable models are logistic regression (LR), fuzzy logic and case-based reasoning (CBR).…”

Section: Datamentioning

confidence: 99%

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Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review

Chromik

Klopfenstein

Pfitzner

et al. 2022

Front. Digit. Health

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Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large amounts of technically false or clinically irrelevant alarms provoke alarm fatigue in staff leading to desensitisation towards critical alarms. With this systematic review, we are following the Preferred Reporting Items for Systematic Reviews (PRISMA) checklist in order to summarise scientific efforts that aimed to develop IT systems to reduce alarm fatigue in ICUs. 69 peer-reviewed publications were included. The majority of publications targeted the avoidance of technically false alarms, while the remainder focused on prediction of patient deterioration or alarm presentation. The investigated alarm types were mostly associated with heart rate or arrhythmia, followed by arterial blood pressure, oxygen saturation, and respiratory rate. Most publications focused on the development of software solutions, some on wearables, smartphones, or headmounted displays for delivering alarms to staff. The most commonly used statistical models were tree-based. In conclusion, we found strong evidence that alarm fatigue can be alleviated by IT-based solutions. However, future efforts should focus more on the avoidance of clinically non-actionable alarms which could be accelerated by improving the data availability.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233461, identifier: CRD42021233461.

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