Dear Readers

It seems most people agree there is something to the electromechanical

delay (EMD). The concept itself betrays its engineering origin where it

used to mean the delay of electromagnetic/mechanic switches (relays).

[Has anyone tracked the history of EMD in biomechanics?] Thinking of the

muscle as an actuator controlled via motor neurons easily provokes the

analogy with the relays. No one doubts there is sort of a turn-on-time

and a turn-off-time for the muscle. The questions are whether they can

be measured and defined in robust ways, and whether they are of any

physiological interest. For instance, i hit upon the paper

Corcos et al., Electromechanical delay: An experimental artifact (J

Electrmyogr Kinesiol, 2, 2, 1992, 59-68)

where is stated that "published values of electromechanical delay are

all so severely influenced by unknown factors of the apparatus on which

they are made that the published record is void of physiological

significance" (67). Their conclusion about the irrelevance of EMD may

apply if one uses their methodology for "measuring" it. Indeed, they

define EMD as the time from onset of DETECTABLE changes in EMG to the

onset of DETECTABLE changes in force, and what is "detectable" naturally

depends on the resolution etc; i.e., becomes device dependent. If one

adapts the threshold level (they call it T) close to the noise level,

instead of say some fraction of MVC or standard deviation of EMG and

force, the results will most likely vary with the resolution, as they

demonstrate experimentally.

Corcos et alii thus raise a valid point about the importance of how one

tries to extract parameters from data, and to what extent we obtain

intrinsic values, or values that mostly reflects properties of the

measuring device. Adopting the threshold idea for determining EMD the

authors obtain, for a simple dash-pot model, the approximative expression

t_f = sqrt {2*(T/R)* B* (1 + K_d/K_s)}

for the time t_f "to generate detectable changes in force". T is the

detection threshold; R is the rate of force development of the muscle

(one assumes that Force(t) of the contractile element grows with time t

as R*t; i.e., a linear ramp); B is the viscosity parameter of the muscle

(corresponding to the velocity term in the Hill-model); K_s is the

spring constant of the muscle SEC; K_d is the spring constant of the

measuring device (e.g. a hand grip). This expression presupposes an over

damped muscle (viscosity term dominates); indeed, the over-damped case

leads to an equation of the form dx/dt = a*t from which one obtains the

above expression setting x(0) = 0 and x(t_f) = T.

Incidentally, a recent paper

Isabelle et al., Electromechanical assessment of ankle stability (Eur J

Appl Physiol 88, 2003, 558-564)

demonstrates a method for measuring EMD of the peroneal muscles (PL)

using supramaximal electrical stimulation while the participant was

standing on a force plate. The EMD was defined as the time from onset of

PL EMG activity to the onset of the lateral ground reaction force (GRF).

For healthy people (no functional ankle instability, FAI) they obtained

10.5 ± 0.7 ms for bipedal stance, and 8.7 ± 0.6 ms for monopedal stance.

These numbers could makes sense, but we are not informed how exactly the

onsets are determined, leaving it open to the criticism of Corcos et

alii. The lower EMD value for monopedal stance is interpreted as a

consequence of "higher SEC stiffness" which would be in line with the

expression for t_f (which decreases with increasing K_d).´The effect of

mechanical coupling could have been tested making also measurement with

compliant foam between the feet and the force plate. Isabelle et alii

note the variations in the EMD values obtained by various groups but

they seem unaware of the points raised by Cocos et alii.

One would certainly expect EMG-to-force models to address the EMD-issue

as well. One example is

Lloyd & Besier, An EMG-driven musculoskeletal model to estimate muscle

forces and knee

joint moment in vivo (J Biom 36, 2003, 765-776).

They too go back to the "critically damped linear second-order

differential system" which they render as a discrete IIR-filter. This

filter involves a delay d which they set to 40 ms and refer to as EMD

and which they employ because it "improves the synchronization between

activation and the force production". Referring to the paper by Cocos et

alii they think d should be reduced to 10 ms in future models "by

modelling the delay of force production within the musculotendon unit".

So the quantity seems model-dependent, but this is not a problem but a

basic condition of the physical sciences in general. While the use of

black box models (such as based on neural networks etc) and system

identification methods may have important uses they turn a blind eye on

the physiological interpretations of the parameters.

Finally, the cross-correlation analysis of EMG-force has been up, and it

does proved a measure of phase shift between EMG and force, but its

relation to turn-on and turn-off times is probably quite convoluted,

necessitating a physical (tailored) model to make a headway on that (a

problem i am interested in).

Regards Frank Borg

###########################################

This message has been scanned by F-Secure Anti-Virus for Microsoft

Exchange.

For more information, connect to http://www.F-Secure.com/

It seems most people agree there is something to the electromechanical

delay (EMD). The concept itself betrays its engineering origin where it

used to mean the delay of electromagnetic/mechanic switches (relays).

[Has anyone tracked the history of EMD in biomechanics?] Thinking of the

muscle as an actuator controlled via motor neurons easily provokes the

analogy with the relays. No one doubts there is sort of a turn-on-time

and a turn-off-time for the muscle. The questions are whether they can

be measured and defined in robust ways, and whether they are of any

physiological interest. For instance, i hit upon the paper

Corcos et al., Electromechanical delay: An experimental artifact (J

Electrmyogr Kinesiol, 2, 2, 1992, 59-68)

where is stated that "published values of electromechanical delay are

all so severely influenced by unknown factors of the apparatus on which

they are made that the published record is void of physiological

significance" (67). Their conclusion about the irrelevance of EMD may

apply if one uses their methodology for "measuring" it. Indeed, they

define EMD as the time from onset of DETECTABLE changes in EMG to the

onset of DETECTABLE changes in force, and what is "detectable" naturally

depends on the resolution etc; i.e., becomes device dependent. If one

adapts the threshold level (they call it T) close to the noise level,

instead of say some fraction of MVC or standard deviation of EMG and

force, the results will most likely vary with the resolution, as they

demonstrate experimentally.

Corcos et alii thus raise a valid point about the importance of how one

tries to extract parameters from data, and to what extent we obtain

intrinsic values, or values that mostly reflects properties of the

measuring device. Adopting the threshold idea for determining EMD the

authors obtain, for a simple dash-pot model, the approximative expression

t_f = sqrt {2*(T/R)* B* (1 + K_d/K_s)}

for the time t_f "to generate detectable changes in force". T is the

detection threshold; R is the rate of force development of the muscle

(one assumes that Force(t) of the contractile element grows with time t

as R*t; i.e., a linear ramp); B is the viscosity parameter of the muscle

(corresponding to the velocity term in the Hill-model); K_s is the

spring constant of the muscle SEC; K_d is the spring constant of the

measuring device (e.g. a hand grip). This expression presupposes an over

damped muscle (viscosity term dominates); indeed, the over-damped case

leads to an equation of the form dx/dt = a*t from which one obtains the

above expression setting x(0) = 0 and x(t_f) = T.

Incidentally, a recent paper

Isabelle et al., Electromechanical assessment of ankle stability (Eur J

Appl Physiol 88, 2003, 558-564)

demonstrates a method for measuring EMD of the peroneal muscles (PL)

using supramaximal electrical stimulation while the participant was

standing on a force plate. The EMD was defined as the time from onset of

PL EMG activity to the onset of the lateral ground reaction force (GRF).

For healthy people (no functional ankle instability, FAI) they obtained

10.5 ± 0.7 ms for bipedal stance, and 8.7 ± 0.6 ms for monopedal stance.

These numbers could makes sense, but we are not informed how exactly the

onsets are determined, leaving it open to the criticism of Corcos et

alii. The lower EMD value for monopedal stance is interpreted as a

consequence of "higher SEC stiffness" which would be in line with the

expression for t_f (which decreases with increasing K_d).´The effect of

mechanical coupling could have been tested making also measurement with

compliant foam between the feet and the force plate. Isabelle et alii

note the variations in the EMD values obtained by various groups but

they seem unaware of the points raised by Cocos et alii.

One would certainly expect EMG-to-force models to address the EMD-issue

as well. One example is

Lloyd & Besier, An EMG-driven musculoskeletal model to estimate muscle

forces and knee

joint moment in vivo (J Biom 36, 2003, 765-776).

They too go back to the "critically damped linear second-order

differential system" which they render as a discrete IIR-filter. This

filter involves a delay d which they set to 40 ms and refer to as EMD

and which they employ because it "improves the synchronization between

activation and the force production". Referring to the paper by Cocos et

alii they think d should be reduced to 10 ms in future models "by

modelling the delay of force production within the musculotendon unit".

So the quantity seems model-dependent, but this is not a problem but a

basic condition of the physical sciences in general. While the use of

black box models (such as based on neural networks etc) and system

identification methods may have important uses they turn a blind eye on

the physiological interpretations of the parameters.

Finally, the cross-correlation analysis of EMG-force has been up, and it

does proved a measure of phase shift between EMG and force, but its

relation to turn-on and turn-off times is probably quite convoluted,

necessitating a physical (tailored) model to make a headway on that (a

problem i am interested in).

Regards Frank Borg

###########################################

This message has been scanned by F-Secure Anti-Virus for Microsoft

Exchange.

For more information, connect to http://www.F-Secure.com/