Biomedical Engineering Reference
In-Depth Information
Figure 12.3
The proposed suture/ligature training system is composed by a personal
computer, a dummy skin with embedded sensors and a webcam (Solis
et al.,
2008). For
color reference, see page 220.
the applied forces while performing the task). In addition, the web camera is used
to capture a digital image of the suture just after the task is completed.
The reason why we have considered two different measurements methods
is based on the principle that in order to provide objective assessments, we
may require considering the following evaluation parameter categories which are
integrated within an evaluation function (Solis, 2004):
•
Ta s k E f fi c i e n c y
: it refers to such parameters that measures the time trainees spend
to complete the task.
•
Ta s k Sa f e t y
: it refers to such task parameters that measures the applied forces
exerted by trainees while doing the task.
•
Task Quality
: it refers to such parameters that measure how well trainees per-
formed the task after concluding it.
In order to evaluate the suture/ligature task, we have proposed the following
evaluation indexes which are mostly considered from OSCE examination's check-
list. The below proposed evaluation indexes have been measured based on two
sensing methods: dummy skin motion tracking and suture image processing.
•
Time (I
T
)
: Conventionally, the time is measured from the starting up to the
completion of the task.
•
ForceinTissue(I
FoT
)
: If during the insertion of the needled, the trainee applies
shear forces, the skin will be damaged.
•
Judging Tension (I
JuT
)
: This evaluation parameter is related to the ligature
phase. If ligature is done too tightly, it may be painful for the patient and may
also provoke an infection.
•
Equidistance (I
EqD
)
: The suture width is measured between the needle insertion
point and the wound edge.
