Alarm Design Research Articles

Creation of a novel microburst alarm for Air Traffic Control using a signal design framework

In this study, we used a previously validated alarm design framework to design and test a new microburst alarm for air traffic controllers. MethodsTwo air traffic controllers participated in a detailed structured interview, describing aspects of the current alarm that worked well and identifying features that should be changed. They then chose the properties most important to the design of this specific alarm. This information was used to develop a prototype microburst alarm while making iterative changes. A short interview asking about those properties was then conducted with sixty-two controllers at a national conference. ResultsWe developed an effective microburst alarm using the Signal Design Framework. Informativeness, Distinguishability, Saliency, Disruptiveness, Exclusivity, and Recognizability were improved by adding an electronically accelerated verbal component (‘Microburst!’) to the beginning and midway through the alert. The tonal component, volume, and timing of the prototype alarm were similar to that of the original alarm. During the alarm testing phase, most controllers agreed that the prototype would work well in both Air Traffic Control Tower and TRACON environments. Controllers agreed that incorporating an audible ‘Microburst!’ helped to direct their attention to the source of the alarm, especially in facilities where this alarm is uncommon. Controllers also spoke favorably of the length, pitch, oscillation, and timbre of the auditory component. ConclusionsWe used a validated framework to develop a new alarm that would work well for controllers in their environment. The framework facilitated design, iterative testing, and large-scale evaluation.

Exploring the Influence of Human System Interfaces: Introducing Support Tools and an Experimental Study

Situational awareness and decision support tools such as procedures and alarm systems are vital for effective interaction among control room operators, especially in safety-critical situations. In safety-critical environments such as process plants, there remains a gap in evaluating specific tools during actual operations, or ”work-as-done.” Additionally, the underlying factors that might impact operators’ cognitive states and performance concerning safety have not been thoroughly explored. The need for such an evaluation is further bolstered by current interaction configurations where operators are more passive than active, thus reducing their cognitive performance. Therefore, this experimental study addresses the highlighted evaluation gap by introducing and comparing three human system interfaces/decision support tools in four human-in-the-loop configurations. The supports include two alarm design formats (prioritized vs. non-prioritized) and three procedure representation formats (paper, screen-based digitized, and an AI-based support system built with an integrated Bayesian network and reinforcement learning model). Ninety-two people (n = 92) participated voluntarily in the test. They were divided equally into four groups. Each group tested three safety-related events in a simulated formaldehyde production facility. Individuals belonging to the group with prioritized alarms and utilized paper procedures rated procedural support slightly higher on average than others in different groups. Unlike the other groups, their assessment of alarm prioritization support remained consistent across all scenarios. Further analysis of the impact of the setup on cognitive states and actual performance will be performed.

Design of anti-theft alarm and fire detection system based on IoT cloud platform

This time for a STM 32 single chip computer as the core of the intelligent home system of anti-theft alarm system for a detailed design, It aims to provide a comprehensive understanding of the hardware composition, software design and implementation principles of the smart home system, And analyze its advantages and disadvantages, Thus better providing intelligent early warning for human beings, Prevent the emergence of emergencies, Saving the lives and property of the people, The security information of the user can be monitored remotely, It can also turn it off via a button, In the anti-theft mode, You can also use an infrared sensor module installed in the human body to detect whether there is anyone in the home, So as to achieve the purpose of fire and fire prevention and theft. On this basis, a residential intelligent management system based on wireless communication is designed. The OLED LCD screen can display the currently detected temperature and the density of the flue gas, and use the button to set an upper alarm limit. When the detected temperature or smoke content exceeds the upper limit, the LED indicator light will light up and issue an alarm. Also, there is an emergency button to send out a distress signal at any time.

Pro-Con Debate: Universal Versus Selective Continuous Monitoring of Postoperative Patients.

In this Pro-Con commentary article, we discuss use of continuous physiologic monitoring for clinical deterioration, specifically respiratory depression in the postoperative population. The Pro position advocates for 24/7 continuous surveillance monitoring of all patients starting in the postanesthesia care unit until discharge from the hospital. The strongest arguments for universal monitoring relate to inadequate assessment and algorithms for patient risk. We argue that the need for hospitalization in and of itself is a sufficient predictor of an individual's risk for unexpected respiratory deterioration. In addition, general care units carry the added risk that even the most severe respiratory events will not be recognized in a timely fashion, largely due to higher patient to nurse staffing ratios and limited intermittent vital signs assessments (e.g., every 4 hours). Continuous monitoring configured properly using a "surveillance model" can adequately detect patients' respiratory deterioration while minimizing alarm fatigue and the costs of the surveillance systems. The Con position advocates for a mixed approach of time-limited continuous pulse oximetry monitoring for all patients receiving opioids, with additional remote pulse oximetry monitoring for patients identified as having a high risk of respiratory depression. Alarm fatigue, clinical resource limitations, and cost are the strongest arguments for selective monitoring, which is a more targeted approach. The proponents of the con position acknowledge that postoperative respiratory monitoring is certainly indicated for all patients, but not all patients need the same level of monitoring. The analysis and discussion of each point of view describes who, when, where, and how continuous monitoring should be implemented. Consideration of various system-level factors are addressed, including clinical resource availability, alarm design, system costs, patient and staff acceptance, risk-assessment algorithms, and respiratory event detection. Literature is reviewed, findings are described, and recommendations for design of monitoring systems and implementation of monitoring are described for the pro and con positions.

Exploration of multimodal alarms for civil aircraft flying task: A laboratory study

AbstractOwing to the increasing amount of information presented in the cockpit, the visual and hearing channels are unable to adequately transmit information, which may increase the mental load on pilots. This study explores the benefits of multimodal alarms under high and low residual capacities during take‐off in civil aircrafts in a quasi‐experimental study. The performance of two modes of multimodal (visual and auditory [VA], and visual, auditory, and tactile [VAT]) alarms were tested. The results showed that the VAT alarms were superior to the VA alarms in terms of choice response times (CRTs) when the participants were exposed to low residual capacities of vision and hearing. However, this effect was not observed when the participants had high residual capacities for vision and hearing. Thus, we considered that an additional tactile alarm could play a significant role in the CRTs when VA resources were consumed. There was no significant difference in the number of response errors between the three multimodal alarm modes. This study provides a key comparison of the two modes of multimodal alarms, indicating that VAT alarms are ideal for use in alarm design strategies for next‐generation civil cockpits.

Validation of a new method for designing air traffic control alarms

Alarms, alerts, and warnings are critical to maintaining safety in the National Airspace System and should be designed to support aircraft separation as well as supplementary tasks such as weather avoidance. The purpose of this study is to validate a novel alarm design framework by asking air traffic controllers to evaluate an existing alarm. MethodsWe invited four air traffic controllers to participate in a structured interview that is part of a novel Signal Design Framework. Controllers were asked a series of scripted questions about 15 specific alarm properties. They were then asked to choose the three properties most important to the design of the conflict alert. Lastly, controllers were asked a series of questions about the overall quality of the taxonomy and its potential for impacting aviation safety. ResultsAll participants agreed that the taxonomy captured all the important characteristics of an alarm and that no gaps or failures existed in the alarm framework. They also agreed that the framework was easy to understand, that the structured interview was easy to understand, and that applying the framework to alarm design and revision would improve alarm ease of use, reduce confusion, and improve overall safety. ConclusionsThe structured interview encouraged controllers to think about the Conflict Alert and helped them to develop novel solutions that could potentially improve this alarm in the Air Traffic Control environment.

A Spatiotemporal and Multisensory Approach to Designing Wearable Clinical ICU Alarms.

In health care, auditory alarms are an important aspect of an informatics system that monitors patients and alerts clinicians attending to multiple concurrent tasks. However, the volume, design, and pervasiveness of existing Intensive Care Unit (ICU) alarms can make it difficult to quickly distinguish their meaning and importance. In this study, we evaluated the effectiveness of two design approaches not yet explored in a smartwatch-based alarm system designed for ICU use: (1) using audiovisual spatial colocalization and (2) adding haptic (i.e., touch) information. We compared the performance of 30 study participants using ICU smartwatch alarms containing auditory icons in two implementations of the audio modality: colocalized with the visual cue on the smartwatch's low-quality speaker versus delivered from a higher quality speaker located two feet away from participants (like a stationary alarm bay situated near patients in the ICU). Additionally, we compared participant performance using alarms with two sensory modalities (visual and audio) against alarms with three sensory modalities (adding haptic cues). Participants were 10.1% (0.24s) faster at responding to alarms when auditory information was delivered from the smartwatch instead of the higher quality external speaker. Meanwhile, adding haptic information to alarms improved response times to alarms by 12.2% (0.23s) and response times on their primary task by 10.3% (0.08s). Participants rated learnability and ease of use higher for alarms with haptic information. These small but statistically significant improvements demonstrate that audiovisual colocalization and multisensory alarm design can improve user response times.

Robust alarm design strategy for medical devices: Application to air-in-line detection and occlusion management

Alarm fatigue in the hospital environment is a recurring problem that can be solved through technical, human, or organizational considerations. The use of technical factors to get a robust alarm management system is illustrated here by two case studies related to air-in-line detection in peritoneal dialysis and insulin pump occlusion management. Air-in-line sensors are usually very sensitive to the presence of small bubbles stuck on tubing and may therefore deliver false alarms. To provide a reliable estimate of the cumulated air volume pumped an IR sensor technology that is insensitive to small bubbles was implemented and tested. Another strategy was used to limit false occlusion alarms in an insulin patch pump. The piezoelectric actuator of this micropump was servo-controlled to the pressure sensor signal to allow insulin to flow into the patient despite the presence of a partial occlusion. The false alarm rate is thus reduced by using a self-adaptive occlusion detection threshold that has been evaluated using numerical simulations.

Considerations for transient operation—Fire incident

AbstractThis is the story of a root cause analysis (RCA) for a fire in a chemical operation during a transient operation. Findings from this investigation illustrate the hazards and key preventative measures that can be utilized to prevent this type of incident. It also illustrates how abnormal or transient operations should be considered in process design and procedure development. Results from the RCA and the lessons learned will be explained. Several aspects will be discussed including a number of latent factors, multiple design, and procedural issues, identification of potential scenarios in safety reviews, and design of controls and alarms.

Improving auditory alarms: Reducing perceived annoyance with musical timbre (a randomized trial)

BackgroundAuditory alarms in medical environments are widely criticized due to problematic design issues affecting learnability, recognition, and annoyance. To overcome these issues, new alarm sets vary properties like pitch, timing, and timbre—the “quality” of a sound. Past work identifies timbre as a promising candidate for improving alarm recognition, however most studies manipulate multiple acoustic parameters, obfuscating the independent effect of timbre on melodic perception. MethodsTo better understand timbre's potential for improving alarm recognizability and reducing annoyance, we recruited forty-four participants for a melody recognition experiment. In a learning phase, participants learned short alarm melodies performed with either a complex musical timbre based on a xylophone or one following the specifications of a universal alarm standard. During a recall phase, participants heard the melodies again presented in either the xylophone or standard timbre and attempted to identify the corresponding label for each alarm. Afterward, participants heard alarm pairs presented in both timbres and chose which one they perceived to be more annoying. ResultsParticipants recalled xylophone alarm melodies with comparable accuracy to the standard timbre, however they found the musical timbre substantially less annoying. Regardless of the timbre at exposure, recognition of familiar melodies decreased if the timbre changed between learning and recall. ConclusionsWe compared the recognizability and annoyance of alarm melodies presented in either a standard alarm timbre or a synthesized xylophone timbre. Our findings reveal musical sounding alarms are comparably recognizable, yet significantly less annoying than alarm signals common in medical environments. These outcomes provide a promising first step to improving patient care through musically informed alarm design.

Multisensory alarm to benefit alarm identification and decrease workload: a feasibility study.

The poor design of conventional auditory medical alarms has contributed to alarm desensitization, and eventually, alarm fatigue in medical personnel. This study tested a novel multisensory alarm system which aims to help medical personnel better interpret and respond to alarm annunciation during periods of high cognitive load such as those found within intensive care units. We tested a multisensory alarm that combined auditory and vibrotactile cues to convey alarm type, alarm priority, and patient identity. Testing was done in three phases: control (conventional auditory), Half (limited multisensory alarm), and Full (complete multisensory alarm). Participants (N = 19, undergraduates) identified alarm type, priority, and patient identity (patient 1 or 2) using conventional and multisensory alarms, while simultaneously completing a cognitively demanding task. Performance was based on reaction time (RT) and identification accuracy of alarm type and priority. Participants also reported their perceived workload. RT was significantly faster for the Control phase (p < 0.05). Participant performance in identifying alarm type, priority, and patient did not differ significantly between the three phase conditions (p = 0.87, 0.37, and 0.14 respectively). The Half multisensory phase produced the lowest mental demand, temporal demand, and overall perceived workload score. These data suggest that implementation of a multisensory alarm with alarm and patient information may decrease perceived workload without significant changes in alarm identification performance. Additionally, a ceiling effect may exist for multisensory stimuli, with only part of an alarm benefitting from multisensory integration.

Unbiased estimation based multivariate alarm design considering temporal and multimodal process characteristics

In alarm systems, conventional univariate alarm methods often result in frequent false and missing alarms, calling for an urgent need to introduce multivariate information. For the multivariate alarm design, although each variable’s detection sensitivity is improved with the assistance of other variables, it is also susceptible to anomalies of other variables. Therefore, it is a challenge to properly introduce multivariate information, especially for complex processes subject to operating condition changes. This paper proposes a multivariate alarm framework that complements temporal and multimodal process characteristics to better alarm for variables by unbiased estimation. The temporal and multimodal characteristics are explored by prediction-oriented network structure and reconstruction-oriented network structure, respectively. To make them properly integrated, pattern labels that reveal the modes change are designed and used as the bridge between the temporal and the multimodal parts. On the one hand, the consideration of two types of characteristics allows perceiving temporal-related and modal-related faults, promoting sensitive alarm performance. On the other hand, unifying the two types of networks can eliminate the estimation bias of normal variables, making them unsusceptible to anomalies of other variables and promoting accurate alarm performance. Experiments on the coal mill prove the effectiveness of the proposed method regarding false alarm rate and missing alarm rate.

Informing Healthcare Alarm Design and Use: A Human Factors Cross-Industry Perspective

Background: Alarms are signals intended to capture and direct human attention to a potential issue that may require monitoring, assessment, or intervention and play a critical safety role in high-risk industries. Healthcare relies heavily on auditory and visual alarms. While there are some guidelines to inform alarm design and use, alarm fatigue and other alarm issues are challenges in the healthcare setting. Automotive, aviation, and nuclear industries have used the science of human factors to develop alarm design and use guidelines. These guidelines may provide important insights for advancing patient safety in healthcare. Methods: We identified documents containing alarm design and use guidelines from the automotive, aviation, and nuclear industries that have been endorsed by oversight agencies. These guidelines were reviewed by human factors and clinical experts to identify those most relevant to healthcare, qualitatively analyze the relevant guidelines to identify meaningful topics, synthesize the guidelines under each topic to identify key commonalities and differences, and describe how the guidelines might be considered by healthcare stakeholders to improve alarm design and use. Results: A total of 356 guidelines were extracted from industry documents (2012–present) and 327 (91.9%) were deemed relevant to healthcare. A qualitative analysis of relevant guidelines resulted in nine distinct topics: Alarm Reduction, Appropriateness, Context-Dependence, Design Characteristics, Mental Model, Prioritization, Specificity, Urgency, and User Control. There were several commonalities, as well as some differences, across industry guidelines. The guidelines under each topic were found to inform the auditory or visual modality, or both. Certain guidelines have clear considerations for healthcare stakeholders, especially technology developers and healthcare facilities. Conclusion: Numerous guidelines from other high-risk industries can inform alarm design and use in healthcare. Healthcare facilities can use the information presented as a framework for working with their technology developers to appropriately design and modify alarming technologies and can evaluate their clinical environments to see how alarming technologies might be improved.

Online Supplement to “Informing Healthcare Alarm Design and Use: A Human Factors Cross-Industry Perspective”

This supplementary material has been provided by the authors to give readers additional information about their work.

Capturing the attentional response to clinical auditory alarms: An ERP study on priority pulses.

Clinical auditory alarms are often found in hospital wards and operating rooms. In these environments, regular daily tasks can result in having a multitude of concurrent sounds (from staff and patients, building systems, carts, cleaning devices, and importantly, patient monitoring devices) which easily amount to a prevalent cacophony. The negative impact of this soundscape on staff and patients' health and well-being, as well as in their performance, demand for accordingly designed sound alarms. The recently updated IEC60601-1-8 standard, in guidance for medical equipment auditory alarms, proposed a set of pointers to distinctly convey medium or high levels of priority (urgency). However, conveying priority without compromising other features, such as ease of learnability and detectability, is an ongoing challenge. Electroencephalography, a non-invasive technique for measuring the brain response to a given stimulus, suggests that certain Event-Related Potentials (ERPs) components such as the Mismatch Negativity (MMN) and P3a may be the key to uncovering how sounds are processed at the pre-attentional level and how they may capture our attention. In this study, the brain dynamics in response to the priority pulses of the updated IEC60601-1-8 standard was studied via ERPs (MMN and P3a), for a soundscape characterised by the repetition of a sound (generic SpO2 "beep"), usually present in operating and recovery rooms. Additional behavioural experiments assessed the behavioural response to these priority pulses. Results showed that the Medium Priority pulse elicits a larger MMN and P3a peak amplitude when compared to the High Priority pulse. This suggests that, at least for the applied soundscape, the Medium Priority pulse is more easily detected and attended at the neural level. Behavioural data supports this indication, showing significantly shorter reaction times for the Medium Priority pulse. The results pose the possibility that priority pointers of the updated IEC60601-1-8 standard may not be successfully conveying their intended priority levels, which may not only be due to design properties but also to the soundscape in which these clinical alarms are deployed. This study highlights the need for intervention in both hospital soundscapes and auditory alarm design settings.

Artificial Intelligence-Assisted Prediction of Effluent Phosphorus in a Full-Scale Wastewater Treatment Plant with Missing Phosphorus Input and Removal Data

Although artificial intelligence (AI) such as machine learning (ML) and deep learning (DL) has been recognized as an emerging and promising tool, its application becomes challenging with incomplete data collection. Herein, in the absence of the influent phosphorus load and chemical dosage data for phosphorus removal, we employed ML/DL models to predict effluent phosphorus using nine-year data from a small-scale wastewater treatment plant. Attempts were made to select essential model input features from 42 variables by using Pearson correlation analysis to reveal internal correlations among variables. First, five ML regression models were used to predict the effluent phosphorus load, and a maximum coefficient of determination (R2) of 0.637 was achieved with the support vector machine model. Then, the DL model named long short-term memory could predict phosphorus load in one-day advance with an R2 value of 0.496. Finally, on the basis of the historical data, an anomaly alarm design was proposed to minimize the chance of exceeding the discharge permit and achieved a maximum accuracy of 79.7% to predict the phosphorus concentration after comparing seven ML classification models. This study provides an example of applying AI for process improvement and potential cost reduction with incomplete data sets.

Utilizing the Alarm Taxonomy and Classification System (ATACS) to Redesign Landing Gear Warnings

Alarms have been in use for many decades, yet there still needs to be more clarity about what makes a good alarm. Vendors and government agencies have developed several useful handbooks describing the Do’s and Don’ts of effective alarm design; however, to date, we cannot find a comprehensive quantitative taxonomy or classification system that allows researchers to easily score and rank various alarm designs in any field—while using a common language that users, engineers, designers, and human factors professionals can understand. The Alarm Taxonomy and Classification System (ATACS) fills this gap in the literature by breaking alarms down into categorical characteristics, providing a quantitative methodology for scoring each characteristic, and outlining a process by which users, vendors, and human factors professionals can agree on the efficacy of the alarm in question. We discuss this process in detail and show how this system was used to improve landing gear warnings.

Design of Rainfall Alarm and Related Applications

A switching device that is triggered by rainfall is known as a rain sensor or rain switch. Rain sensors are primarily used in two different contexts. The first is a water-saving device that is connected to an automatic irrigation system and causes it to turn off during a downpour. The second application is in the automotive sector, where rain sensors are used to turn on windscreen wipers automatically when rain is sensed, increasing driver convenience and safety. This technology has become a standard feature in many modern cars and has greatly improved driving conditions during inclement weather. Additionally, some rain sensors are now capable of adjusting the wiper speed based on the intensity of the rainfall, further enhancing their effectiveness.

A Data-Driven Process Monitoring Approach Based on Evidence Reasoning Rule Considering Interval-Valued Reliability

In the process industry, an alarm system is one of the important ways of condition monitoring. Due to the complexity and irregularity of process information in condition monitoring, there are too many false alarms in the current alarm system. In order to solve the problem of designing an alarm system, this paper proposes a multivariate alarm design method based on the evidence reasoning (ER) rule, considering interval-valued reliability, which can make full use of process information to make accurate alarm decisions. Firstly, the referential evidence matrixes (REMs) are constructed based on the training samples of process variables, and the real-time samples of the process variables are converted into alarm evidence by activating the REMs. Alarm evidence is then fused by the ER rule. In this fusion process, in order to better describe the uncertainty of the process information, the reliability of the alarm evidence is characterized by random variables with certain probability distributions, and it can be adjusted in dynamic intervals according to the real-time change of alarm evidence. Finally, the reactor fault case is implemented in the Tennessee Eastman (TE) process, which shows that the adjustment of interval-valued reliability can adapt to the irregular change of process information and obtains consistent alarm results to further improve the accuracy of alarm decisions.

Performance analysis of up/down counters in alarm design

Alarm systems, as a layer of protection, play a critical role in process safety. Modern alarm systems, however, pose a challenge in the process industry due to alarm floods, missed alarms, and a large number of false, nuisance, and chattering alarms. In this paper, we propose up/down counter configurations as a technique to improve the quality of univariate alarm systems. Mathematical models are developed based on the Markov chain to study the performance of up/down counters and analytical expressions for performance indices (the false alarm rate, missed alarm rate, and expected detection delay) are derived. The results are confirmed using Monte Carlo simulation and the utility of the proposed technique is demonstrated through examples. This proposed up/down counter is specifically compared to delay-timers as a common and well-studied alarm configuration technique.