1. Identifying RFID-
embedded objects in
pervasive healthcare
applications
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2. Reference
 Yu-Ju Tu, Wei Zhou, Selwyn Piramuthu “Identifying
RFID-embedded objects in pervasive healthcare
applications” , Decision Support Systems Volume 46 , Issue 2
(January 2009)
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3. Outline
 Introduction
 RFID tags and healthcare
 Related literature on improving RFID tag identification
accuracy
 Proposed methods
 Discussion
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4. Introduction
 The primary goal of pervasive healthcare is to be able to
deliver necessary quality healthcare service anytime to
anyone regardless of location and other constraints.
 The underlying principle in most of these intelligent
information systems are rather similar to the extent that
they all utilize knowledge in some form to enable
decision making in the healthcare environment.
Clinical Decision Support Systems (CDSS)
Intelligent Decision Support Systems (IDSS)
Healthcare Information Systems (HIS)
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5. Introduction
 RFID tags are used in scenarios
an object needs to be identified
tracked
when ambient condition surrounding an object is captured
stored
 Although it is generally assumed that data read from
RFID tags are highly accurate, variations in accuracy
can and do occur due to several reasons.
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6. RFID tags and healthcare
 One of the largest volumes of RFID application has been in
the healthcare industry, where about 4.5 million tags have
been used every year on Diprivan drug syringes by
AstraZeneca since 1999.
 Asset tracking is a prime candidate for RFID applications
A typical hospital is unable to locate about 15–20% of its assetswhen
needed
 Cost and privacy concerns have generally been recognized
as major factors in the success of RFID applications
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7. RFID tags and healthcare
 Three main areas benefit from RFID technology in the
healthcare industry:
(1) asset management
(2) patient care
(3) inventory management
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8. Related literature on improving RFID tag
identification accuracy
 Bai et al. propose means to filter and clean data streams
from RFID applications that contain false (e.g., false
positive, false negative) readings and duplicates
 To improve RFID tag detection reliability, Agarwal et al.
let the reader sample every 2 s
 Data reliability and ambiguity are two major issues in
extraction of information from RFID data
 Khoussainova et al. use probabilistic method to provide
the application with the flexibility to build its own
balance between detection and precision rate
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9. Proposed methods
 False positives and false negatives can be a problem in
RFID-embedded systems, especially when signal from a
given tag is blocked by an impenetrable object (e.g.,
metal shielding) or when corrupted signal is read
 Algorithm 1 (the base case)
 Algorithm 2
 Algorithm 3
 Algorithm 4
 Results
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10. Algorithm 1 (the base case)
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11. Algorithm 2
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12. Algorithm 3
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13. Algorithm 4
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14. Algorithm 4
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15. Results
 We simulated the four algorithms presented above 10
times with 1000 readings per run with the following
assumptions: The tag T (or, T1 in Algorithm 4) is always
present (or, absent) during both the reads in a reader's
field
 Algorithm 1
 Algorithm 2
 Algorithm 3
 Algorithm sliding window
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16. Results
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17. The p-values for results
(using pairwise t-test)
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18. Average false positive cases using
different probability values for reader R1
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19. Average false negative cases using
different probability values for reader R1
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20. Average overall false cases using different
probability values for reader R1
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21. Average false positive cases using
different probability values for reader R2
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22. Average false negative cases using
different probability values for reader R2
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23. Average overall false cases using different
probability values for reader R2
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24. Discussion
 The algorithms to reduce false positives and false negatives
while identifying the presence/absence of an RFID tag in the
field of a reader, and illustrated these algorithms by means
of an example scenario (Although our results are based on
simplified assumptions)
 Any successful attempt at improving true (positive and
negative) readings would ultimately increase the
performance and efficiency of RFID tag-enabled systems
 This is even more salient given that the methods proposed in
this paper can be implemented with minimal resources and
effort
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