Background: There is an emergence of mobile health (mHealth) interventions to support self-management in patients with chronic obstructive pulmonary disease (COPD). Recently, an evidence-driven mHealth intervention has been developed to support patients with COPD in exacerbation-related self-management: the Copilot app. Health care providers (HCPs) are important stakeholders as they are the ones who have to provide the app to patients, personalize the app, and review the app. It is, therefore, important to investigate at an early stage whether the app is feasible in the daily practice of the HCPs. Objective: The aim of this study is to evaluate the perceived feasibility of the Copilot app in the daily practice of HCPs. Methods: A multimethods design was used to investigate how HCPs experience working with the app and how they perceive the feasibility of the app in their daily practice. The feasibility areas described by Bowen et al were used for guidance. HCPs were observed while performing tasks in the app and asked to think aloud. The System Usability Scale was used to investigate the usability of the app, and semistructured interviews were conducted to explore the feasibility of the app. The study was conducted in primary, secondary, and tertiary care settings in the Netherlands from February 2019 to September 2019. Results: In total, 14 HCPs participated in this study—8 nurses, 5 physicians, and 1 physician assistant. The HCPs found the app acceptable to use. The expected key benefits of the app were an increased insight into patient symptoms, more structured patient conversations, and more tailored self-management support. The app especially fits within the available time and workflow of nurses. The use of the app will be influenced by the autonomy of the professional, the focus of the organization on eHealth, costs associated with the app, and compatibility with the current systems used. Most HCPs expressed that there are conditions that must be met to be able to use the app. The app can be integrated into the existing care paths of primary, secondary, and tertiary health care settings. Individual organizational factors must be taken into account when integrating the app into daily practice. Conclusions: This early-stage feasibility study shows that the Copilot app is feasible to use in the daily practice of HCPs and can be integrated into primary, secondary, and tertiary health care settings in the Netherlands. The app was considered to best fit the role of the nurses. The app will be less feasible for those organizations in which many conditions need to be met to use the app. This study provides a new approach to evaluate the perceived feasibility of mHealth interventions at an early stage and provides valuable insights for further feasibility testing.
An important issue in the field of motion control of wheeled mobile robots is that the design of most controllers is based only on the robot’s kinematics. However, when high-speed movements and/or heavy load transportation are required, it becomes essential to consider the robot dynamics as well. The control signals generated by most dynamic controllers reported in the literature are torques or voltages for the robot motors, while commercial robots usually accept velocity commands. In this context, we present a velocity-based dynamic model for differential drive mobile robots that also includes the dynamics of the robot actuators. Such model has linear and angular velocities as inputs and has been included in Peter Corke’s Robotics Toolbox for MATLAB, therefore it can be easily integrated into simulation systems that have been built for the unicycle kinematics. We demonstrate that the proposed dynamic model has useful mathematical properties. We also present an application of such model on the design of an adaptive dynamic controller and the stability analysis of the complete system, while applying the proposed model properties. Finally, we show some simulation and experimental results and discuss the advantages and limitations of the proposed model.
The inefficiency of maintaining static and long-lasting safety zones in environments where actual risks are limited is likely to increase in the coming decades, as autonomous systems become more common and human workers fewer in numbers. Nevertheless, an uncompromising approach to safety remains paramount, requiring the introduction of novel methods that are simultaneously more flexible and capable of delivering the same level of protection against potentially hazardous situations. We present such a method to create dynamic safety zones, the boundaries of which can be redrawn in real-time, taking into account explicit positioning data when available and using conservative extrapolation from last known location when information is missing or unreliable. Simulation and statistical methods were used to investigate performance gains compared to static safety zones. The use of a more advanced probabilistic framework to further improve flexibility is also discussed, although its implementation would not offer the same level of protection and is currently not recommended.
MULTIFILE
Today, embedded devices such as banking/transportation cards, car keys, and mobile phones use cryptographic techniques to protect personal information and communication. Such devices are increasingly becoming the targets of attacks trying to capture the underlying secret information, e.g., cryptographic keys. Attacks not targeting the cryptographic algorithm but its implementation are especially devastating and the best-known examples are so-called side-channel and fault injection attacks. Such attacks, often jointly coined as physical (implementation) attacks, are difficult to preclude and if the key (or other data) is recovered the device is useless. To mitigate such attacks, security evaluators use the same techniques as attackers and look for possible weaknesses in order to “fix” them before deployment. Unfortunately, the attackers’ resourcefulness on the one hand and usually a short amount of time the security evaluators have (and human errors factor) on the other hand, makes this not a fair race. Consequently, researchers are looking into possible ways of making security evaluations more reliable and faster. To that end, machine learning techniques showed to be a viable candidate although the challenge is far from solved. Our project aims at the development of automatic frameworks able to assess various potential side-channel and fault injection threats coming from diverse sources. Such systems will enable security evaluators, and above all companies producing chips for security applications, an option to find the potential weaknesses early and to assess the trade-off between making the product more secure versus making the product more implementation-friendly. To this end, we plan to use machine learning techniques coupled with novel techniques not explored before for side-channel and fault analysis. In addition, we will design new techniques specially tailored to improve the performance of this evaluation process. Our research fills the gap between what is known in academia on physical attacks and what is needed in the industry to prevent such attacks. In the end, once our frameworks become operational, they could be also a useful tool for mitigating other types of threats like ransomware or rootkits.
Public safety is under enormous pressure. Demonstrations regularly result in riots and VIPs are often threatened even at their homes ! Criminal graffiti-gangs are threatening security professionals and costing the Dutch railways (NS), causing a loss of 10 M€ yearly. The safety incidents often escalate quickly, therefore, they require a very quick and correct scaling up of the security professionals. To do so, it is necessary for the security professionals to get very quick and accurate overview of the evolving situation using Mobile Drone intervention unit for quick response (Mobi Dick). The successfully completed project The Beast (9/11) has delivered a universal docking station with an automatic security drone. The drone takes off from a permanently installed docking station. Nest Fly emerged as a startup from this RAAK project, and it has already developed the prototype further to a first product. Based on extensive interaction with security professionals, it has been concluded that a permanently installed docking station is not suitable for all emergency cases. Therefore, a mobile, car-roof top mounted, docking station with a ready-for-take-off drone is required for the more severe and quickly escalating incidents. These situations require a drone taking off from the car-roof top mounted docking station while the vehicles continue to drive towards the incident. In this RAAK KIEM, a feasibility study will be executed by developing a car-roof top docking station. The concept will functionally be designed within the project (task 1). The two required subsystems car roof docking station (task 2) and dynamic take-off & landing (task 3) will technically be developed and integrated (task 4). The outcome of the experiments in this task will show the feasibly of the idea. Task 5 will ensure the results are disseminated in new cooperation’s, publications, and educational products.
The automobile industry is presently going through a rapid transformation towards autonomous driving. Nearly all vehicle manufacturers (such as Mercedes Benz, Tesla, BMW) have commercial products, promising some level of vehicle automation. Even though the safe and reliable introduction of technology depends on the quality standards and certification process, but the focus is primarily on the introduction of (uncertified) technology and not on developing knowledge for certification. Both industry and governments see the lack of knowledge about certification, which can ensure the safety of autonomous technology and thus will guarantee the safety of the driver, passenger, and environment. HAN-AR recognized the lack of knowledge and the need for novel certification methodology for emerging vehicle technology and initiated the PRAUTOCOL project together with its SME partners. The PRAUTOCOL project investigated certification methodology for two use-cases: certification for automated highway overtaking pilot; and certification for automatic valet parking. The PRAUTOCOL research is conducted in two parallel streams: certification of the driver by human factors experts and certification of vehicle by technology experts. The results from both streams are published and presented in respective but limited target groups. Also, an overview of the PRAUTOCOL certification methodology is missing, which can enable its translation to different use-cases of automated technology (other than the used ones). Therefore, to realize a better pass-through of PRAUTOCOL's results to a broader audience, the top-up is required. Firstly, to write a (peer-reviewed) Open Access article, focusing on the application and translation of PRAUTOCOL's methodology to other automated technology use-cases. Secondly, to write a journal article, focusing on the validation of automatic highway overtaking system using naturalistic driving data. Thirdly, to organize a workshop to present PRAUTOCOL's results (valorization) to industrial, research, and government representatives and to discuss a follow-up initiative.
