6.2 Signals of the Muscles and Motions

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Fig. 6.11: Determination of two instants of time for the synchronisation called trigger points; KB:=

knee bend, force (lined), knee angle (dotted).

Design of MATLAB algorithm

Based on manual analysis [11, 73] of the points of synchronisation an algorithm was

developed which automates the first steps of synchronisation [69]. Attention should

be paid on the patient data, because the results achieved, can vary individually. The

selected features should minimise the inaccuracy of the synchronisation based on the

measured data.

As above mentioned there are characteristic patterns in the force and joint angle

data which can be used as features. Prominent features are the times of rest between

the knee bends, which are further referred to as standing phases. In these phases the

patient legs are mostly extended in an upright position. In Figure 6.9 the standing

phases are circled black. The time difference between the standing phases in the force

and joint angle curve is roughly the same thus the centres of the standing phases can

be used as anchors for synchronising force and joint angle data. The centre points of

the standing phases are further referred to as trigger points (TP). Regarding the joint

angles we will discuss furthermore the knee joint angle because the data of the joint

angle of hip, knee and ankle are in already synchronous.

Synchronisation procedure

In the following part a variety of algorithms will be presented regarding the finding

of the relevant characteristic points discussed previously. In MATLAB there are sev-