add_knee_ankle_hip_ratios: Add knee-to-hip, ankle-to-hip, and knee-to-ankle separation...

In steenharsted/mocapr: Functions to import, plot, animate, and analyse motion capture data

Add knee-to-hip, ankle-to-hip, and knee-to-ankle separation ratios.

Description

The ratios are calculated in the anatomical frontal plane, using joint-center positions from both lower extremities. Therefore, they should only be used to analyze bilateral symetric movements (e.g., squats, or bilateral jump-landings).

Knee-to-hip separation ratio (KHR) is the distance between the knee joint centers divided by the distance between the hip joint centers.
Ankle-to-hip separation ratio (AHR) is the distance between the ankle joint centers divided by the distance between the hip joint centers.
Knee-to-ankle separation ratio (KASR) is the distance between the knee joint centers divided by the distance between the ankle joint centers.

knee-to-hip and ankle-to-hip separation ratio was orignially described Barber-Westin et al. and Noyes et al. as "Normalised knee separation distance" and "Normalised ankle separation distance". Mizner et. al described the "Knee-to-ankle separation ratio" in 2012. The measures were originally developed for 2D analysis of video recordings.

Usage

add_knee_ankle_hip_ratios(.data)

Arguments

.data

A tbbile containg ankle, knee, and hip spatial joint center positions in the anatomical frontal plane. These positions can be generated from global spatial positions using project_full_body_to_AP().

Value

The tibble supplied in .data argument with the added columns KHR, AHR, and KASR.

Equations

Knee-to-hip separation ratio:

Ankle-to-hip separation ratio:

Knee-to-ankle separation ratio:

Figures

Knee-to-hip separation ratio:

Ankle-to-hip separation ratio:

Knee-to-ankle separation ratio:

References

Barber-Westin SD, Galloway M, Noyes FR, Corbett G, Walsh C. Assessment of lower limb neuromuscular control in prepubescent athletes. Am J Sports Med. 2005;33(12):1853-60.

Noyes FR, Barber-Westin SD, Fleckenstein C, Walsh C, West J. The drop-jump screening test: difference in lower limb control by gender and effect of neuromuscular training in female athletes. Am J Sports Med. 2005;33(2):197-207.

Mizner RL, Chmielewski TL, Toepke JJ, Tofte KB. Comparison of 2-dimensional measurement techniques for predicting knee angle and moment during a drop vertical jump. Clin J Sport Med. 2012;22(3):221-7.

Harsted S, Holsgaard-Larsen A, Hestbaek L, Boyle E, Lauridsen HH. Concurrent validity of lower extremity kinematics and jump characteristics captured in pre-school children by a markerless 3D motion capture system. Chiropr Man Therap. 2019;27:39.

Examples

# Prepare data
df <- dplyr::filter(mocapr::mocapr_synthetic_data, sample == 1)
add_knee_ankle_hip_ratios(df)

# The ratio measures are unaffected by the depth of the pelvis.

df2 <- dplyr::filter(mocapr::mocapr_synthetic_data, sample == 2)
df2 <- add_knee_ankle_hip_ratios(df2)
animate_anatomical(df2,
                  planes = "R",
                  return_plot = TRUE,
                  col_facets = col_fa,
                  row_facets = row_fa)+
ggplot2::geom_text(ggplot2::aes(label = paste0("KHR: ", round(KHR, 2)),
                  x = mean(value), y= max(U)+30), color = "black", size = 3)+
ggplot2::geom_text(ggplot2::aes(label = paste0("AHR: ", round(AHR, 2)),
                  x = mean(value), y= max(U)+20), color = "black", size = 3)+
ggplot2::geom_text(ggplot2::aes(label = paste0("KASR: ", round(KASR, 2)),
                  x = mean(value), y= max(U)+10), color = "black", size = 3)

steenharsted/mocapr documentation built on Feb. 1, 2024, 1:49 p.m.