Matthias Wille

Interaction of human, machine, and environment in automated driving systems

In view of the increase in traffic volume and growing demands on traffic, alternative mobility concepts such as automation of the driving task are increasingly being investigated. In line with this course of development project KONVOI was initiated, where an interdisciplinary research team carried out the electronic coupling of trucks. Because the technical feasibility of such automated systems had already been proved, project KONVOI focused on quantifying the impact of automated systems on traffic and on the interaction between humans and machines. Technical development of the system took place with preferential consideration of the human being. The KONVOI system was analyzed for acceptance and the potential workload by using test people in a driving simulator. The test results had a direct effect on the technical development of the system. After approval of the prototype, the traffic effects of the KONVOI system were examined in the context of real German highways. The results of this impact analysis served as a comparison of the developmental concept and evaluation of the system. Open questions concerning the effects of the KONVOI system on car drivers were investigated through additional test drives in the driving simulator. In project KONVOI, an automated system was run in real traffic for the first time in Europe. This testing and the strong consideration of the human being in the development process have provided new insights into the development of driver assistant systems and automated driving systems.

The “Aachen fall prevention App” – a Smartphone application app for the self-assessment of elderly patients at risk for ground level falls

BackgroundFall incidents are a major problem for patients and healthcare. The “Aachen Fall Prevention App” (AFPA) represents the first mobile Health (mHealth) application (app) empowering older patients (persons 50+ years) to self-assess and monitor their individual fall risk. Self-assessment is based on the “Aachen Fall Prevention Scale,” which consists of three steps. First, patients answer ten standardized yes–no questions (positive criterion ≥ 5 “Yes” responses). Second, a ten-second test of free standing without compensatory movement is performed (positive criterion: compensatory movement). Finally, during the third step, patients rate their subjective fall risk on a 10-point Likert scale, based on the results of steps one and two. The purpose of this app is (1) to offer a low-threshold service through which individuals can independently monitor their individual fall risk and (2) to collect data about how a patient-centered mHealth app for fall risk assessment is used in the field.ResultsThe results represent the first year of an ongoing field study. From December 2015 to December 2016, 197 persons downloaded the AFPA (iOS™ and Android™; free of charge). N = 111 of these persons voluntarily shared their data and thereby participated in the field study. Data from a final number of n = 79 persons were analyzed due to exclusion criteria (age, missing objective fall risk, missing self-assessment). The objective fall risk and the self-assessed subjective risk measured by the AFPA showed a significant positive relationship.ConclusionsThe “Aachen Fall Prevention App” (AFPA) is an mHealth app released for iOS and Android. This field study revealed the AFPA as a promising tool to raise older adults’ awareness of their individual fall risk by means of a low-threshold patient-driven fall risk assessment tool.

Influence of Mobile ICT on the Adherence of Elderly People with Chronic Diseases

A great variety of applications for mobile devices are designed to support users during medical intake. One of these applications is ‘Medication Plan’ which aims at supporting regular and correct intake of medication and documentation of vital parameters. The purpose of this study is to examine the influence of demographic and health-related factors on user behavior and patterns of use. The application was available free of charge between 2010 and 2012 in the Apple™-App-Store™. The study is based on data collected via an online questionnaire. In total 1799 participants generated 1708 complete data sets. 69 % of the users (74 % male) with a median age of 45 applied ‘Medication Plan’ for more than one day. The mean duration of application increased substantially with age ( 60 years = 103.9 days). However, other demographic factors (sex, educational status etc.) had no effect on usage intensity. Users with complicated medical treatment or aged > 60 years applied the application for 3 month on average. This is a promising trend towards the support treatment of chronic conditions with mobile applications.

Mobile Technology Improves Therapy-Adherence Rates in Elderly Patients Undergoing Rehabilitation—A Crossover Design Study

In this publication the results of an empirical study are analyzes regarding the research question if a mobile application on a tablet computer, to support the drug intake and vital sign parameter documentation, affects adherence of elderly patients. For the achievement in the management of patients with hypertension adherence of their medication is essential. Patients with no prior knowledge of tablet computers and a coronary heart disease were included. All Patients were instructed personally into the mobile application “Medication Plan”, installed on an Apple iPad™. This study was performed in a crossover design with three sequences. The first sequence is the initial phase, followed by the interventional phase (28 days of using the app system) and at least the comparative phase (28 days of using a paper diary). The interventional and comparative phases were conducted alternately. Altogether, 24 patients (12 male; mean age 73.8 years) were registered. The subjectively assessed adherence (A 14 scale) was 50.0 before the study started (SD 3.44). After the enforcement of both interventions there was a significant increase, which was more pronounced after the intervention phase (54.0, SD 2.01) than the comparative phase (52.6, SD 2.49) (for all pairs p < 0.001). Furthermore, the medical conditions, or the number of drug intakes per day had no effect on the subjective adherence. For both blood pressure recordings (p < 0.001) and medication intake (p = 0.033) the obtained logging data showed a significantly stronger adherence for the medication-app than the paper diary system. The majority of participants (n = 22) denoted that they would like to use the medication-app in everyday life and do not need any further assistance. A mobile app for medication adherence strengthened objectively and subjectively metered adherence of elderly users folding rehabilitation.

User-Driven Semantic Classification for the Analysis of Abstract Health and Visualization Tasks

Present article outlines characteristics of a general task analysis in terms of digital health visualization evaluation and design. Furthermore, a number of methodological approaches are discussed. One example, in which a hierarchical structure was empirically built with semantic classification by 98 users, will be discussed together with the expected benefits of its successful implementation with respect to system development and human factors research on health data visualizations. It is concluded that experimental approaches to taxonomy construction offer considerable promise in capturing tasks which are relevant but that further investigation is needed validating and iteratively extending the abstract task structures. We thus recommend based on our experiences to conduct a combination of semantic classification with users and hierarchical task analysis to capture all needed task abstraction levels.

Neuroergonomic analysis of perihand space: effects of hand proximity on eye-tracking measures and performance in a visual search task

ABSTRACT According to recent studies, cognitive processes are modulated by the proximity of the hands to a stimulus. Specifically, hand proximity (also known as nearby-hand or hand-presence effects) induces a bias to process information near the hands more precisely and this effect can be facilitative or debilitative depending on the task context. Two different distances of the hands in reference to the screen were studied as independent variables: hands placed on the screen and hands placed on the lap. The dependent variables were search times and different eye-tracking parameters. Given the age-related decline in the perception of peripersonal space, the results were analysed for two different age groups. Overall, we found a more detailed evaluation of information near the hands depending on age. In conclusion, the study presents a cognitive behavioural evaluation of human–computer interaction which can be used for touchscreen interface and interaction design as well as modelling human–system interaction.

Ergonomic Considerations For The Design And The Evaluation Of Uncertain Data Visualizations

Uncertainty impacts many crucial issues the world is facing today – from climate change prediction, to scientific modelling, to the interpretation of medical data. Decisions typically rely on data which can be aggregated from different sources and further transformed using a variety of algorithms and models. Such data processing pipelines involve different types of uncertainty. As visual data representations are able to mediate between human cognition and computational models, a trustworthy conveyance of data characteristics requires effective representations of uncertainty which take productivity and cognitive abilities, as important human factors, into account. We summarize findings resulting from prior work on interactive uncertainty visualizations. Subsequently, an evaluation study is presented which investigates the effect of different visualizations of uncertain data on users’ efficiency (time, error rate) and subjectively perceived cognitive load. A table, a static graphic, and an interactive graphic containing uncertain data were compared. The results of an online study (N = 146) showed a significant difference in the task completion time between the visualization type, while there are no significant differences in error rate. A non-parametric K-W test found a significant difference in subjective cognitive load [H (2) = 7.39, p < 0.05]. Subjectively perceived cognitive load was lower for static and interactive graphs than for the numerical table. Given that the shortest task completion time was produced by a static graphic representation, we recommend this for use cases in which uncertain data are to be used time-efficiently.

Building and Exchanging Competence Interdisciplinarily Design Patterns as Domain Mediator

Design pattern languages are already used extensively in architecture and computer science. In 2009 we first proposed the idea of a design pattern language for the health sector and in particular the Ambient Assisted Living sector. Based on the first language, we now present a new design pattern language focusing on “mobile information and communication technology for elderly”. Addressing the increasing importance of healthcare ICT, especially for older users, the next logical step was to build upon the experience from the development of a language for “ambient assisted living”. The pattern language is proposed as a mediator to build and exchange competence interdisciplinary. Therefore, this paper introduces the idea of design pattern languages as well as the newly developed language. Furthermore, best practices in developing and applying design pattern languages are presented to enable the reader to use this as a method to exchange research results and ideas between disciplines and in laymen’s terms, even with novices of the research topic.

Desktop PC, Tablet PC, or Smartphone? An Analysis of Use Preferences in Daily Activities for Different Technology Generations of a Worldwide Sample

Our daily life is characterized by increasing digitalization. As a result digital technologies are becoming an integrated part of everyday activities. The most used devices are desktop PCs or laptops, tablet PCs, and smartphones, which mainly differ with regard to the screen size and the method of data entry. Given the growing diffusion of technological devices, the increasing ownership of multiple devices, and the resulting different usage patterns between devices, it is essential to gain insights into which devices are used for which activities. The aim of this analysis was to examine a total of 21 activities people engage in on a day-to-day basis with regard to desktop PC or laptop, tablet PC, and smartphone usage. When considering user characteristics with regard to technology, one of the most influential factors is the user’s age. Therefore, the sample (N = 1923) was analyzed with regard to four different technology generations. Results show that there are significant differences in device usage between the activities under study and between the four analyzed technology generations.

Home Use Devices and SaMDs in Patient Self-Care: Concept to Develop Excellenct Products in Digital Health

The German healthcare system is characterized by digital change. In recent years, a trend towards the entry of start-ups and medium-sized enterprises into this sector has developed. These types of companies in particular are facing enormous challenges due to the industry and the ongoing digital change. This article presents the fundamental developments and challenges of these companies. Further solutions developed by the Tech4Age research group are presented briefly. Finally, this article describes how these solutions can be integrated into a formal concept for the promotion and further development of SMEs and start-ups in the German health industry in order to enable them quickly and comprehensively for the development of excellent digital health products.