ArticleScientific reports2019
Seal and Sea lion Whiskers Detect Slips of Vortices Similar as Rats Sense Textures.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 0 citations in OpenAlex.
- Hydrodynamic Responses and Machine Learning-Based Shape Classification of Harbor Seal Whiskers in the Wake of Bluff Bodies.Biomimetics (Basel, Switzerland) · 2025Article
- Monosynaptic trans-collicular pathways link mouse whisker circuits to integrate somatosensory and motor cortical signals.PLoS biology · 2023Article
- Sea lions could use multilateration localization for object tracking as tested with bio-inspired whisker arrays.Scientific reports · 2022Article
- Creating underwater vision through wavy whiskers: a review of the flow-sensing mechanisms and biomimetic potential of seal whiskers.Journal of the Royal Society, Interface · 2021Review
- A Deep-Learning Model for Underwater Position Sensing of a Wake's Source Using Artificial Seal Whiskers.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pinnipeds like seals and sea lions use their whiskers to hunt their prey in dark and turbid situations. There is currently no theoretical model or hypothesis to explain the interaction between whiskers and hydrodynamic fish trails. The current study, however, provides a theoretical and experimental insight into the mechanism behind the detection of the Strouhal frequency from a Von-Karman vortex street, similar to that of the inverted hydrodynamic fish trail. Herein the flow around a 3D printed sea lion head, with integrated whiskers of comparable geometry and material properties to a real seal lion, is investigated when exposed to vortex streets generated by cylindrical bluff bodies. The whiskers respond to the vortices with a jerky motion, analogous to the stick-slip response of rat whiskers; this motion is found to be the time derivative of the Gaussian function. Compared to the displacement response, the time-derivative of the whisker response decodes the Strouhal frequency of the Von-Karman wake, which improves the sensing efficiency in noisy environments. The study hypothesizes that the time derivative of the whisker bending moment is the best physical variable that can be used as the input to the pinnipeds neural system.
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