Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry

Prevailing trends in the automotive and medical device industry, such as life cycle overarching configurability, connectivity, and automation, require an adaption of development processes, especially regarding the security and safety thereof. The changing requirements imply that interfaces are more exposed to the outside world, making them more vulnerable to cyberattacks or data leaks. Consequently, not only do development processes need to be revised but also cybersecurity countermeasures and a focus on safety, as well as privacy, have become vital. While vehicles are especially exposed to cybersecurity and safety risks, the medical devices industry faces similar issues. In the automotive industry, proposals and draft regulations exist for security-related risk assessment processes. The medical device industry, which has less experience in these topics and is more heterogeneous, may benefit from drawing inspiration from these efforts. We examined and compared current standards, processes, and methods in both the automotive and medical industries. Based on the requirements regarding safety and security for risk analysis in the medical device industry, we propose the adoption of methods already established in the automotive industry. Furthermore, we present an example based on an interoperable Operating Room table (OR table)

Deep Denoising for Hearing Aid Applications

Reduction of unwanted environmental noises is an important feature of today's hearing aids (HA), which is why noise reduction is nowadays included in almost every commercially available device. The majority of these algorithms, however, is restricted to the reduction of stationary noises. In this work, we propose a denoising approach based on a three hidden layer fully connected deep learning network that aims to predict a Wiener filtering gain with an asymmetric input context, enabling real-time applications with high constraints on signal delay. The approach is employing a hearing instrument-grade filter bank and complies with typical hearing aid demands, such as low latency and on-line processing. It can further be well integrated with other algorithms in an existing HA signal processing chain. We can show on a database of real world noise signals that our algorithm is able to outperform a state of the art baseline approach, both using objective metrics and subject tests.Comment: submitted to IWAENC 201

Generic Patterns for Intrusion Detection Systems in Service-Oriented Automotive and Medical Architectures

To implement new software functions and more flexible updates in the future as well as to provide cloud-based functionality, the service-oriented architecture (SOA) paradigm is increasingly being integrated into automotive electrical and electronic architecture (E/E architectures). In addition to the automotive industry, the medical industry is also researching SOA-based solutions to increase the interoperability of devices (vendor-independent). The resulting service-oriented communication is no longer fully specified during design time, which affects information security measures. In this paper, we compare different SOA protocols for the automotive and medical fields. Furthermore, we explain the underlying communication patterns and derive features for the development of an SOA-based Intrusion Detection System (IDS)

Eating habits of preschool children with high migrant status in Switzerland according to a new food frequency questionnaire

Assessment of eating habits in young children from multicultural backgrounds has seldom been conducted. Our objectives were to study the reproducibility and the results of a food frequency questionnaire (FFQ) developed to assess changes in eating habits of preschool children with a high migrant population, in the context of a multidisciplinary multilevel lifestyle intervention. Three kindergarten classes (53% from migrant backgrounds) in French-speaking Switzerland were randomly selected and included 16 girls and 28 boys (mean age +/- SD, 5.4 +/- 0.7 years). The FFQ was filled out twice within a 4-week interval by the parents. Spearman rank correlations between the first and the second FFQ for the 39 items of the food questions were as follows: low (r or= 0.70) for 9 (all P 0.50, all P > .01). Eighty-six percent of the children ate breakfast at home daily, but only 67% had lunch at home. The percentages of children eating at least once a week in front of the TV were as follows: 50% for breakfast, 33% for lunch, 38% for dinner, and 48% for snacks. Forty percent of children asked their parents to buy food previously seen in advertisements and ate fast food between once a week and once a month. Children generally consumed foods with a high-energy content. The FFQ yielded good test-retest reproducibility for most items of the food questions and gave relevant findings about the eating habits of preschool children in areas with a high migrant populatio