Limits...
A universal approach to determine footfall timings from kinematics of a single foot marker in hoofed animals.

Starke SD, Clayton HM - PeerJ (2015)

Bottom Line: While we found that use of velocity thresholds for foot on detection results in biased event estimates for the foot on the inside of the circle at trot, adjusting thresholds for this condition negated the effect.For the final four algorithms, we found no noteworthy bias between conditions or between front- and hind-foot timings.Different force thresholds in the range of 50 to 150 N had the greatest systematic effect on foot-off estimates in the hind limbs (up to on average 16 ms per condition), being greater than the effect on foot-on estimates or foot-off estimates in the forelimbs (up to on average ±7 ms per condition).

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Electronic, Electrical and Systems Engineering, University of Birmingham , Edgbaston, Birmingham, West Midlands , UK.

ABSTRACT
The study of animal movement commonly requires the segmentation of continuous data streams into individual strides. The use of forceplates and foot-mounted accelerometers readily allows the detection of the foot-on and foot-off events that define a stride. However, when relying on optical methods such as motion capture, there is lack of validated robust, universally applicable stride event detection methods. To date, no method has been validated for movement on a circle, while algorithms are commonly specific to front/hind limbs or gait. In this study, we aimed to develop and validate kinematic stride segmentation methods applicable to movement on straight line and circle at walk and trot, which exclusively rely on a single, dorsal hoof marker. The advantage of such marker placement is the robustness to marker loss and occlusion. Eight horses walked and trotted on a straight line and in a circle over an array of multiple forceplates. Kinetic events were detected based on the vertical force profile and used as the reference values. Kinematic events were detected based on displacement, velocity or acceleration signals of the dorsal hoof marker depending on the algorithm using (i) defined thresholds associated with derived movement signals and (ii) specific events in the derived movement signals. Method comparison was performed by calculating limits of agreement, accuracy, between-horse precision and within-horse precision based on differences between kinetic and kinematic event. In addition, we examined the effect of force thresholds ranging from 50 to 150 N on the timings of kinetic events. The two approaches resulted in very good and comparable performance: of the 3,074 processed footfall events, 95% of individual foot on and foot off events differed by no more than 26 ms from the kinetic event, with average accuracy between -11 and 10 ms and average within- and between horse precision ≤8 ms. While the event-based method may be less likely to suffer from scaling effects, on soft ground the threshold-based method may prove more valuable. While we found that use of velocity thresholds for foot on detection results in biased event estimates for the foot on the inside of the circle at trot, adjusting thresholds for this condition negated the effect. For the final four algorithms, we found no noteworthy bias between conditions or between front- and hind-foot timings. Different force thresholds in the range of 50 to 150 N had the greatest systematic effect on foot-off estimates in the hind limbs (up to on average 16 ms per condition), being greater than the effect on foot-on estimates or foot-off estimates in the forelimbs (up to on average ±7 ms per condition).

No MeSH data available.


Related in: MedlinePlus

Threshold-based footfall detection method.(A) Principle for foot on (top, red) and foot off (bottom, cyan) detection based on a threshold in resultant speed for foot on and a threshold in distance travelled for foot off. (B) Detailed illustration of the foot-off detection approach: hoof height is extracted during stance; foot off then corresponds to the first frame at which the horizontal distance travelled by the marker exceeds the marker height in stance. (C) Kinematic (dashed lines) and kinetic (solid lines) event detection for foot on (red) and foot off (cyan) illustrated for a single stride of a forelimb during trot on a circle. Top row: resultant speed shown at two magnifications; middle row: distance measurements of horizontal distance travelled relative to the marker hoof height position during stance (left) as well as vertical displacement (right); bottom row: vertical ground reaction force shown at two magnifications. Arrows are shown in those data fields that are used to determine kinematic events. Grey: raw data (unfiltered) for resultant speed. Vertical displacement is given as a reference. Vertical blue dotted line: approximate end of stance. Horizontal green dashed line: 75 N force threshold.
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fig-1: Threshold-based footfall detection method.(A) Principle for foot on (top, red) and foot off (bottom, cyan) detection based on a threshold in resultant speed for foot on and a threshold in distance travelled for foot off. (B) Detailed illustration of the foot-off detection approach: hoof height is extracted during stance; foot off then corresponds to the first frame at which the horizontal distance travelled by the marker exceeds the marker height in stance. (C) Kinematic (dashed lines) and kinetic (solid lines) event detection for foot on (red) and foot off (cyan) illustrated for a single stride of a forelimb during trot on a circle. Top row: resultant speed shown at two magnifications; middle row: distance measurements of horizontal distance travelled relative to the marker hoof height position during stance (left) as well as vertical displacement (right); bottom row: vertical ground reaction force shown at two magnifications. Arrows are shown in those data fields that are used to determine kinematic events. Grey: raw data (unfiltered) for resultant speed. Vertical displacement is given as a reference. Vertical blue dotted line: approximate end of stance. Horizontal green dashed line: 75 N force threshold.

Mentions: Eight unshod Arabian horses (mean ± SD weight: 448 ± 19 kg; height at the withers: 149.6 ± 2.6 cm, height at the hip: 150.4 ± 2.8 cm) were equipped with retro-reflective markers attached to the proximal aspect of the dorsal hoof wall on each of the four feet (Fig. 1). Horses were visually assessed for lameness by Dr. Clayton and passed as moving within the margins of what is perceived ‘normal.’ Marker movement in 3D space was recorded at 100 Hz using an optical motion capture system (Motion Analysis Corporation, Santa Rosa, California, USA). The error in a linear measurement of 1,000 mm was <0.8 mm. Horses repeatedly walked and trotted in hand on a straight line and on the lunge on a 3 m radius circle, moving both clockwise (‘right rein’) and anti-clockwise (‘left rein’). This radius was chosen to correspond with the smallest diameter circle (volte) performed in dressage competitions as specified by the International Equestrian Federation. 11


A universal approach to determine footfall timings from kinematics of a single foot marker in hoofed animals.

Starke SD, Clayton HM - PeerJ (2015)

Threshold-based footfall detection method.(A) Principle for foot on (top, red) and foot off (bottom, cyan) detection based on a threshold in resultant speed for foot on and a threshold in distance travelled for foot off. (B) Detailed illustration of the foot-off detection approach: hoof height is extracted during stance; foot off then corresponds to the first frame at which the horizontal distance travelled by the marker exceeds the marker height in stance. (C) Kinematic (dashed lines) and kinetic (solid lines) event detection for foot on (red) and foot off (cyan) illustrated for a single stride of a forelimb during trot on a circle. Top row: resultant speed shown at two magnifications; middle row: distance measurements of horizontal distance travelled relative to the marker hoof height position during stance (left) as well as vertical displacement (right); bottom row: vertical ground reaction force shown at two magnifications. Arrows are shown in those data fields that are used to determine kinematic events. Grey: raw data (unfiltered) for resultant speed. Vertical displacement is given as a reference. Vertical blue dotted line: approximate end of stance. Horizontal green dashed line: 75 N force threshold.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493675&req=5

fig-1: Threshold-based footfall detection method.(A) Principle for foot on (top, red) and foot off (bottom, cyan) detection based on a threshold in resultant speed for foot on and a threshold in distance travelled for foot off. (B) Detailed illustration of the foot-off detection approach: hoof height is extracted during stance; foot off then corresponds to the first frame at which the horizontal distance travelled by the marker exceeds the marker height in stance. (C) Kinematic (dashed lines) and kinetic (solid lines) event detection for foot on (red) and foot off (cyan) illustrated for a single stride of a forelimb during trot on a circle. Top row: resultant speed shown at two magnifications; middle row: distance measurements of horizontal distance travelled relative to the marker hoof height position during stance (left) as well as vertical displacement (right); bottom row: vertical ground reaction force shown at two magnifications. Arrows are shown in those data fields that are used to determine kinematic events. Grey: raw data (unfiltered) for resultant speed. Vertical displacement is given as a reference. Vertical blue dotted line: approximate end of stance. Horizontal green dashed line: 75 N force threshold.
Mentions: Eight unshod Arabian horses (mean ± SD weight: 448 ± 19 kg; height at the withers: 149.6 ± 2.6 cm, height at the hip: 150.4 ± 2.8 cm) were equipped with retro-reflective markers attached to the proximal aspect of the dorsal hoof wall on each of the four feet (Fig. 1). Horses were visually assessed for lameness by Dr. Clayton and passed as moving within the margins of what is perceived ‘normal.’ Marker movement in 3D space was recorded at 100 Hz using an optical motion capture system (Motion Analysis Corporation, Santa Rosa, California, USA). The error in a linear measurement of 1,000 mm was <0.8 mm. Horses repeatedly walked and trotted in hand on a straight line and on the lunge on a 3 m radius circle, moving both clockwise (‘right rein’) and anti-clockwise (‘left rein’). This radius was chosen to correspond with the smallest diameter circle (volte) performed in dressage competitions as specified by the International Equestrian Federation. 11

Bottom Line: While we found that use of velocity thresholds for foot on detection results in biased event estimates for the foot on the inside of the circle at trot, adjusting thresholds for this condition negated the effect.For the final four algorithms, we found no noteworthy bias between conditions or between front- and hind-foot timings.Different force thresholds in the range of 50 to 150 N had the greatest systematic effect on foot-off estimates in the hind limbs (up to on average 16 ms per condition), being greater than the effect on foot-on estimates or foot-off estimates in the forelimbs (up to on average ±7 ms per condition).

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Electronic, Electrical and Systems Engineering, University of Birmingham , Edgbaston, Birmingham, West Midlands , UK.

ABSTRACT
The study of animal movement commonly requires the segmentation of continuous data streams into individual strides. The use of forceplates and foot-mounted accelerometers readily allows the detection of the foot-on and foot-off events that define a stride. However, when relying on optical methods such as motion capture, there is lack of validated robust, universally applicable stride event detection methods. To date, no method has been validated for movement on a circle, while algorithms are commonly specific to front/hind limbs or gait. In this study, we aimed to develop and validate kinematic stride segmentation methods applicable to movement on straight line and circle at walk and trot, which exclusively rely on a single, dorsal hoof marker. The advantage of such marker placement is the robustness to marker loss and occlusion. Eight horses walked and trotted on a straight line and in a circle over an array of multiple forceplates. Kinetic events were detected based on the vertical force profile and used as the reference values. Kinematic events were detected based on displacement, velocity or acceleration signals of the dorsal hoof marker depending on the algorithm using (i) defined thresholds associated with derived movement signals and (ii) specific events in the derived movement signals. Method comparison was performed by calculating limits of agreement, accuracy, between-horse precision and within-horse precision based on differences between kinetic and kinematic event. In addition, we examined the effect of force thresholds ranging from 50 to 150 N on the timings of kinetic events. The two approaches resulted in very good and comparable performance: of the 3,074 processed footfall events, 95% of individual foot on and foot off events differed by no more than 26 ms from the kinetic event, with average accuracy between -11 and 10 ms and average within- and between horse precision ≤8 ms. While the event-based method may be less likely to suffer from scaling effects, on soft ground the threshold-based method may prove more valuable. While we found that use of velocity thresholds for foot on detection results in biased event estimates for the foot on the inside of the circle at trot, adjusting thresholds for this condition negated the effect. For the final four algorithms, we found no noteworthy bias between conditions or between front- and hind-foot timings. Different force thresholds in the range of 50 to 150 N had the greatest systematic effect on foot-off estimates in the hind limbs (up to on average 16 ms per condition), being greater than the effect on foot-on estimates or foot-off estimates in the forelimbs (up to on average ±7 ms per condition).

No MeSH data available.


Related in: MedlinePlus