|| Master Thesis Seminar at the Signals & Systems Group
Speaker: Gunnar Karlsson, Pharmacia Diagnostics
- Time and Place:
- Wednesday, November 14th, at 15:00
Room 1116, floor 1 at Magistern, Dag Hammarskjölds
väg 31, Uppsala
A pipetting system used for aspiration of patient sample in the
Pharmacia UniCAP-system is studied. The patient sample might contain
small clots that can clog the pipette or affect the test result. The
samples with clogged pipettes should be aborted and those with aspirated
clots should be marked to enable further evaluation of the clot's
effect on the test result.
- The pressure inside the tubing is measured using a pressure sensor
and the surface drop with a level detector. A damped spring system is
simulated to identify and isolate properties of the pipetting system.
Different approaches are made on the classification problem of signals
from the pipetting system, the three studied in depth are:
- A Neural Network with neurons in layers is trained to perform the
- With help from the spring model a simpler solution is made. A spring,
which is extended, has an internal pressure, the same for the pipetting
system when the pipette is clogged. This means the pressure inside the
tubing is lower after aspiration than it was before. The volume of the
aspirated sample is roughly proportional to this pressure difference.
- Most samples have approximately the same appearance. When the samples
with clots are aspirated the pressure dips as the clot hits the pipette
tip and then returns to normal when the clot enters the bigger cavity
in the pipette. The root square sum of the difference between the normal
sample and the pressure for these signals is used as a classifier.
- The proposed algorithm is based on 700 measurements from patient samples
with ~50 clogs and ~100 clotted samples. Around 500 other measurements
were made with other fluids.