Overground Gait Kinematics and Muscle Activation Patterns in the Yucatan Mini Pig

Mirkiani, Soroush; Da, Roszko; Cl, O’Sullivan; Faridi, Pouria; Ds, Hu; Fang, Daniel; Dg, Everaert; Toossi, Amirali; Robinson, Kevin; Vk, Mushahwar

doi:10.1101/2021.10.19.465020

Cited by 3 publications

(3 citation statements)

References 63 publications

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“…Piglets are a well-studied model system in which scientific interest joins the economic interest of commercial breeding. These animals have been subject to a variety of locomotor studies, including paradigms to test the effects of breed (Mirkiani et al, 2021), birth weight (Vanden Hole et al, 2018a, 2017, surface friction (von Wachenfelt et al, 2008), welfare (Guesgen and Bench, 2017), various pathologies (Abell et al, 2014;Benasson et al, 2020;LaVallee et al, 2020), and more (cf. Netukova et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Methodological Advances in Studying Postnatal Locomotor Development

Mielke¹

2023

Preprint

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We study piglet locomotion, attempting to falsify a difference that is due to birth weight category.This requires a methodological foundation on topics unfamiliar to most Biologists (Fourier Analysis, probabilistic models), which I introduce in dedicated chapters._Part I: Kinematic Analysis_+ I will introduce Fourier Methods with a practical guide and review its occurrence specifically in the field of locomotor biomechanics (Ch. 2).+ The power of Fourier tools is then unleashed onto a large cross-species study that covers most of the ungulate clade (Ch. 3, Mielke et al., 2019)._Part II: Probabilistic Modeling_+ Processing complex kinematic data, I will introduce the basics of probabilistic modeling (Ch. 4) in a "tiny textbook of statistics"...+ ... before turning around the conventional modeling strategy and applying it to piglets (Ch. 5, Mielke et al., 2023)._Part III: Dynamics_+ Kinematics are just half of locomotor research: the study of forces and moments is reviewed and summarized in another overview chapter (Ch. 6).+ To calculate joint moments, one needs to measure inertial properties, yet it turns out that these are not trivial to retrieve from x-ray tomographic images (Ch. 7).The thesis closes with a general discussion to round up and project the presented work to potential future applications (Ch. 8).

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Section: Introductionmentioning

confidence: 99%

Methodological Advances in Studying Postnatal Locomotor Development

Mielke¹

2023

Preprint

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“…Piglets are a well-studied model system in which scientific interest joins the economic interest of commercial breeding. These animals have been subject to a variety of locomotor studies, including paradigms to test the effects of breed (Mirkiani et al, 2021), birth weight (Vanden Hole et al, 2018a, 2021, 2017), surface friction (von Wachenfelt et al, 2008), welfare (Guesgen and Bench, 2017), various pathologies (Abell et al, 2014; Benasson et al, 2020; LaVallee et al, 2020), and more ( cf . Netukova et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A Workflow for High Through-Put, High Precision Livestock Diagnostic Screening of Locomotor Kinematics

Mielke

Ginneken

Aerts

2022

Preprint

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In the study of vertebrate locomotion, kinematic measures of gait, dynamic posture, and coordination often change when comparing subjects of different body mass, size, and age. Is it, conversely, possible to infer subject characteristics from the kinematic measures? For this study, piglets (Sus domesticus) were filmed from lateral perspective during their first ten hours of life, an age at which body mass and size have major consequences for survival. We then apply deep learning methods for point digitization (DeepLabCut), calculate joint angle profiles, and apply an information-preserving transfromation (Fourier series) to retrieve a multivariate kinematic data set. We train a probabilistic model to predict subject characteristics from kinematics. The model infers subject characteristics accurately for strides from piglets of normal birth weight (i.e. the category it was trained on), but surprisingly predicts the body mass and size of low birth weight piglets (which were left out of training, out-of-sample prediction) to be "normal". The discrepancies between prediction and observation confirm that dynamic posture and coordination are unaffected by lower birth weight and lower size, which is evidence that low birth weight does not imply locomotor deficits. However, the age of some (but not all) low birth weight individuals is underestimated, supporting the hypothesis that these piglets experience a delay in locomotor maturation.

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“…Domestic pigs are a well-studied model system in which scientific interest joins the economic interest of commercial breeding. These animals have been subject to a variety of locomotor studies, including paradigms to test the effects of breed (39), birth weight (40)(41)(42), surface friction (43), welfare (44), various pathologies (45)(46)(47), and more [cf. (8)].…”

mentioning

confidence: 99%

A workflow for automatic, high precision livestock diagnostic screening of locomotor kinematics

2023

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Locomotor kinematics have been challenging inputs for automated diagnostic screening of livestock. Locomotion is a highly variable behavior, and influenced by subject characteristics (e.g., body mass, size, age, disease). We assemble a set of methods from different scientific disciplines, composing an automatic, high through-put workflow which can disentangle behavioral complexity and generate precise individual indicators of non-normal behavior for application in diagnostics and research. For this study, piglets (Sus domesticus) were filmed from lateral perspective during their first 10 h of life, an age at which maturation is quick and body mass and size have major consequences for survival. We then apply deep learning methods for point digitization, calculate joint angle profiles, and apply information-preserving transformations to retrieve a multivariate kinematic data set. We train probabilistic models to infer subject characteristics from kinematics. Model accuracy was validated for strides from piglets of normal birth weight (i.e., the category it was trained on), but the models infer the body mass and size of low birth weight (LBW) piglets (which were left out of training, out-of-sample inference) to be “normal.” The age of some (but not all) low birth weight individuals was underestimated, indicating developmental delay. Such individuals could be identified automatically, inspected, and treated accordingly. This workflow has potential for automatic, precise screening in livestock management.

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Overground Gait Kinematics and Muscle Activation Patterns in the Yucatan Mini Pig

Cited by 3 publications

References 63 publications

Methodological Advances in Studying Postnatal Locomotor Development

Methodological Advances in Studying Postnatal Locomotor Development

A Workflow for High Through-Put, High Precision Livestock Diagnostic Screening of Locomotor Kinematics

A workflow for automatic, high precision livestock diagnostic screening of locomotor kinematics

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