![](bg4.png)
Table 2: Sepsis treatment policy expressed in ARTEMIS.
(x) ← wbc(x) < 4000 | () > 20000
(x) ← (x) < 96.8 | (x) > 100.4
(x) ← (x) > 20
(x) ← ℎ(x) > 90
(x) ←
(
x
)
∨(x)
(x) ←
(
x
)
∨(x)
ℎℎ(x) ←
◆
[
,
(x) ∧ ◆
[
,
(x)
(x) ←
◆
[
,
m
(
x
)
∧ ◆
[
,
min(x)
ℎ(x) ← ℎℎ(x)
(x) ←
(
x
)
∧¬◆
[,)
(
x
)
∨ℎ
(
x
)
(x) ←
ℎ
(
x
)
∨
(
x
)
∧¬◆
[
,
)
()
(x) ←
(
x
)
(x) ←
◆
[
,
(
x
)
∧
(x)
issueHighAlert and issueLowAlert signalled, when a
high priority or low priority alert had to be sent out
for patient x. For any patient x, when we reached
SIRSalert, we initialized the Verification tester (once
in every 24 hours, because the test takes significant
amount of time; also note that this is not part of the
original protocol, we used it for demonstration
purposes only) for that patient. Relation approval
signalled the results of the verification. If approval
was received, the patient was sent to lab tests by
issuing Sepsis_lab. On the arrival of lab tests,
relation labtests_done was updated. If lab tests were
done within 24 hours after the approval of sepsis
treatment, we could start the sepsis treatment action
signalled by Sepsis_treatment.
Even though the performance of the algorithm
heavily depends on several factors, we simulated
SIRS alert with 100000 distinct events affecting 100
patients leading to 25074 issued SIRS alert to
demonstrate the order of magnitude. The average
performance was 0.21ms / event.
5 CONCLUSIONS
We showed the concept of Active Real-Time Event
Monitoring and Integration System (ARTEMIS)
which is an extension of traditional real-time
monitoring systems with active participation from
the part of the monitor. As a workflow management
system ARTEMIS competes with systems like
Drools, but supports a broader and more expressive
set of temporal expressions which might show
immediate advantages in signal processing
scenarios.
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ACTIVE MONITORING USING REAL-TIME METRIC LINEAR TEMPORAL LOGIC SPECIFICATIONS
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