ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

each movement speed. The speed was synchronized with auditory cues produced by a
digital metronome and with verbal commands and visual cues provided by the
examiner. Each repetition was separated by 10 s of rest and each set of movements was
separated by 2 s intervals. The record of each flexion with the 6 mentioned velocities
lasted 1 min and 6 to 8 movements were performed and stored on PC during this
interval.
The signals were processed by custom-made program written in MATLAB.
EMG signals were filtered (high-pass Butterworth filter, order 2, cut-off frequency
15Hz), rectified and smoothed after true zero-line obtaining. The angle displacement ϕ
was smoothed and numerical differentiated to calculate angle velocity, ϕ& and angle
acceleration,ϕ& & . The external moment in the joint, Mext, was calculated according to the
equation: Mext=I
ϕ& & zz +Glsin(ϕ ), where Izz
and G are the inertial moment and the gravity
force of the hand and forearm and l is the distance from the axis of rotation in the joint
to the application point of G.
4. MUSCLE MODEL AND MOTCO SOFTWARE
The muscle model and the MotCo software (http://www.motco.info/) are described in
detail in [8, 9]. The two muscles are composed by nearly real number of MUs - 774 for
BIC and 686 for TRI. Their twitch properties are continuously distributed and the twitch
amplitudes are from 0.198 N to 1.189N for BIC and from 0.197 N to 1.184 N for TRI.
The fitness function was weighted combination of four criteria: minimal MUs'
activation, minimal sum of muscle forces, minimal deviation from the external joint
moment and minimal antagonist co-contraction. The goal of the algorithm is to find the
optimal impulsation of all MUs that best satisfies the fitness function. Multiple solutions
are evaluated in parallel and are subjects of random genetic operations - mutation and
crossover. The mutation modifies an existing solution by adding, removing or shifting
impulses from the impulsation pattern of randomly chosen MUs. The crossover
combines parts of two different solutions into one. The probability for selection of
solutions for mutation, crossover and survival is proportional to the estimates of the
fitness function. It has to be noted here that the well know size principle for
recruitment/decruitment of the MUs [10, 11] was not used in the current simulations.
5. RESULTS
The experimental data for one subject are presented in the current paper. For each of the
6 flexion speeds, six trials were chosen, and one of these six trials were selected for
simulation with MotCo software. The processed EMGs of m.BIC and m.TRI, the angle
displacement, velocity and acceleration, and the external joint moment are shown in
Fig.1 for one trial for the slowest (Fig.1a), the fastest (Fig.1b) and the maximal fast
(Fig.1c) movement. Small TRI activity can be observed during the flexion performed
with the 4-th velocity (360 deg/s). This activity was essential for the two last speeds (see
Fig.1b and 1c), while for the slow movements the extensor was nearly silent for all time
period (Fig.1a). The maximal amplitude of the filtered, rectified and averaged EMGs of
m.BIC increases from 0.3847 mV (the first speed) to 1.6270 mV (the sixth speed), and
for TRI - from nearly zero to 1.5438 mV. The calculated external joint moment was
positive for the first 4 speeds and its peak increased from 6.12 mN to 7.26 mN. For the
last two fast flexions, the joint moment had three phases - positive, negative and again
positive (see the gray dashed horizontal lines in Fig.1c). The minimal value of Mext was