Studying Natural Human-computer Interaction in Immersive Virtual Reality: A Comparison between Actions in the Peripersonal and in the Near-action Space

Bassano, Chiara; Solari, Fabio; Chessa, Manuela

doi:10.5220/0006622701080115

Cited by 7 publications

(4 citation statements)

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“…Details of the derivation of the model assuming a straight trajectory and its parameter estimation method are provided in the Appendix. We used the data reported by Corbett et al [24] in the Database for Reaching Experiments and Models (DREAM) 1 . In their experiment, six individuals each performed two reaching movements towards 18 target positions; our experiment only used the data collected during the training sessions to target the natural reaching movements.…”

Section: B Three-dimensional Reaching Data Analysismentioning

confidence: 99%

“…A basic component of everyday human motor repertoire, the reaching movement refers to the movement of the hand from an initial to a target position according to a motivationbased trajectory generated by the brain by taking distance and direction into account. Reaching movements have been evaluated by investigators to help improve motor function in rehabilitation and to inform the design of user interfaces [1]- [5].…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Parameterization of Human Reaching Movements Based on Time Base Generator

et al. 2020

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Human reaching movement is characterized by the invariant features of linearity and the symmetrical bell-shaped velocity profile of the hand trajectory. Reaching movement has been widely evaluated in fields such as rehabilitation and interface design; however, no standardized protocols exist for data collection, processing, or analysis. This paper proposes a spatiotemporal parameterization method that evaluates reaching movements with a trajectory generation model based on a time base generator. The proposed method extracts motion information as a set of model parameters, such as motion duration, distance, and asymmetry of the bell-shaped velocity profile from the reaching data, that are estimated by fitting the model to reaching data with a robust parameter estimation method. The reaching trajectory generation model, for which a straight trajectory in a three-dimensional space is assumed, is also derived from the proposed model. Experiments were conducted using simulated data and real-world three-dimensional and one-dimensional human reaching movement datasets. The results show that the model assuming a straight trajectory in the three-dimensional space is reasonable for evaluating reaching movements. In addition, the model parameters were estimated with relatively greater robustness than were those of the conventional model and were highly correlated with physical features extracted from measured datasets. The results also showed that the parameters representing the asymmetry of the bell-shaped velocity profile differed between individuals. Therefore, the characteristics of reaching movements can be parameterized and evaluated with the proposed method. INDEX TERMS Human reaching movements, time base generator (TBG), trajectory generation model, parameter estimation, motion parameterization.

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Section: B Three-dimensional Reaching Data Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Parameterization of Human Reaching Movements Based on Time Base Generator

et al. 2020

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“…The literature on conversation adaptation is also very recent and almost limited [27,30]. Apart from Amazon Sumerian 5 , it seems that no frameworks for integrating chatbots into VR/AR applications (AD and VD areas in Figure 1) exist, which makes the RAC vision extremely novel and original. Sumerian was launched in 2018 [20] and some authors criticize it for its lack of transparency and its questionable data policy, concluding that it is inappropriate for health-related applications [41].…”

Section: State Of the Artmentioning

confidence: 99%

“…addressing the wrong estimation of distances [11,26,29,38,39,48]. This negatively affects interaction, for example in industrial or medical training tasks, but how to interact in a natural way in such environments is also important for their acceptance, especially by fragile people [5]. Indeed, immersion, presence and interactivity are all factors that influence VR acceptance and use [13,46].…”

Section: State Of the Artmentioning

confidence: 99%

Engineering Reliable Interactions in the Reality-Artificiality Continuum

Ancona

Bassano

Chessa

et al. 2020

Electron. Proc. Theor. Comput. Sci.

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Milgram's reality-virtuality continuum applies to interaction in the physical space dimension, going from real to virtual. However, interaction has a social dimension as well, that can go from real to artificial depending on the companion with whom the user interacts. In this paper we present our vision of the Reality-Artificiality bidimensional Continuum (RAC), we identify some challenges in its design and development and we discuss how reliable interactions might be supported inside RAC.

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