Context Awareness in Human-Computer Interaction

Makkonen, Jarmo; Avdouevski, Ivan; Kerminen, Riitta; Visa, Ari

doi:10.5772/7743

Cited by 7 publications

(6 citation statements)

References 38 publications

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“…Benerecetti et al [7] defined it as 1 http://www.yourdictionary.com/context a collection of features of the physical or virtual environment, which can affect the behaviour of an entity (for example, a person, user, agent, 2 place, or computational object). Other works [8]- [12] concur, with some variations depending on the application domain, that a context typically refers to a set of observable real world parameters (e.g. location, temperature, velocity etc.)…”

Section: ) Contextmentioning

confidence: 93%

“…Lastly, some of the papers were excluded during the review on the basis that even though they contain the keywords, on closer investigation the systems discussed in these papers had no sufficient level of context-awareness characteristics discussed in previous section. That is, they do not satisfy the key criteria for technologies that use contextawareness [8], [11], such as:…”

Section: Review Methodology and Structurementioning

confidence: 99%

“…When context-aware applications are in use, sensors are constantly collecting private data from users, thus this could be regulated by law [8]. In some cases, the use of private information is enabled through the consent of the user, but in some other cases users can be monitored without their permission and their data made available to third parties.…”

Section: A Contextual Awareness In Privacymentioning

confidence: 99%

“…Context-awareness can enhance the interaction between humans and computers. Computer systems do this by providing services semi-automatically to sense the surroundings, evaluate the situation, and execute decisions to offer functionalities to the user [8]. However, context-aware applications can demand too much information and the applications can become disturbing for the user and be seen as untrustworthy.…”

Section: Contextual Awareness For Human Computer/machine Interactionmentioning

confidence: 99%

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Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey

et al. 2019

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Autonomous vehicles are becoming a reality in places with advanced infrastructure to support their operations. In crowded places, harsh environments, missions that require these vehicles to be aware of the context in which they are operating, and situations requiring continuous coordination with humans such as in disaster relief, advanced-vehicle systems (AVSs) need to be better contextually aware. The vast literature referring to ''context-aware systems'' is still sparse, focusing on very limited forms of contextual awareness. It requires a structured approach to bring it together to truly realize contextual awareness in AVSs. This paper uses a human-AVSs (HAVSs) lens to polarize the literature in a coherent form suitable for designing distributed HAVSs. We group the relevant literature into two categories: contextual-awareness related to the vehicle infrastructure itself that enables AVSs to operate, and contextual-awareness related to HAVSs. The former category focuses on the communication backbone for AVSs including ad-hoc networks, services, wireless communication, radio systems, and the cyber security and privacy challenges that arise in these contexts. The latter category covers recommender systems, which are used to coordinate the actions that sit at the interface of the human and AVSs, human-machine interaction issues, and the activity recognition systems as the enabling technology for recommender systems to operate autonomously. The structured analysis of the literature has identified a number of open research questions and opportunities for further research in this area.

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Section: ) Contextmentioning

confidence: 93%

Section: Review Methodology and Structurementioning

confidence: 99%

Section: A Contextual Awareness In Privacymentioning

confidence: 99%

Section: Contextual Awareness For Human Computer/machine Interactionmentioning

confidence: 99%

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Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey

et al. 2019

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“…Human-machine interaction can become more natural once machines become aware of their surroundings and their users [1, 2]. These so-called context-aware or affective interfaces can open up new dimensions of device functionality, thus more accurately addressing human needs while keeping the interfaces as natural as possible [3].…”

Section: Introductionmentioning

confidence: 99%

Fusion of Motif- and Spectrum-Related Features for Improved EEG-Based Emotion Recognition

Tiwari

Falk

2019

Computational Intelligence and Neuroscience

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Emotion recognition is a burgeoning field allowing for more natural human-machine interactions and interfaces. Electroencephalography (EEG) has shown to be a useful modality with which user emotional states can be measured and monitored, particularly primitives such as valence and arousal. In this paper, we propose the use of ordinal pattern analysis, also called motifs, for improved EEG-based emotion recognition. Motifs capture recurring structures in time series and are inherently robust to noise, thus are well suited for the task at hand. Several connectivity, asymmetry, and graph-theoretic features are proposed and extracted from the motifs to be used for affective state recognition. Experiments with a widely used public database are conducted, and results show the proposed features outperforming benchmark spectrum-based features, as well as other more recent nonmotif-based graph-theoretic features and amplitude modulation-based connectivity/asymmetry measures. Feature and score-level fusion suggest complementarity between the proposed and benchmark spectrum-based measures. When combined, the fused models can provide up to 9% improvement relative to benchmark features alone and up to 16% to nonmotif-based graph-theoretic features.

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