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Figure 4 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 4. Typical tracks produced in the walk. The faster the walk (and the longer the limbs and the shorter the trunk), the greater is the distance (d) between the ipsilateral front- and hind hooves (i.e. the degree of overstepping increases); horizontal axis: distance covered in m. (a) Slow walk and (b) Fast walk of a German warmblood.

Figure 8 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 8. Typical footfall pattern of the canter (German: Galopp) in its three varieties. (a) Right lead of a Paso Fino at slow speed; (b) Left lead of a German warmblood horse at normal speed; (c) Right lead of a medium sized German saddle horse at fast speed. The stride length increases with increasing speed. The Paso Fino places the hind hooves between the imprints of the fore hooves, because of slow speed. The warmblood has the same limb length as the Paso Fino, but it is placing the hind hooves beneath the prints of the fore hooves, because of higher speed. The German saddle horse is medium sized and places the hind hooves in front of the fore hooves. With increasing speed in the canter, the separation between all four hoofprints becomes clearer (in the example of right lead the group HL, HR, FL, FR.).

Figure 1 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 1. Horse hooves. (a) Hind hoof and fore hoof of a horse seen from below; (b) Longitudinal section through the mechanically relevant elements of the autopodium. The hoof is shown during the middle of the stance phase, while highest loads are acting. Dots at the tips of the hooves are indicating the points used for track measurement. The difference between the imprints of hind hoof and fore hooves is not obvious, so that both are hardly discernible in most tracks.

Figure 3 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 3. Relationship between trunk length and length of the limbs. The extremities are reduced to their "functional limb lengths". Step length (s) is the product of excursion angles (α or β) and limb lengths (for example s sin αl αĮ sin αĮ l). The = fa + fr longer the limbs, the lower the ground level below the animal, and the greater the distance (s) covered during each step, without any change of trunk length. The uppermost ground level indicates a lagging of the hind hoof behind the imprint of the fore hoof; the middle level indicates capping; the lowermost indicates overstepping. Excursion angles (α and β) are determined by the resultant GRF. Among living mammals, α usually is greater than αĮ, while β is commonly smaller than β Į; l – left forelimb in anteversion; l – fa fr left forelimb in retroversion; lha – left hind in anteversion; lhr – left hind in retroversion.

Figure 7 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 7. Part of the original tracks comparing fast running pace (a) and fast trot (b). In the running pace the contralateral hoofprints are grouped together with overstepping of the fore hoof over the contralateral hind hoof. In the trot the ipsilateral hoofprints are grouped with an overstepping of the front hoof over the ipsilateral hind hoof. The horizontal axis shows the distance covered in cm.

Figure 2 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 2. Raw data of two randomly chosen trackways; horizontal axis: distance covered in cm. (a) Slow tölt (i.e. amble); (b) Fast tölt of an Icelandic horse; FR – front right; HR – hind right; FL – front left; HL – hind left.

Figure 6 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 6. Typical tracks produced in the trot of a German warmblood. With higher speed, the overstepping (d) of the ipsilateral hind hoof is increasing. (b) Slow trot: the hind hoof is placed right on top of the fore hoof imprint (capping); (a) fast (extended) trot, which leads to marked overstepping. A third possibility is the placing of the hind hoof in front of the fore hoof at very slow speed (this is rarely done and not shown here).

Figure 5 in Do tracks yield reliable information on gaits? - Part 1: The case of horses

Figure 5. Typical track produced in the tölt (amble) of an Icelandic horse. In the amble the overstepping (d1) is greater than in the walk and the contralateral hoofprints are close to each other at fast speeds (d2). This is similar to the pace. (a) Slow tölt; (b) fast tölt.

opencc-by-nc-nd-4.0Nov 2018View details →

Mocap gait motion samples - Optical marker trajectories

======================= Summary ======================= This database gathers a set of optical marker-based motion capture (mocap) tracking samples. Each sample corresponds to a single acquisition containing the 3D trajectories of a set of markers along a continuous interval of time. Keywords: Motion capture, mocap, Gait analysis, marker tracking. ======================= Data description ======================= Several persons wearing small reflective balls (markers) were asked to walk normally while recorded using motion capture cameras. These cameras, previously calibrated, are thought to detect the 2D pixel image position of the markers against the background thanks to IR lightning they are provided with. The XYZ position can be afterwards recovered by means of photogrammetric methods, whereas the tracking is kept across the frames. This data set contains the raw 3D trajectories of the aforementioned markers along the time. The set of markers is the layout proposed by Kadaba, Ramakrishnan, and Wootten, from the Helen Hayes Hospital. More details can be found in 'Dynamics of Human Gait' from Vaughan et al. Check out 'HH_marker_arrangement.png' for a visual description on marker placement. This database was built on purpose to serve as ground truth for the doctoral research "Cloud Point Labeling in Optical Motion Capture Systems", written by Juan L. Jiménez B. and supervised by Prof. Manuel Graña, from the Computational Intelligence Group, University of the Basque Country (UPV/EHU), and expected to be presented by the beginning of 2019. This work has been partially supported by the EC through project CybSPEED funded by the H2020 MSCA-RISE grant agreement Num. 777720. ======================= Equipment ======================= The following elements were taken to harvest the data:   - Six (6) motion capture cameras model S250e from Natural Point Inc. ( https://optitrack.com/ );   - Fifteen (15) passive-reflective optical markers;   - One computer running motion capture software from s.t.t.;   - A number of other minor accessories as camera wall mounts, Ethernet wires, adhesive tape, coffee and time. ======================= Technical details =======================   Database size: 71 recordings between 1.5 and 7 seconds long, summing up more than 20.000 frames   Exercise: regular gait motion at different paces   People: 14 different persons of different ages and shapes were recorded. No gait pathologies openly acknowledged.   Number of markers: 15 (Helen Hayes marker system)   Native camera resolution: 800x800 pixels   Sampling frequency: 100Hz   Cartesian units: millimeters   Right handed reference frame, +Y vertical upwards, ground height at Y=~0 ======================= Data base format =======================   The database is composed by 71 different files, one per gait sequence. Each file is written in plain ASCII, comma separated values (CSV) format. Each line represents an instant of time (frame) containing the 3D Cartesian positions of all the 15 markers with to 2 mantissa digits and dot symbol as decimal separator. A triple 'nan nan nan' instead of actual numbers stands for marker occlusion and consequently no measured position can be given. The coordinates are numerically arranged as follows:       X1; Y1; Z1; X2; Y2; Z2; ... Xi; Yi; Zi; ... X15; Y15; Z15;        ... where 'i' refers to the i-th marker among the following list:    1- Right ASIS    2- Left ASIS    3- Sacrum    4- Right Femoral wand    5- Left Femoral wand    6- Right Femoral epicondyle    7- Left Femoral epicondyle    8- Right Tibial wand    9- Left Tibial wand   10- Right Malleolus   11- Left Malleolus   12- Right Heel   13- Left Heel   14- Right Metatarsal head II   15- Left Metatarsal head II ======================= Privacy statement ======================= The personal privacy of the volunteers, adults of 25 and over, remains protected since no confidential data has been collected at any time. The authors count on the express written consent of the company to use the gathered data in the scope of academic research and as ground truth for the aforementioned PhD Thesis, including its publication under the specified license terms. ======================= Further information ======================= If you find any mistake or experience any trouble in the interpretation of the data, please do not hesitate to contact us.

opencc-by-4.0May 2019View details →

Validity of accelerometry in step detection and gait speed measurement in orthogeriatric patients (DATASET)

see README.txt for descriptions of files and formats

opencc-by-4.0May 2021View details →

Multi-segment phase coupling to oscillatory visual drive, Gait & Posture (2021): Data

Data set accompanying the publication: Engel, D., Schwenk, J., Schütz, A., Morris, A. P., & Bremmer, F. (2021). Multi-segment phase coupling to oscillatory visual drive. Gait & posture, 86, 132–138. <a href="https://doi.org/10.1016/j.gaitpost.2021.03.010">https://doi.org/10.1016/j.gaitpost.2021.03.010</a>

Figure 16 in Support polygons and symmetrical gaits in mammals

Figure 16. Possible adaptive value of diagonal-sequence walking gaits in primates. At the moment of forefoot touchdown, when weight is about to be transferred to a new and untested substrate, the line of gravity (grey arrow: the vertical through the body's centre of mass, estimated here as the vertical through the midpoint of an ischium-to-occiput line) passes approximately through the supporting hindfoot (grey tone) in the D-S walk of the baboon (top), but not in the L-S walk of the horse (bottom). In primates or other arboreal animals with marked grasping specializations of the hind foot, the primate support pattern allows the animal to draw back or regain its balance if the new support breaks or bends precipitously.

Figure 11 in Support polygons and symmetrical gaits in mammals

Figure 11. Modified Hildebrand diagram for the walking gaits (average duty factor ≥ 50) in our data set. The theoretically relevant duty factor in each case – Sh for diagonal-sequence walks, Sf for lateral-sequence walks – is plotted against diagonality. The diagonal lines show the distribution predicted by the support-polygon model as initially formulated.

Figure 12 in Support polygons and symmetrical gaits in mammals

Figure 12. Modified Hildebrand diagram for our data set: revised support-polygon model. The relevant duty factor in each case – which is now Sf for L-S, D-C gaits (Rule 2: D = 100 – Sf) and Sh for the others – is plotted against diagonality. The diagonal lines show the distribution predicted for walking gaits by the revised support-pattern model. Compare Figs 3 and 11.

Figure 8 in Support polygons and symmetrical gaits in mammals

Figure 8. Values of diagonality predicted from the support-polygon model. Duty factors and graphic conventions as in Figure 4. To minimize overall bipedality while maximizing diagonal bipedality ('2-diag'), a quadruped walking with a lateral-sequence gait (A) should adopt a Dvalue equal to 100 minus the forelimb duty factor (100 − Sf: horizontal arrows). A quadruped using a diagonal-sequence walk (B) should adopt a D-value equal to the hindlimb duty factor (Sh: horizontal arrows). In A, this entails that forefoot liftoffs and ipsilateral hind footfalls should be simultaneous; in B, fore footfalls and ipsilateral hindfoot liftoffs should be simultaneous (vertical arrows). In both A and B, diagonal bipedality ('2-diag') comprises the minimal percentage (64%) of the stride period possible for these duty factors. The animal is supported on 3 legs ('3-ped') for the remaining 36% of the stride period.

Figure 15 in Support polygons and symmetrical gaits in mammals

Figure 15. Values of diagonality predicted for lateralsequence, lateral-couplets walks from the revised supportpolygon model. Duty factors and graphic conventions as in Figure 4. To minimize overall bipedality while maximizing unilateral bipedality ('2-unilat'), a quadruped walking with an L-S, L-C gait should adopt a D-value equal to the hindlimb duty factor minus 50 (horizontal arrows). This entails that fore footfalls and contralateral hind liftoffs should be simultaneous (vertical arrows). Compare Figure 8.

Figure 7 in Support polygons and symmetrical gaits in mammals

Figure 7. Curves of unilateral bipedality (Bu) and diagonal bipedality (Bd) against diagonality (D) for the general case where the duty factors of the hind- and forelimbs (Sh, Sf) are unequal. Kh = Sh − 50; Kf = Sf − 50. All variables represent durations expressed as percentages of the stride period (time between two successive falls of the same foot). See text for explanation.

Figure 6. Diagrammatic quadruped seen from above. Points A-D in Support polygons and symmetrical gaits in mammals

Figure 6. Diagrammatic quadruped seen from above. Points A-D represent the animal's four feet; point G represents the vertical drawn through its centre of gravity. The animal will be more nearly balanced when standing on two diagonally opposite feet (A, C) than when standing on two ipsilateral feet (A, D), as long as G is closer to line AC than to line AD – which will be the case in most situations.

Figure 2 in Support polygons and symmetrical gaits in mammals

Figure 2. Plot of diagonality against (average) duty factor: the Hildebrand diagram. Positions of some mammalian gait types (two-letter codes) are plotted on the diagram. DS, diagonal-sequence walks; LS, lateral-sequence walks; RP, running pace; RT, running trot; WP, walking pace; WT, walking trot.

Figure 10 in Support polygons and symmetrical gaits in mammals

Figure 10. Running gaits (Sh <50> Sf) in our data, plotted on the Hildebrand diagram. The arrow ('trot line') indicates the diagonality predicted for running gaits (D = 50).