Pose-gait analysis for cetacean biologging tag data.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2022
Historique:
received: 07 12 2021
accepted: 09 09 2022
entrez: 23 9 2022
pubmed: 24 9 2022
medline: 28 9 2022
Statut: epublish

Résumé

Biologging tags are a key enabling tool for investigating cetacean behavior and locomotion in their natural habitat. Identifying and then parameterizing gait from movement sensor data is critical for these investigations, but how best to characterize gait from tag data remains an open question. Further, the location and orientation of a tag on an animal in the field are variable and can change multiple times during a deployment. As a result, the relative orientation of the tag with respect to (wrt) the animal must be determined for analysis. Currently, custom scripts that involve species-specific heuristics tend to be used in the literature. These methods require a level of knowledge and experience that can affect the reliability and repeatability of the analysis. Swimming gait is composed of a sequence of body poses that have a specific spatial pattern, and tag-based measurements of this pattern can be utilized to determine the relative orientation of the tag. This work presents an automated data processing pipeline (and software) that takes advantage of these patterns to 1) Identify relative motion between the tag and animal; 2) Estimate the relative orientation of the tag wrt the animal using a data-driven approach; and 3) Calculate gait parameters that are stable and invariant to animal pose. Validation results from bottlenose dolphin tag data show that the average relative orientation error (tag wrt the body) after processing was within 11 degrees in roll, pitch, and yaw directions. The average precision and recall for detecting instances of relative motion in the dolphin data were 0.87 and 0.89, respectively. Tag data from humpback and beluga whales were then used to demonstrate how the gait analysis can be used to enhance tag-based investigations of movement and behavior. The MATLAB source code and data presented in the paper are publicly available (https://github.com/ding-z/cetacean-pose-gait-analysis.git), along with suggested best practices.

Identifiants

pubmed: 36149842
doi: 10.1371/journal.pone.0261800
pii: PONE-D-21-38732
pmc: PMC9506652
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0261800

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Ding Zhang (D)

Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States of America.

Kari Goodbar (K)

Dolphin Quest Oahu, Honolulu, HI, United States of America.

Nicole West (N)

Dolphin Quest Oahu, Honolulu, HI, United States of America.

Veronique Lesage (V)

Fisheries and Oceans Canada, Ottawa, Canada.

Susan E Parks (SE)

Department of Biology, Syracuse University, Syracuse, NY, United States of America.

David N Wiley (DN)

National Oceanic and Atmospheric Agency's (NOAA) Stellwagen Bank National Marine Sanctuary, Scituate, MA, United States of America.

Kira Barton (K)

Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States of America.

K Alex Shorter (KA)

Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States of America.

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Classifications MeSH