Dataset Information

Honeybees Prefer to Steer on a Smooth Wall With Tetrapod Gaits.

ABSTRACT: Insects are well equipped in walking on complex three-dimensional terrain, allowing them to overcome obstacles or catch prey. However, the gait transition for insects steering on a wall remains unexplored. Here, we find that honeybees adopted a tetrapod gait to change direction when climbing a wall. On the contrary to the common tripod gait, honeybees propel their body forward by synchronously stepping with both middle legs and then both front legs. This process ensures the angle of the central axis of the honeybee to be consistent with the crawling direction. Interestingly, when running in an alternating tripod gait, the central axis of honeybee sways around the center of mass under alternating tripod gait to maintain stability. Experimental results show that tripod, tetrapod, and random gaits result in the amazing consensus harmony on the climbing speed and gait stability, whether climbing on a smooth wall or walking on smooth ground.

SUBMITTER: Zhao J

PROVIDER: S-EPMC5930183 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Honeybees Prefer to Steer on a Smooth Wall With Tetrapod Gaits.

Zhao Jieliang J Zhu Fei F Yan Shaoze S

Journal of insect science (Online) 20180301 2

Insects are well equipped in walking on complex three-dimensional terrain, allowing them to overcome obstacles or catch prey. However, the gait transition for insects steering on a wall remains unexplored. Here, we find that honeybees adopted a tetrapod gait to change direction when climbing a wall. On the contrary to the common tripod gait, honeybees propel their body forward by synchronously stepping with both middle legs and then both front legs. This process ensures the angle of the central ...[more]

PMID: 29722862

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Project description:Computational models that predict in vivo joint loading and muscle forces can potentially enhance and augment our knowledge of both typical and pathological gaits. To adopt such models into clinical applications, studies validating modeling predictions are essential. This study created a full-body musculoskeletal model using data from the "Sixth Grand Challenge Competition to Predict in vivo Knee Loads." This model incorporates subject-specific geometries of the right leg in order to concurrently predict knee contact forces, ligament forces, muscle forces, and ground contact forces. The objectives of this paper are twofold: (1) to describe an electromyography (EMG)-driven modeling methodology to predict knee contact forces and (2) to validate model predictions by evaluating the model predictions against known values for a patient with an instrumented total knee replacement (TKR) for three distinctly different gait styles (normal, smooth, and bouncy gaits). The model integrates a subject-specific knee model onto a previously validated generic full-body musculoskeletal model. The combined model included six degrees-of-freedom (6DOF) patellofemoral and tibiofemoral joints, ligament forces, and deformable contact forces with viscous damping. The foot/shoe/floor interactions were modeled by incorporating shoe geometries to the feet. Contact between shoe segments and the floor surface was used to constrain the shoe segments. A novel EMG-driven feedforward with feedback trim motor control strategy was used to concurrently estimate muscle forces and knee contact forces from standard motion capture data collected on the individual subject. The predicted medial, lateral, and total tibiofemoral forces represented the overall measured magnitude and temporal patterns with good root-mean-squared errors (RMSEs) and Pearson's correlation (p2). The model accuracy was high: medial, lateral, and total tibiofemoral contact force RMSEs?=?0.15, 0.14, 0.21 body weight (BW), and (0.92?<?p2?<?0.96) for normal gait; RMSEs?=?0.18 BW, 0.21 BW, 0.29 BW, and (0.81?<?p2?<?0.93) for smooth gait; and RMSEs?=?0.21 BW, 0.22 BW, 0.33 BW, and (0.86?<?p2?<?0.95) for bouncy gait, respectively. Overall, the model captured the general shape, magnitude, and temporal patterns of the contact force profiles accurately. Potential applications of this proposed model include predictive biomechanics simulations, design of TKR components, soft tissue balancing, and surgical simulation.

Dataset Information

Honeybees Prefer to Steer on a Smooth Wall With Tetrapod Gaits.

Publications

Honeybees Prefer to Steer on a Smooth Wall With Tetrapod Gaits.

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