config/muscles/recti.r
In ime-luebeck/semgsim: Simulating surface electromyographic (sEMG) and force signals
##### Rectus Abdominis Superior Definitions #####
generate_rectus_part <- function(width, thickness, length, base_pos, emg_force_rel) {
## Create the muscle object.
## Set the base shape of the muscle endplate.
## Currently supported shapes are:
## - "rect". Will be interpreted as the unit square [0,1]x[0,1].
rectus_part <- create_rect_muscle(width = width,
thickness = thickness)
## Define the geometrical transformation by which the endplate base shape will
## be turned into its final shape. Must be some function that takes a 2D vector
## and returns a 3D vector, as this is also used to position the endplate in 3D
## space.
rectus_part$shape_transformation <-
function(x) c(x[1] * width + base_pos[1],
-x[2] * thickness,
base_pos[2])
## Define the muscle fiber shape. This must be an object providing a method
## $pos(x) that implements a parametrization of the fiber shape curve. It takes
## a numerical argument x between 0 and 1 denoting the relative position on the
## fiber and returns a 3D vector containing the position of the curve in 3D
## space at that length. The curve is assumed to start at (0,0) and to be
## normalized to length 1, i.e. the length of the curve given by pos(x) from x=0
## to x=1 is equal to one.
## Here, we set all fibers to be straight lines.
rectus_part$fiber_shape <- create_straight_line()
## Define the rotation that will be applied to the muscle fiber's base shape,
## depending on their relative position on the muscle base shape.
## The absolute position in 3D space of a point on the fiber is then given in
## terms of its relative position on the fiber (which is between 0 and 1) as
##
## x(x_rel) = fiber$innervation_zone + fiber$length * translation,
##
## where
##
## translation =
## rotate3D_lh(fiber_shape$pos(x.rel) -
## fiber_shape$pos(innervation_zone_rel),
## fiber_rotations(fiber_base_pos_rel_to_muscle))
##
## and rotate3D_lh(x, angles) rotates the vector x by the three angles specified
## in angles around the x, y and z axis, respectively. Positive angles result in
## counter-clockwise rotations.
rectus_part$fiber_rotations <- function(pos_rel_to_muscle)
c(0, 0, 0)
## Define how the muscle fibers will be placed inside a given MU.
rectus_part$rel_fiber_distributor <- distribute_fibers_unif
## Define the base length of the muscles fibers as a function of their position
## on the muscle endplate.
rectus_part$fiber_base_length_calculator <- function(base_pos_rel_to_muscle) length
## Define a random relative variation of the fiber length.
## Don't forget to keep the relation between this and fiber_length_max (see
## below) up to date.
rectus_part$variation <- 0.025
rectus_part$fiber_length_randomizer <-
function() runif(n = 1,
min = 1 - rectus_part$variation,
max = 1 + rectus_part$variation)
## Give an upper bound for the value
##
## fiber_base_length_calculator() * fiber_length_randomizer().
##
## This will be used for estimating an upper bound on the time scale length of
## an IAP impulse response as measured on the skin.
rectus_part$fiber_length_max <-
length * (1 + rectus_part$variation)
## Define, how the relative locations of the innervation zones of the muscle
## fibers will be determined.
rectus_part$innervation_zone_placer <-
function(fiber) rnorm_bounded(min = 0.4, max = 0.6, n_sigma = 3)
## Give an upper bound on
##
## max(innervation_zone_placer(fiber), 1 - innervation_zone_placer(fiber)).
##
## This will be used for estimating an upper bound on the time scale length of
## an IAP impulse response as measured on the skin.
rectus_part$fiber_rel_half_length_max <- 0.6
## Define whether the conduction velocity of the muscle fibers can change with
## time.
## Here, we take it to be constant.
rectus_part$cv_variability <- "const"
rectus_part$MU_class <- "MU_circ"
## MU Pool Organization ####
rectus_part$num_MUs <- 50
rectus_part$random_MU_params <- list(
fiber_density = list(shape = 8, scale = 9 / mm_^2,
min = 1 / mm_^2, max = 30 / mm_^2))
## Rate Coding and Recruitment ##
## Define the parameters that specify the characteristics of the rate coding
## strategy employed in the muscle.
rectus_part$rate_coding_params <- list()
if(exists('alternative_rate_coding') && alternative_rate_coding) {
# Use our newly proposed rate coding model
rectus_part$rate_coding_params$alternative_rate_coding <- TRUE
rectus_part$rate_coding_params$A <- 20
rectus_part$rate_coding_params$B <- 1.5
rectus_part$rate_coding_params$C <- 30
rectus_part$rate_coding_params$D <- 13
rectus_part$rate_coding_params$E <- 8
rectus_part$rate_coding_params$F <- 8
rectus_part$rate_coding_params$G <- 0.05
} else {
# Use the model of De Luca and Hostage (2010)
rectus_part$rate_coding_params$alternative_rate_coding <- FALSE
## Define the minimum and maximum firing rate (in pps, pulses per second) of all
## MUs in the muscle.
rectus_part$rate_coding_params$A <- 100
rectus_part$rate_coding_params$B <- 0.2
rectus_part$rate_coding_params$C <- -25
rectus_part$rate_coding_params$D <- 7
rectus_part$rate_coding_params$E <- 20
}
## Define the ratio of maximum muscle force at which MU recruitment is complete.
## Must be a value between 0 and 1.
rec_stop <- 0.6
rectus_part$rate_coding_params$rec_model <- 2
## Shape parameter of the recruitment model
rectus_part$rate_coding_params$shape_b <- 0.2
a1 <- log(rec_stop) / rectus_part$num_MUs
a2 <- log(rec_stop/ rectus_part$rate_coding_params$shape_b) / rectus_part$num_MUs
if (rectus_part$rate_coding_params$rec_model == 1) {
rec_start <- exp(a1 * 1)
} else
rec_start <- rectus_part$rate_coding_params$shape_b * 1 * exp(a2 * 1) / rectus_part$num_MUs
## Size principle parameters
LINEAR <- 1 # Variable is linearly related to the recruitment threshold
SQUARE <- 2 # Variable is related to the square of the recruitment threshold
# Intracellular conductivity, cf. Dimitrova (1974) http://www.ncbi.nlm.nih.gov/pubmed/4457323
cond_ic <- 1
# Range of fiber radius, cf. Hwang et al. (2013) [for index finger!]
# https://doi.org/10.3109/2000656X.2012.755988
min_fib_rad <- 12e-6
max_fib_rad <- 20e-6
rectus_part$MU_size_params <- list(rec_thresh = list(min=rec_start, max=rec_stop, lower_bound=0.005,
relation=LINEAR, round=FALSE),
peak_force = list(min=1, max=100, lower_bound=0.1,
relation=LINEAR, round=FALSE),
cv = list(min=2.5, max=5.5, lower_bound=2,
relation=LINEAR, round=FALSE),
twitch_t_rise = list(shape = 7, min = 50 * ms_, max = 30 * ms_,
lower_bound = 20 * ms_, relation=LINEAR, round=FALSE),
twitch_t_half_rel = list(shape = 7, min = 125 * ms_, max = 25 * ms_,
lower_bound = 20 * ms_, relation=LINEAR, round=FALSE),
twitch_t_lead = list(shape = 10, min = 10 * ms_, max = 3.5 * ms_, lower_bound = 3 * ms_,
relation=LINEAR, round=FALSE),
IAP_scale_amp = list(shape = 12,
min = cond_ic*pi*min_fib_rad^2,
max = cond_ic*pi*max_fib_rad^2,
lower_bound = 0.8*cond_ic*pi*min_fib_rad^2,
relation=SQUARE,
round=FALSE),
peak_fiber_force = list(shape = 8, min = 0.033, max = 0.1, lower_bound = 0.025,
relation=SQUARE, round=FALSE))
## Nonlinear force gain factor parameters
rectus_part$twitch_r <- 0.85
rectus_part$twitch_c <- 2.5
## Define the way in which the motor unit (MU) regions are determined from the
## muscle endplate region.
rectus_part$MU_distributor <-
function(MUs) distribute_MUs_unif(MUs = MUs,
muscle = rectus_part,
tiling = c(3, 2))
rectus_part
}
## For ref, refer to Rankin, Stokes, Newham / Abdominal Muscle Size and Symmetry in normal Subjects, 2006, Muscle & Nerve
## Right RA thickness 1.25, cross/sectional area 8.27
## Left RA thickness 1.24, cross/sectional area 8.15
## both for mean male subjects
## Teyhen, Chils et al. 2012 report mean over both left and right /male again/ to be 1.41, 8.00 which is in good agreement.
## Delp et al. 2001 report cumulative recti lengths of mean 34.3cm.
left_thickness = 1.24 * cm_
right_thickness = 1.25 * cm_
left_width = 8.15 / 1.24 * cm_
right_width = 8.27 / 1.25 * cm_
lower_length = 10 * cm_
mid_length = 12 * cm_
upper_length = 10 * cm_
rectus_la <- generate_rectus_part(width = left_width, thickness = left_thickness, length = lower_length, base_pos = c(-left_width - 1 * mm_, 0), emg_force_rel = emg_force_rel)
rectus_lb <- generate_rectus_part(width = left_width, thickness = left_thickness, length = mid_length, base_pos = c(-left_width - 1 * mm_, lower_length + 1 * cm_), emg_force_rel = emg_force_rel)
rectus_lc <- generate_rectus_part(width = left_width, thickness = left_thickness, length = upper_length, base_pos = c(-left_width - 1 * mm_, lower_length + mid_length + 2 * cm_), emg_force_rel = emg_force_rel)
rectus_ra <- generate_rectus_part(width = right_width, thickness = right_thickness, length = lower_length, base_pos = c(1 * mm_, 0), emg_force_rel = emg_force_rel)
rectus_rb <- generate_rectus_part(width = right_width, thickness = right_thickness, length = mid_length, base_pos = c(1 * mm_, lower_length + 1 * cm_), emg_force_rel = emg_force_rel)
rectus_rc <- generate_rectus_part(width = right_width, thickness = right_thickness, length = upper_length, base_pos = c(1 * mm_, lower_length + mid_length + 2 * cm_), emg_force_rel = emg_force_rel)
recti <- list(rectus_la, rectus_lb, rectus_lc, rectus_ra, rectus_rb, rectus_rc)
ime-luebeck/semgsim documentation built on April 14, 2022, 11:02 p.m.
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##### Rectus Abdominis Superior Definitions #####
generate_rectus_part <- function(width, thickness, length, base_pos, emg_force_rel) {
## Create the muscle object.
## Set the base shape of the muscle endplate.
## Currently supported shapes are:
## - "rect". Will be interpreted as the unit square [0,1]x[0,1].
rectus_part <- create_rect_muscle(width = width,
thickness = thickness)
## Define the geometrical transformation by which the endplate base shape will
## be turned into its final shape. Must be some function that takes a 2D vector
## and returns a 3D vector, as this is also used to position the endplate in 3D
## space.
rectus_part$shape_transformation <-
function(x) c(x[1] * width + base_pos[1],
-x[2] * thickness,
base_pos[2])
## Define the muscle fiber shape. This must be an object providing a method
## $pos(x) that implements a parametrization of the fiber shape curve. It takes
## a numerical argument x between 0 and 1 denoting the relative position on the
## fiber and returns a 3D vector containing the position of the curve in 3D
## space at that length. The curve is assumed to start at (0,0) and to be
## normalized to length 1, i.e. the length of the curve given by pos(x) from x=0
## to x=1 is equal to one.
## Here, we set all fibers to be straight lines.
rectus_part$fiber_shape <- create_straight_line()
## Define the rotation that will be applied to the muscle fiber's base shape,
## depending on their relative position on the muscle base shape.
## The absolute position in 3D space of a point on the fiber is then given in
## terms of its relative position on the fiber (which is between 0 and 1) as
##
## x(x_rel) = fiber$innervation_zone + fiber$length * translation,
##
## where
##
## translation =
## rotate3D_lh(fiber_shape$pos(x.rel) -
## fiber_shape$pos(innervation_zone_rel),
## fiber_rotations(fiber_base_pos_rel_to_muscle))
##
## and rotate3D_lh(x, angles) rotates the vector x by the three angles specified
## in angles around the x, y and z axis, respectively. Positive angles result in
## counter-clockwise rotations.
rectus_part$fiber_rotations <- function(pos_rel_to_muscle)
c(0, 0, 0)
## Define how the muscle fibers will be placed inside a given MU.
rectus_part$rel_fiber_distributor <- distribute_fibers_unif
## Define the base length of the muscles fibers as a function of their position
## on the muscle endplate.
rectus_part$fiber_base_length_calculator <- function(base_pos_rel_to_muscle) length
## Define a random relative variation of the fiber length.
## Don't forget to keep the relation between this and fiber_length_max (see
## below) up to date.
rectus_part$variation <- 0.025
rectus_part$fiber_length_randomizer <-
function() runif(n = 1,
min = 1 - rectus_part$variation,
max = 1 + rectus_part$variation)
## Give an upper bound for the value
##
## fiber_base_length_calculator() * fiber_length_randomizer().
##
## This will be used for estimating an upper bound on the time scale length of
## an IAP impulse response as measured on the skin.
rectus_part$fiber_length_max <-
length * (1 + rectus_part$variation)
## Define, how the relative locations of the innervation zones of the muscle
## fibers will be determined.
rectus_part$innervation_zone_placer <-
function(fiber) rnorm_bounded(min = 0.4, max = 0.6, n_sigma = 3)
## Give an upper bound on
##
## max(innervation_zone_placer(fiber), 1 - innervation_zone_placer(fiber)).
##
## This will be used for estimating an upper bound on the time scale length of
## an IAP impulse response as measured on the skin.
rectus_part$fiber_rel_half_length_max <- 0.6
## Define whether the conduction velocity of the muscle fibers can change with
## time.
## Here, we take it to be constant.
rectus_part$cv_variability <- "const"
rectus_part$MU_class <- "MU_circ"
## MU Pool Organization ####
rectus_part$num_MUs <- 50
rectus_part$random_MU_params <- list(
fiber_density = list(shape = 8, scale = 9 / mm_^2,
min = 1 / mm_^2, max = 30 / mm_^2))
## Rate Coding and Recruitment ##
## Define the parameters that specify the characteristics of the rate coding
## strategy employed in the muscle.
rectus_part$rate_coding_params <- list()
if(exists('alternative_rate_coding') && alternative_rate_coding) {
# Use our newly proposed rate coding model
rectus_part$rate_coding_params$alternative_rate_coding <- TRUE
rectus_part$rate_coding_params$A <- 20
rectus_part$rate_coding_params$B <- 1.5
rectus_part$rate_coding_params$C <- 30
rectus_part$rate_coding_params$D <- 13
rectus_part$rate_coding_params$E <- 8
rectus_part$rate_coding_params$F <- 8
rectus_part$rate_coding_params$G <- 0.05
} else {
# Use the model of De Luca and Hostage (2010)
rectus_part$rate_coding_params$alternative_rate_coding <- FALSE
## Define the minimum and maximum firing rate (in pps, pulses per second) of all
## MUs in the muscle.
rectus_part$rate_coding_params$A <- 100
rectus_part$rate_coding_params$B <- 0.2
rectus_part$rate_coding_params$C <- -25
rectus_part$rate_coding_params$D <- 7
rectus_part$rate_coding_params$E <- 20
}
## Define the ratio of maximum muscle force at which MU recruitment is complete.
## Must be a value between 0 and 1.
rec_stop <- 0.6
rectus_part$rate_coding_params$rec_model <- 2
## Shape parameter of the recruitment model
rectus_part$rate_coding_params$shape_b <- 0.2
a1 <- log(rec_stop) / rectus_part$num_MUs
a2 <- log(rec_stop/ rectus_part$rate_coding_params$shape_b) / rectus_part$num_MUs
if (rectus_part$rate_coding_params$rec_model == 1) {
rec_start <- exp(a1 * 1)
} else
rec_start <- rectus_part$rate_coding_params$shape_b * 1 * exp(a2 * 1) / rectus_part$num_MUs
## Size principle parameters
LINEAR <- 1 # Variable is linearly related to the recruitment threshold
SQUARE <- 2 # Variable is related to the square of the recruitment threshold
# Intracellular conductivity, cf. Dimitrova (1974) http://www.ncbi.nlm.nih.gov/pubmed/4457323
cond_ic <- 1
# Range of fiber radius, cf. Hwang et al. (2013) [for index finger!]
# https://doi.org/10.3109/2000656X.2012.755988
min_fib_rad <- 12e-6
max_fib_rad <- 20e-6
rectus_part$MU_size_params <- list(rec_thresh = list(min=rec_start, max=rec_stop, lower_bound=0.005,
relation=LINEAR, round=FALSE),
peak_force = list(min=1, max=100, lower_bound=0.1,
relation=LINEAR, round=FALSE),
cv = list(min=2.5, max=5.5, lower_bound=2,
relation=LINEAR, round=FALSE),
twitch_t_rise = list(shape = 7, min = 50 * ms_, max = 30 * ms_,
lower_bound = 20 * ms_, relation=LINEAR, round=FALSE),
twitch_t_half_rel = list(shape = 7, min = 125 * ms_, max = 25 * ms_,
lower_bound = 20 * ms_, relation=LINEAR, round=FALSE),
twitch_t_lead = list(shape = 10, min = 10 * ms_, max = 3.5 * ms_, lower_bound = 3 * ms_,
relation=LINEAR, round=FALSE),
IAP_scale_amp = list(shape = 12,
min = cond_ic*pi*min_fib_rad^2,
max = cond_ic*pi*max_fib_rad^2,
lower_bound = 0.8*cond_ic*pi*min_fib_rad^2,
relation=SQUARE,
round=FALSE),
peak_fiber_force = list(shape = 8, min = 0.033, max = 0.1, lower_bound = 0.025,
relation=SQUARE, round=FALSE))
## Nonlinear force gain factor parameters
rectus_part$twitch_r <- 0.85
rectus_part$twitch_c <- 2.5
## Define the way in which the motor unit (MU) regions are determined from the
## muscle endplate region.
rectus_part$MU_distributor <-
function(MUs) distribute_MUs_unif(MUs = MUs,
muscle = rectus_part,
tiling = c(3, 2))
rectus_part
}
## For ref, refer to Rankin, Stokes, Newham / Abdominal Muscle Size and Symmetry in normal Subjects, 2006, Muscle & Nerve
## Right RA thickness 1.25, cross/sectional area 8.27
## Left RA thickness 1.24, cross/sectional area 8.15
## both for mean male subjects
## Teyhen, Chils et al. 2012 report mean over both left and right /male again/ to be 1.41, 8.00 which is in good agreement.
## Delp et al. 2001 report cumulative recti lengths of mean 34.3cm.
left_thickness = 1.24 * cm_
right_thickness = 1.25 * cm_
left_width = 8.15 / 1.24 * cm_
right_width = 8.27 / 1.25 * cm_
lower_length = 10 * cm_
mid_length = 12 * cm_
upper_length = 10 * cm_
rectus_la <- generate_rectus_part(width = left_width, thickness = left_thickness, length = lower_length, base_pos = c(-left_width - 1 * mm_, 0), emg_force_rel = emg_force_rel)
rectus_lb <- generate_rectus_part(width = left_width, thickness = left_thickness, length = mid_length, base_pos = c(-left_width - 1 * mm_, lower_length + 1 * cm_), emg_force_rel = emg_force_rel)
rectus_lc <- generate_rectus_part(width = left_width, thickness = left_thickness, length = upper_length, base_pos = c(-left_width - 1 * mm_, lower_length + mid_length + 2 * cm_), emg_force_rel = emg_force_rel)
rectus_ra <- generate_rectus_part(width = right_width, thickness = right_thickness, length = lower_length, base_pos = c(1 * mm_, 0), emg_force_rel = emg_force_rel)
rectus_rb <- generate_rectus_part(width = right_width, thickness = right_thickness, length = mid_length, base_pos = c(1 * mm_, lower_length + 1 * cm_), emg_force_rel = emg_force_rel)
rectus_rc <- generate_rectus_part(width = right_width, thickness = right_thickness, length = upper_length, base_pos = c(1 * mm_, lower_length + mid_length + 2 * cm_), emg_force_rel = emg_force_rel)
recti <- list(rectus_la, rectus_lb, rectus_lc, rectus_ra, rectus_rb, rectus_rc)
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