Study of animal locomotion

The study of animal locomotion is a branch of biology that investigates and quantifies how animals move.

Kinematics Kinematics is the study of how objects move, whether they are mechanical or living. In animal locomotion, kinematics is used to describe the motion of the body and limbs of an animal. The goal is ultimately to understand how the movement of individual limbs relates to the overall movement of an animal within its environment. Below highlights the key kinematic parameters used to quantify body and limb movement for different modes of animal locomotion.

Quantifying locomotion

Walking Legged locomotion is the dominant form of terrestrial locomotion, the movement on land. The motion of limbs is quantified by the kinematics of the limb itself (intralimb kinematics) and the coordination between limbs (interlimb kinematics).

To quantify the intralimb kinematics and interlimb coordination during walking, the stance and swing phases of the step cycle must be isolated. Stance is associated with the portion of the step where the leg contacts the ground, whereas, swing is where the leg lifts off the ground and moves forward along the body. High-speed videography is used to record the motion of the legs. Pose-estimation methods are then used to track key point(s) on each leg, typically at the joints of the leg. After extracting the positions of each leg throughout a recording, there are several ways of determining the stance and swing phases of the step cycle. One approach involves using peak and trough detection of the leg tip positions in ego-centric coordinates and after the animal has been aligned to a common heading (Fig. 1). Alternatively, swing and stance can be classified as leg tip velocities above and below a chosen threshold, respectively. In this case, leg tip velocities are calculated in allocentric, or world-oriented, coordinates. Once swing and stance phases are determined, the following kinematic and coordination parameters can be calculated.

Intralimb kinematic parameters Source:

Anterior Extreme Position (AEP): the forwardmost position of the leg (i.e. usually the start of stance phase). Posterior Extreme Position (PEP): the rearmost position of the leg (i.e. usually the start of swing phase). Step duration: elapsed time between two onsets of stance. Step frequency: inverse of stride duration (i.e. number of strides per second) Stance duration: time elapsed between stance onset and swing onset. Swing duration: time elapsed between swing onset and the subsequent stance onset . Step amplitude: the distance a leg travels during swing in a ego-centric reference frame. Step length: the distance from the stance onset to stance onset in a world reference frame. Stride range of motion: the leg's integrated path between stance onset and swing offset. Joint angles: Walking can also be quantified through the analysis of joint angles. During legged locomotion, an animal flexes and extends its joints in an oscillatory manner, creating a joint angle pattern that repeats across steps. The following are some useful joint angle analyses for characterizing walking: Joint angle trace: a trace of the angles that a joint exhibits during walking. Joint angle distribution: the distribution of angles of a joint. Joint angle extremes: the maximum (extension) and minimum (flexion) angle of a joint during walking. Joint angle variability across steps: the variability between joint angle traces of several steps.

Interlimb kinematic parameters Phase offsets: the lag of a leg relative to the stride period of a reference leg. Number of legs in stance: The number of legs in stance at a single point in time. Tripod coordination strength (TCS): specific to hexapod interlimb coordination, this parameter determines how much the interlimb coordination resembles the canonical tripod gait. TCS is calculated as the ratio of the total time legs belonging to a tripod (i.e. left front, middle right, and hind left legs, or vice versa) are in swing together, by the time elapsed between the first leg of the tripod that enters swing and the last leg of the same tripod that exits swing. Relationship between several joint angles: the relative angles of two joints, either from the same leg or between legs. For example, the angle of a human's left femur-tibia (knee) joint when the right femur-tibia joint is at its most flexed or extended angle.

Measures of walking stability Static stability: minimum distance from the center of mass (COM) to any edge of the support polygon created by the legs in stance for each moment in time. A walking animal is statically stable if there are enough legs to form the support polygon (i.e. 3 or more) and the COM is within the support polygon. Moreover, static stability is at its maximum when it lies at the center of the support polygon. Steps to calculate static stability are as follows:

Find which legs are in stance and the location of the center of mass. Note, if there are less than 3 legs in stance then the animal is not statically stable. Form the support polygon by creating edges between these legs in a clock-wise manner. Determine if the center of mass lies inside or outside of the support polygon. The ray casting algorithm is a common approach of finding if a point is located within a polygon. If the center of mass is outside of the polygon then the animal is statically unstable. If the center of mass is inside the support polygon, calculate static stability by computing the minimum distance of the center of mass to any edge of the polygon. Dynamic stability: dictates the degree to which deviations from periodic movement during walking will result in instability.

Analyzing kinematics across steps Quantifying walking often involves assessing the kinematics of individual steps. For more information on methods for acquiring this data, see Methods of Study. The first task is to parse walking data into individual steps. Methods for parsing individual steps from walking data rely heavily on the data collection process. At a high-level, walking data should be periodic with each cycle reflecting the movements of one step, and steps can therefore be parsed at the peaks of the signal. It is often useful to compare or pool step data. One difficulty in this pursuit is the variable length of steps both within and between legs. There are many ways to align steps, the following are a few useful methods.

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