ArticleBiomimetics (Basel, Switzerland)2019
What Does a Hand-Over Tell?-Individuality of ShortMotion Sequences.
Article in Biomimetics (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of handover actions in human dyads.Frontiers in psychology · 2023Pooled it
- Predicting object properties based on movement kinematics.Brain informatics · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
How much information with regard to identity and further individual participantcharacteristics are revealed by relatively short spatio-temporal motion trajectories of a person?We study this question by selecting a set of individual participant characteristics and analysingmotion captured trajectories of an exemplary class of familiar movements, namely handover of anobject to another person. The experiment is performed with different participants under different,predefined conditions. A selection of participant characteristics, such as the Big Five personalitytraits, gender, weight, or sportiness, are assessed and we analyse the impact of the three factor groups"participant identity", "participant characteristics", and "experimental conditions" on the observedhand trajectories. The participants' movements are recorded via optical marker-based hand motioncapture. One participant, the giver, hands over an object to the receiver. The resulting time courses ofthree-dimensional positions of markers are analysed. Multidimensional scaling is used to projecttrajectories to points in a dimension-reduced feature space. Supervised learning is also applied.We find that "participant identity" seems to have the highest correlation with the trajectories, withfactor group "experimental conditions" ranking second. On the other hand, it is not possible to find acorrelation between the "participant characteristics" and the hand trajectory features.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.