Overlapping medical alarms are almost indiscriminable

Objective: We explore how accurately and quickly nurses can identify melodic medical equipment alarms when no mnemonics are used, when alarms may overlap, and when concurrent tasks are performed. Background: The international standard IEC 60601-1-8 (International Electrotechnical Commission, 2005) has proposed simple melodies to distinguish seven alarm sources. Previous studies with nonmedical participants reveal poor learning of melodic alarms and persistent confusions between some of them. The effects of domain expertise, concurrent tasks, and alarm overlaps are unknown. Method: Fourteen intensive care and general medical unit nurses learned the melodic alarms without mnemonics in two sessions on separate days. In the second half of Day 2 the nurses identified single alarms or pairs of alarms played in sequential, partially overlapping, or nearly completely overlapping configurations. For half the experimental blocks nurses performed a concurrent mental arithmetic task. Results: Nurses' learning was poor and was no better than the learning of nonnurses in a previous study. Nurses showed the previously noted confusions between alarms. Overlapping alarms were exceptionally difficult to identify. The concurrent task affected response time but not accuracy. Conclusion: Because of a failure of auditory stream segregation, the melodic alarms cannot be discriminated when they overlap. Directives to sequence the sounding of alarms in medical electrical equipment must be strictly adhered to, or the alarms must redesigned to support better auditory streaming. Application: Actual or potential uses of this research include the implementation of IEC 60601-1-8 alarms in medical electrical equipment.

Learnability and discriminability of melodic medical equipment alarms

Melodic alarms proposed in the IEC 60601-1-8 standard for medical electrical equipment were tested for learnability and discriminability. Thirty-three non-anaesthetist participants learned the alarms over two sessions of practice, with or without mnemonics suggested in the standard. Fewer than 30% of participants could identify the alarms with 100% accuracy at the end of practice. Confusions persisted between pairs of alarms, especially if mnemonics were used during learning (p = 0.011). Participants responded faster (p < 0.00001) and more accurately (p = 0.002) to medium priority alarms than to high priority alarms, even though they rated the high priority alarms as sounding more urgent (p < 0.00001). Participants with at least 1 year of formal musical training identified the alarms more accurately (p = 0.0002) than musically untrained participants, and found the task easier overall (p < 0.00001). More intensive studies of the IEC 60601-1-8 alarms are needed for their effectiveness to be determined.

Reducing SCADA System Nuisance Alarms in the Water Industry in Northern Ireland

The advancement of telemetry control for the water industry has increased the difficulty of 14 managing large volumes of nuisance alarms (i.e. alarms that do not require a response). The aim 15 of this study was to identify and reduce the number of nuisance alarms that occur for Northern 16 Ireland (NI) Water by carrying-out alarm duration analysis to determine the appropriate length of 17 persistence (an advanced alarm management tool) that could be applied. All data was extracted 18 from TelemWeb (NI Water’s telemetry monitoring system) and analysed in Excel. Over a 6 19 week period, an average of 40,000 alarms occurred per week. The alarm duration analysis, which 20 has never been implemented before by NI Water, found that an average of 57% of NI Water 21 alarms had a duration of <5 minutes. Applying 5 minute persistence; therefore, could prevent an 22 average 26,816 nuisance alarms per week. Most of these alarms were from wastewater assets.

Optimal alarms systems and its application to financial time series

This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.

Roll Call for Fires and Alarms for Citizens' Hose Company No. 1

Roll call for fires and alarms for Citizens’ Hose Company No. 1. (1 double sided printed page). H.K. Woodruff is listed as a member, 1883.

An immunological approach to raising alarms in video surveillance

Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three detectors for detecting abnormal activity are generated using negative selection. Tracks gathered by people’s movements in a room are used for experimentation and results have shown that the classifier is able to discriminate abnormal from normal activities in terms of both trajectory and time spent at a location.

An immunological approach to raising alarms in video surveillance

Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three types of detectors for detecting abnormal activity are developed using negative selection. Tracks gathered by people's movements in a room are used for experimentation and results have shown that the classifier is able to discriminate abnormal from normal activities in terms of both trajectory and time spent at a location.

False alarms in damage detection approaches

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in structures in order to improve reliability and reduce life-cycle costs. The greatest challenge for designing a SHM system is knowing what changes to look for and how to classify them. Different approaches for SHM have been proposed for damage identification, each one with advantages and drawbacks. This paper presents a methodology for improvement in vibration signal analysis using statistics information involving the probability density. Generally, the presence of noises in input and output signals results in false alarms, then, it is important that the methodology can minimize this problem. In this paper, the proposed approach is experimentally tested in a flexible plate using a piezoelectric (PZT) actuator to provide the disturbance.

Alarms and discursions,

First published, 1910.

Tailoring reveals information requirements: the case of anaesthesia alarms

We discuss the phenomenon of system tailoring in the context of data from an observational study of anaesthesia. We found that anaesthetists tailor their monitoring equipment so that the auditory alarms are more informative. However, the occurrence of tailoring by anaesthetists in the operating theatre was infrequent, even though the flexibility to tailor exists on many of the patient monitoring systems used in the study. We present an influence diagram to explain how alarm tailoring can increase situation awareness in the operating theatre but why factors inhibiting tailoring prevent widespread use. Extending the influence diagram, we discuss ways that more informative displays could achieve the results sought by anaesthetists when they tailor their alarm systems. In particular, we argue that we should improve our designs rather than simply provide more flexible tailoring systems. because users often find tailoring a complex task. We conclude that properly designed auditory displays may benefit anaesthetists in achieving greater patient situation awareness and that designers should consider carefully how factors promoting and inhibiting tailoring will affect the end-users' likelihood of conducting tailoring. (C) 2004 Elsevier B.V. All rights reserved.

Learnability and discriminability of melodic medical equipment alarms

Melodic alarms proposed in the IEC 60601-1-8 standard for medical electrical equipment were tested for learnability and discriminability. Thirty-three non-anaesthetist participants learned the alarms over two sessions of practice, with or without mnemonics suggested in the standard. Fewer than 30% of participants could identify the alarms with 100% accuracy at the end of practice. Confusions persisted between pairs of alarms, especially if mnemonics were used during learning (p = 0.011). Participants responded faster (p < 0.00001) and more accurately (p = 0.002) to medium priority alarms than to high priority alarms, even though they rated the high priority alarms as sounding more urgent (p < 0.00001). Participants with at least 1 year of formal musical training identified the alarms more accurately (p = 0.0002) than musically untrained participants, and found the task easier overall (p < 0.00001). More intensive studies of the IEC 60601-1-8 alarms are needed for their effectiveness to be determined.