Addressing misconceptions of flow disruption studies in "Is non-stop always better? Examining assumptions behind the concept of flow disruptions in studies of robot-assisted surgery".

This letter to the editor provides a response to "Is non-stop always better? Examining assumptions behind the concept of flow disruptions in studies of robot-assisted surgery." The authors provide much needed clarification on misconceptions of flow disruption studies. The evolving methodology is not aimed at creating a "non-stop" flow, or optimizing efficiency, but understanding the clinical process from a systems perspective.

Study on Characteristics of Electromagnetic Coil Used in MEMS Safety and Arming Device.

Traditional silicon-based micro-electro-mechanical system (MEMS) safety and arming devices, such as electro-thermal and electrostatically driven MEMS safety and arming devices, experience problems of high insecurity and require high voltage drive. For the current electromagnetic drive mode, the electromagnetic drive device is too large to be integrated. In order to address this problem, we present a new micro electromagnetically driven MEMS safety and arming device, in which the electromagnetic coil is small in size, with a large electromagnetic force. We firstly designed and calculated the geometric structure of the electromagnetic coil, and analyzed the model using COMSOL multiphysics field simulation software. The resulting error between the theoretical calculation and the simulation of the mechanical and electrical properties of the electromagnetic coil was less than 2% under the same size. We then carried out a parametric simulation of the electromagnetic coil, and combined it with the actual processing capacity to obtain the optimized structure of the electromagnetic coil. Finally, the electromagnetic coil was processed by deep silicon etching and the MEMS casting process. The actual electromagnetic force of the electromagnetic coil was measured on a micro-mechanical test system, compared with the simulation, and the comparison results were analyzed.

Enhanced Hazard Analysis and Risk Assessment for Human-in-the-Loop Systems.

OBJECTIVE: The objective of this study was to enhance the existing system hazard analysis (SHA) technique by introducing the concepts of human and automation reliability quantification as well as fuzzy classification of system risks. These enhancements led to formulation of a new overall system risk-reliability score. BACKGROUND: Many system safety analysis methods focus on individual physical component failure. Some human reliability analyses (HRA) consider human-automation interaction in determining system failure rates. There is no system safety analysis technique that quantifies the impact of human and automation reliability on the risk of hazard exposure. METHOD: Classification of the probability and severity of hazard exposure is typically made in terms of linguistic rather than numerical variables. Fuzzy sets are applicable for transforming linguistic classifications to numerical quantities. We focused on using fuzzy sets to define overlapping bands of system risk exposure with reference to the hazard risk categories defined in MIL-STD 882B. Fuzzy sets were also used for human-automated system reliability classification. RESULTS: Introduction of human and automation reliability assessment in the SHA allows for definition of a system risk-reliability modeling space. The enhanced SHA (E-SHA) technique yields a mishap risk index, which is projected based on a composite assessment of human-automated system reliability at the time of operation. The E-SHA was compared with one of the most advanced HRA techniques. CONCLUSION: The E-SHA technique supports broader safety control recommendations and provides comparable, if not more detailed, results than prior systems safety and HRA techniques.

A systemic analysis of South Korea Sewol ferry accident - Striking a balance between learning and accountability.

The South Korea Sewol ferry accident in April 2014 claimed the lives of over 300 passengers and led to criminal charges of 399 personnel concerned including imprisonment of 154 of them as of Oct 2014. Blame and punishment culture can be prevalent in a more hierarchical society like South Korea as shown in the aftermath of this disaster. This study aims to analyse the South Korea ferry accident using Rasmussen's risk management framework and the associated AcciMap technique and to propose recommendations drawn from an AcciMap-based focus group with systems safety experts. The data for the accident analysis were collected mainly from an interim investigation report by the Board of Audit and Inspection of Korea and major South Korean and foreign newspapers. The analysis showed that the accident was attributed to many contributing factors arising from front-line operators, management, regulators and government. It also showed how the multiple factors including economic, social and political pressures and individual workload contributed to the accident and how they affected each other. This AcciMap was presented to 27 safety researchers and experts at 'the legacy of Jens Rasmussen' symposium adjunct to ODAM2014. Their recommendations were captured through a focus group. The four main recommendations include forgive (no blame and punishment on individuals), analyse (socio-technical system-based), learn (from why things do not go wrong) and change (bottom-up safety culture and safety system management). The findings offer important insights into how this type of accident should be understood, analysed and the subsequent response.

Usability and Safety in Electronic Medical Records Interface Design: A Review of Recent Literature and Guideline Formulation.

OBJECTIVE: The objectives of this study were to (a) review electronic medical record (EMR) and related electronic health record (EHR) interface usability issues, (b) review how EMRs have been evaluated with safety analysis techniques along with any hazard recognition, and (c) formulate design guidelines and a concept for enhanced EMR interfaces with a focus on diagnosis and documentation processes. BACKGROUND: A major impact of information technology in health care has been the introduction of EMRs. Although numerous studies indicate use of EMRs to increase health care quality, there remain concerns with usability issues and safety. METHOD: A literature search was conducted using Compendex, PubMed, CINAHL, and Web of Science databases to find EMR research published since 2000. Inclusion criteria included relevant English-language papers with subsets of keywords and any studies (manually) identified with a focus on EMR usability. RESULTS: Fifty studies met the inclusion criteria. Results revealed EMR and EHR usability problems to include violations of natural dialog, control consistency, effective use of language, effective information presentation, and customization principles as well as a lack of error prevention, minimization of cognitive load, and feedback. Studies focusing on EMR system safety made no objective assessments and applied only inductive reasoning methods for hazard recognition. CONCLUSION: On the basis of the identified usability problems and structure of safety analysis techniques, we provide EMR design guidelines and a design concept focused on the diagnosis process and documentation. APPLICATION: The design guidelines and new interface concept can be used for prototyping and testing enhanced EMRs.

SafeNet: a methodology for integrating general-purpose unsafe devices in safe-robot rehabilitation systems.

Robot-assisted neurorehabilitation often involves networked systems of sensors ("sensory rooms") and powerful devices in physical interaction with weak users. Safety is unquestionably a primary concern. Some lightweight robot platforms and devices designed on purpose include safety properties using redundant sensors or intrinsic safety design (e.g. compliance and backdrivability, limited exchange of energy). Nonetheless, the entire "sensory room" shall be required to be fail-safe and safely monitored as a system at large. Yet, sensor capabilities and control algorithms used in functional therapies require, in general, frequent updates or re-configurations, making a safety-grade release of such devices hardly sustainable in cost-effectiveness and development time. As such, promising integrated platforms for human-in-the-loop therapies could not find clinical application and manufacturing support because of lacking in the maintenance of global fail-safe properties. Under the general context of cross-machinery safety standards, the paper presents a methodology called SafeNet for helping in extending the safety rate of Human Robot Interaction (HRI) systems using unsafe components, including sensors and controllers. SafeNet considers, in fact, the robotic system as a device at large and applies the principles of functional safety (as in ISO 13489-1) through a set of architectural procedures and implementation rules. The enabled capability of monitoring a network of unsafe devices through redundant computational nodes, allows the usage of any custom sensors and algorithms, usually planned and assembled at therapy planning-time rather than at platform design-time. A case study is presented with an actual implementation of the proposed methodology. A specific architectural solution is applied to an example of robot-assisted upper-limb rehabilitation with online motion tracking.

At the cross-roads: an on-road examination of driving errors at intersections.

A significant proportion of road trauma occurs at intersections. Understanding the nature of driving errors at intersections therefore has the potential to lead to significant injury reductions. To further understand how the complexity of modern intersections shapes behaviour of these errors are compared to errors made mid-block, and the role of wider systems failures in intersection error causation is investigated in an on-road study. Twenty-five participants drove a pre-determined urban route incorporating 25 intersections. Two in-vehicle observers recorded the errors made while a range of other data was collected, including driver verbal protocols, video, driver eye glance behaviour and vehicle data (e.g., speed, braking and lane position). Participants also completed a post-trial cognitive task analysis interview. Participants were found to make 39 specific error types, with speeding violations the most common. Participants made significantly more errors at intersections compared to mid-block, with misjudgement, action and perceptual/observation errors more commonly observed at intersections. Traffic signal configuration was found to play a key role in intersection error causation, with drivers making more errors at partially signalised compared to fully signalised intersections.