Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE
Recent publications
In search and rescue missions, teleoperated rovers equipped with sensor technology are deployed into harsh environments to search for targets. To support the search task, unimodal/multimodal cues can be presented via visual, acoustic and/or haptic channels. However, human operators often perform the search task in parallel with the driving task, which can cause interference of attentional resources based on multiple resource theory. Navigating corners can be a particularly challenging aspect of remote driving, as described with the Cornering Law. Therefore, search cues should not interfere with cornering. The present research explores how unimodal/multimodal search cues affect cornering performance, with typical communication delays of 50ms and 500ms. One-hundred thirty-one participants, distributed into two delay groups, performed a target search task with unimodal/multimodal search cues. Search cues did not interfere with cornering performance with 50ms delays. For 500ms delays, search cues presented via the haptic channel significantly interfered with the driving task.
For the prevention of musculoskeletal disorders (MSD), the evaluation of manual materials handling (MMH) is important. Cumulative loading can be used to quantify exposure, but there is little applied research on its effectiveness in risk assessment. Therefore, this publication presents an analysis of whether cumulative loading estimates can be used to assess the occupational risk of MSD. Five methods for estimating cumulative spine loads from time-varying data are compared based on real collective exposure data of MMH associated with both high and low incidences of MSD. Results show that cumulative loading estimates can be used to assess the occupational risk of MSD. Still, it should be noted that assessment results are substantially influenced by the recorded level of detail of the exposure data and do not allow for reliable conclusions regarding physiological demands. Further research is needed regarding the inclusion of physiological responses and task sequences. Relevance to industry The findings can be applied to ergonomic risk assessment in occupational practice. By becoming more aware of the differences between calculation methods and the influence of the level of detail of the exposure data, the planning and implementation of the ergonomic risk assessment can be facilitated.
Affect-adaptive systems detect the emotional user state, assess it against the current situation, and adjust interaction accordingly. Tools for real-time emotional state detection, like the Emotient FACET engine (Littlewort et al., 2011), are based on the analysis of facial expressions. When developing affect-adaptive systems, output from the diagnostic engine must be mapped onto theoretical models of emotion. The Circumplex Model of Affect (Russell, 1980) describes emotion on two dimensions: valence and arousal. However, FACET offers three classifiers for valence: positive, neutral, and negative valence. The present study aimed at developing an algorithm that converts these into a unified valence scale. We used FACET to analyze valence-labeled images from the AffectNet database. In a multiple regression analysis, FACET classifier values predicted database valence and explained 38% of the variance. By inserting classifier values into the regression equation, a unified valence scale can be calculated that matches dimensional models of emotion. This research forms the groundwork for adaptation of the emotional user state based on the FACET engine. A future affect-adaptive system can now use the FACET engine to detect the emotional user state on a unified valence dimension, which allows for distinct classification and interpretation of emotions.
Polar codes are a relatively new family of linear block codes which have garnered a lot of attention from the scientific community, owing to their low-complexity implementation and provably capacity achieving capability. They have been proposed to be used for encoding information on the control channels in 5G wireless networks due to their robustness for short codeword lengths. The basic approach introduced by Arikan can only be used to generate polar codes of length N=2n, ∀n∈N. To overcome this limitation, polarization kernels of size larger than 2×2 (like 3×3, 4×4, and so on), have already been proposed in the literature. Additionally, kernels of different sizes can also be combined together to generate multi-kernel polar codes, further improving the flexibility of codeword lengths. These techniques undoubtedly improve the usability of polar codes for various practical implementations. However, with the availability of so many design options and parameters, designing polar codes that are optimally tuned to specific underlying system requirements becomes extremely challenging, since a variation in system parameters can result in a different choice of polarization kernel. This necessitates a structured design technique for optimal polarization circuits. We developed the DTS-parameter to quantify the best rate-matched polar codes. Thereafter, we developed and formalized a recursive technique to design polarization kernels of higher order from component smaller order. A scaled version of the DTS-parameter, namely SDTS-parameter (denoted by the symbol ζ in this article) was used for the analytical assessment of this construction technique and validated for single-kernel polar codes. In this paper, we aim to extend the analysis of the aforementioned SDTS parameter for multi-kernel polar codes and validate their applicability in this domain as well.
Recent advancements in radar technology and telecommunications have led to a high population of increasingly complex emitters in the electromagnetic spectrum. From the perspective of a signals intelligence (SIGINT) operator, assessing the general situation comes with several major challenges, e.g. the detection and extraction of signals of interest, the elimination of unwanted interferences, or the meaningful representation of increasingly complex modulation patterns. This paper provides a general overview of the challenges of SIGINT and suggests possible ways to support operators with automated signal processing.
This paper addresses the challenge of testing military systems and applications over different communication scenarios with both network conditions and user data flows changing independently. We assume that systems developed to handle ever-changing communication scenarios are more likely to be reliable and robust during real military operations. Therefore, we propose the Tactical Network Test (TNT) platform to automate the evaluation of military systems and applications over real military radios using a reproducible test methodology. TNT has four main goals (i) the creation of QoS-constrained data flows; (ii) the execution of models to change network conditions; (iii) the automation of experiments to quantify the performance of military systems over ever-changing communication scenarios; and (iv) the monitoring of quantitative metrics and performing data analysis. Our platform was used to execute experiments in a VHF network by sending uniformly distributed data flows during seven different communication scenarios, either generated by a stochastic model or mobility models. The experimental results are used to discuss the military system's performance by quantitative analysis using network metrics such as packet loss, delay, jitter, and data rate, and the test scenario characterization using mobility metrics such as speed, distance, and acceleration.
The transformation of power grids into intelligent cyber-physical systems brings numerous benefits, but also significantly increases the surface for cyber-attacks, demanding appropriate countermeasures. However, the development, validation, and testing of data-driven countermeasures against cyber-attacks, such as machine learning-based detection approaches, lack important data from real-world cyber incidents. Unlike attack data from real-world cyber incidents, infrastructure knowledge and standards are accessible through expert and domain knowledge. Our proposed approach uses domain knowledge to define the behavior of a smart grid under non-attack conditions and detect attack patterns and anomalies. Using a graph-based specification formalism, we combine cross-domain knowledge that enables the generation of whitelisting rules not only for statically defined protocol fields but also for communication flows and technical operation boundaries. Finally, we evaluate our specification-based intrusion detection system against various attack scenarios and assess detection quality and performance. In particular, we investigate a data manipulation attack in a future-orientated use case of an IEC 60870-based SCADA system that controls distributed energy resources in the distribution grid. Our approach can detect severe data manipulation attacks with high accuracy in a timely and reliable manner.
Visually induced motion sickness (VIMS) is a well-known side effect of virtual reality (VR) immersion, with symptoms including nausea, disorientation, and oculomotor discomfort. Previous studies have shown that pleasant music, odor, and taste can mitigate VIMS symptomatology, but the mechanism by which this occurs remains unclear. We predicted that positive emotions influence the VIMS-reducing effects. To investigate this, we conducted an experimental study with 68 subjects divided into two groups. The groups were exposed to either positive or neutral emotions before and during the VIMS-provoking stimulus. Otherwise, they performed exactly the same task of estimating the time-to-contact while confronted with a VIMS-provoking moving starfield stimulation. Emotions were induced by means of pre-tested videos and with International Affective Picture System (IAPS) images embedded in the starfield simulation. We monitored emotion induction before, during, and after the simulation, using the Self-Assessment Manikin (SAM) valence and arousal scales. VIMS was assessed before and after exposure using the Simulator Sickness Questionnaire (SSQ) and during simulation using the Fast Motion Sickness Scale (FMS) and FMS-D for dizziness symptoms. VIMS symptomatology did not differ between groups, but valence and arousal were correlated with perceived VIMS symptoms. For instance, reported positive valence prior to VR exposure was found to be related to milder VIMS symptoms and, conversely, experienced symptoms during simulation were negatively related to subjects’ valence. This study sheds light on the complex and potentially bidirectional relationship of VIMS and emotions and provides starting points for further research on the use of positive emotions to prevent VIMS.
Challenges in manual materials handling (MMH) are posed in particular by the requirements for continuous repetition and individual feedback. Low effort in MMH instructions is accordingly a relevant factor. The combination of a markerless motion capture system with a biomechanical model providing visual MMH instructions by individual real-time feedback of the compression force of the intervertebral disc in L5/S1 (CF) could tackle these challenges. However, this raises the question of whether this approach provides appropriate MMH instructions to improve the lifting technique in MMH. Results of an experiment with 22 young male participants indicate that visual MMH instructions with such individual real-time feedback have significant advantages in improving the lifting technique by reducing those factors associated with lower back pain compared to instructions with a reference paper-based tutorial or a baseline without instructions. Thus, peak and mean CF and peak trunk flexion, for example, were significantly lower when lifting with individual real-time feedback of CF compared to other conditions tested. Hence, the results suggest that it may be sensible to improve the lifting technique by such an approach of MMH instructions and integrate it in MMH training programs or on-the-job training in order to reduce or prevent lower back pain. Relevance to industry Using real-time feedback of the compression force of the intervertebral disc of L5/S1 based on markerless optical motion capture can improve the lifting technique in manual materials handling. This may be integrated into MMH training programs or on-the-job training to reduce or prevent low back pain.
The text discusses the concept of hybrid intelligence, which is a form of collaboration between machines and humans. It describes how this concept can be used in manufacturing to help improve productivity. The text also discusses how this concept can be used to help humans learn from machines. There is a debate in the intelligence community about the role of humans vs. machines. Machine intelligence can do some things better than humans, such as processing large amounts of data, but is not good at tasks that require common sense or empathy. Augmented intelligence emphasizes the assistive role of machine intelligence, while hybrid intelligence posits that humans and machines are part of a common loop, where they adapt to and collaborate with each other. The text discusses the implications of increasing machine involvement in organizational decision-making, specifically mentioning two challenges: negative effects on human behavior and flaws in machine decision-making. It argues that, in order for machine intelligence to improve decision-making processes, humans and machines must collaborate. The chapter argues that hybrid intelligence is the most likely scenario for decision-making in the future factory. The chapter discusses the advantages of this approach and how it can be used to improve quality control in a production system. The transformer-based language model called GPT-3 can be used to generate summaries of text. This task is difficult for machines because they have to understand sentiment and meaning in textual data. The model is also a “few-shot learner,” which means that it is able to generate a text based on a limited amount of examples. Transformer-based language models are beneficial because they are able to take the context of the processed words into consideration. This allows for a more nuanced understanding of related words and concepts within a given text.[Abstract generated by machine intelligence with GPT-3. No human intelligence applied.]
The aim was to investigate whether severe symptoms of visually induced motion sickness (VIMS) can occur in augmented reality (AR) optical see-through applications. VIMS has been extensively studied in virtual reality (VR), whereas it has received little attention in the context of AR technology, in which the real world is enhanced by virtual objects. AR optical see-through glasses are becoming increasingly popular as technology advances. Previous studies showed minor oculomotor symptoms of VIMS with the aforementioned technology. New applications with more dynamic simulations could alter previously observed symptom severity and patterns. In experiment 1, we exposed subjects to a traditional static AR application for pilot candidate training. In experiment 2, subjects completed tasks in a dynamic starfield simulation. We analyzed symptom profiles pre and post with the simulator sickness questionnaire (SSQ) and during exposure with the Fast Motion Sickness Scale (FMS). We also developed a new FMS-D that captures symptoms of dizziness during simulation. As expected, in experiment 1 we found low VIMS symptomatology with predominantly oculomotor symptoms. In experiment 2, on the other hand, we detected severe VIMS symptoms in some subjects, with disorientation (SSQ subscale) as the main symptom group. The present work demonstrates that VIMS can be of serious concern in modern AR applications. The FMS-D represents a new tool to measures symptoms of dizziness during exposure. VIMS symptoms need to be considered in the design and usage of future AR applications with dynamic virtual objects, e. g. for flight training or machine maintenance work.
Digital communication receivers extract information about the transmitted data from the received signal in subsequent processing steps, such as synchronization, demodulation and channel decoding. Technically, the receiver-side signal processing for conducting these tasks is complex and hence causes bottleneck situations in terms of power, delay and chip area. Typically, many bits per sample are required to represent and process the received signal in the digital receiver hardware accurately. In addition, demanding arithmetical operations are required in the signal processing algorithms. A popular recent trend is designing entire receiver chains or some of their crucial building blocks from an information theoretical perspective. Signal processing blocks with very simple mathematical operations can be designed to directly maximize the relevant information that flows through them. At the same time, a strong quantization reduces the number of bits processed in the receiver to further lower the complexity. The described system design approach follows the principle of the information bottleneck method. Different authors proposed various ideas to design and implement mutual information-maximizing signal processing units. The first important aim of this article is to explain the fundamental similarities between the information bottleneck method and the functionalities of communication receivers. Based on that, we present and investigate new results on an entire receiver chain that is designed following the information bottleneck design principle. Afterwards, we give an overview of different techniques following the information bottleneck design paradigm from the literature, mainly dealing with channel decoding applications. We analyze the similarities of the different approaches for information bottleneck signal processing. This comparison leads to a general view on information bottleneck signal processing which goes back to the learning of parameters of trainable functions that maximize the relevant mutual information under compression.
Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European countries (Germany, United Kingdom, Spain) about their expectations and concerns regarding sensor-based monitoring of employee mental workload. The data confirm the relevance of expectations regarding improvements of workplace design and employee well-being, as well as concerns about restrictions of employees' privacy and sovereignty, for the implementation of workload monitoring. Furthermore, Bayesian regression models show that the examined expectations have a substantial positive association with managers’ willingness to support workload monitoring in their company. Privacy concerns are identified as a significant barrier to the acceptance of workload monitoring, both in terms of their prevalence among managers and their strong negative relationship with monitoring support.
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144 members
Hans-Christian Schmitz
  • Information Technology for Command and Control Research Area
Felix Govaers
  • Sensor Data and Information Fusion Research Area
Carsten Winkelholz
  • Ergonomics and Human Machine Systems Research Area
Frank E. Schneider
  • Unmanned Systems Research Area
Dirk Schulz
  • Unmanned Systems Research Area
Fraunhoferstraße 20 , 53343 Wachtberg-Werthhoven, Wachtberg, Germany
Head of institution
Prof. Dr. Peter Martini
+49 (0)228 9435-0