Tracking the joints of arthropod legs using multiple images and inverse kinematics

Hwang, Sangchul; Choi, Young Hee

doi:10.1007/s12541-015-0089-y

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…Several euarthropod groups have been subject to kinematic examination using various methods (deVries et al . 2012; Hwang & Choi 2015; Vagts et al . 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Several euarthropod groups have been subject to kinematic examination using various methods (deVries et al 2012;Hwang & Choi 2015;Vagts et al 2017). Earlier studies considered arachnid appendage joints with in vivo measurements of dissected animals or live specimen observations (Petrunkevitch 1909;Ellis 1944;Manton 1977;Shultz 1989;Wolff et al 2016), while more recent studies have explored strike kinematics and run video-based ROM analyses to obtain angle values (Santer & Hebets 2009;Seiter et al 2019;McLean et al 2020).…”

Section: Kinematic Approaches Of Arthropod Jointsmentioning

confidence: 99%

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Kinematics of whip spider pedipalps: a 3D comparative morpho‐functional approach

2021

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Amblypygi are tropical and subtropical ambush predators that use elongated, raptorial pedipalps for different activities. Although pedipalp use in predation and courtship has been explored in videography in vivo analyses, kinematic ex vivo examination of these appendages has not been conducted. Here, we rectify this lack of data by using micro‐CT scans to 3D‐kinematically model the appendage morphology and the range of motion (ROM) of the joints for Damon medius and Heterophrynus elaphus. We illustrate the successful application of this technique to terrestrial euarthropods in determining the maximum ROM values for each pedipalp joint. We also note that, in life, these values would be lower due to motion restricting structures like tendons, arthrodial membranes, and muscles. We further compare our maximum values obtained here with data from video‐based motion analyses. The ROM of each joint shows the greatest flexibility in the femur‐tibia joint (140–150°), the lowest in the basitarsus‐claw joint (35–40°). ROM in the tibia‐basitarsus joint is markedly distinct (D. medius: 44°; H. elaphus: 105°). This disparity reflects how H. elaphus uses the joint in the capture basket, while D. medius uses the femur‐tibia joint to form the capture basket. We further illustrate notable vertical motion of the H. elaphus pedipalp compared to D. medius. This difference reflects the retro‐ventral trochanter apophysis of H. elaphus. Our study opens the possibility to further whip spider kinematic understanding. Examination of other taxa using this approach will result in a more comprehensive understanding of the ecological significance and ethological implications of this unique arachnid group.

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“…Several euarthropod groups have been subject to kinematic examination using various methods (deVries et al . 2012; Hwang & Choi 2015; Vagts et al . 2017).…”

Section: Discussionmentioning

confidence: 99%

Section: Kinematic Approaches Of Arthropod Jointsmentioning

confidence: 99%

Kinematics of whip spider pedipalps: a 3D comparative morpho‐functional approach

2021

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“…Hwang et al [103] followed a similar approach to the one proposed by John et al [92] but without the use of markers. They used a combination of six-color charge-coupled device (CCD) cameras (Sca640-70fc, BASLER Co., Schiller Park, IL, USA) for video recording of the insects.…”

Section: Video Tracking Aided By Hardwarementioning

confidence: 99%

Computer Methods for Automatic Locomotion and Gesture Tracking in Mice and Small Animals for Neuroscience Applications: A Survey

Abbas

Rodó

2019

Sensors

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Neuroscience has traditionally relied on manually observing laboratory animals in controlled environments. Researchers usually record animals behaving freely or in a restrained manner and then annotate the data manually. The manual annotation is not desirable for three reasons; (i) it is time-consuming, (ii) it is prone to human errors, and (iii) no two human annotators will 100% agree on annotation, therefore, it is not reproducible. Consequently, automated annotation for such data has gained traction because it is efficient and replicable. Usually, the automatic annotation of neuroscience data relies on computer vision and machine learning techniques. In this article, we have covered most of the approaches taken by researchers for locomotion and gesture tracking of specific laboratory animals, i.e. rodents. We have divided these papers into categories based upon the hardware they use and the software approach they take. We have also summarized their strengths and weaknesses.

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Comparison of linear and torsion-based dynamic modeling of a jumping robot via energy conversion

Choi

Jeong

Seo

2017

Int. J. Precis. Eng. Manuf.

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Tracking the joints of arthropod legs using multiple images and inverse kinematics

Cited by 4 publications

References 15 publications

Kinematics of whip spider pedipalps: a 3D comparative morpho‐functional approach

Kinematics of whip spider pedipalps: a 3D comparative morpho‐functional approach

Computer Methods for Automatic Locomotion and Gesture Tracking in Mice and Small Animals for Neuroscience Applications: A Survey

Comparison of linear and torsion-based dynamic modeling of a jumping robot via energy conversion

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