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Figure 4.10 Pulse oximeter oxygen saturation
ࡿࡻ
FONG et al 2011 The accuracy of the measurement can also be affected as the
amount of arterial blood flow is affected by the sequence of heart beat. Therefore, it is a must to measure for a sufficient period of
time that covers two successive heart beats to get the average value. In the case of an accident, the measurement of oxygen sat-
uration is a crucial step to detect hypoxia in order to facilitate emergency treatment when the victim arrives at the hospital.
Hereby, problems such as tricuspid regurgitation, hypovolaemia and vasoconstriction affecting the blood flow may influence the
measurement given by an oximeter. An oximeter is also unable to differentiate carboxy hemoglobin from normal hemoglobin in the
case of carbon monoxide poisoning and it will also cause the reading to be of higher value than the actual value.
4.2 Processing and Bio-signal Transmission
Telemedicine functions to offer remote medical services where- by data must be transferred from the one site to another. For in-
stance, the data from an accident scene must be transferred to the hospital. There are various types of information. Further-
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more, the raw data that is received has to be processed before being used for analysis and storage. Some are self-explanatory
but variables such as oxygen saturation require expert analysis before factors of the abnormalities can be established. To col-
lect and process any type of data about a patient, a specific type of mechanism like Figure 4.11 is needed. The mechanism is ex-
tended from the basic communication system as shown in Fig- ure 2.1 with the additive noise as seen in Figure 2.2.
Lets take a look of the block diagram that shows a biosensor capturing data such as those discussed in section 4.1. The sensor
networking system that is linked to a transmitter via analogue- to-digital converter will transmit the acquired data to a remote.
To ensure transmission security and efficiency, analogue data is converted into digital domain. This section will discuss trans-
mission efficiency whereas information security will be dis- cussed in Chapter 6. At the receiving end, the data that is
acquired will then be analyzed and stored for analysis. This is a common information system that relates to basic information
theory. For further discussion, it is necessary to refer to the work by Shannon 1948a, Shannon 2001b which quantifies
information in entropy, a term that relates to a particular ex- pected data value in association with a data set.
Figure 4.11 collecting a patient’s information
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The Shannon entropy theory is used to measure the highest ca- pacity of data transferable between communicative networks by
using statistic modeling to describe the size of the network af- fected by unwanted noises during transmittance. However, the
mathematical concept will not be further evaluated and readers who want to determine the concept should look it up from the
references Cover, 2006a, Cover 2012b. The theory appears to be much simpler by excluding the mathematical concept. By
using Figure 2.1 as a reference, we will look briefly into the fundamental communicative network equipped with a discrete
source S. It has a measurable output values and uses R bits rate to calculate data. The discrete source has the entropy of:
H S ≤ R
According to the theory, the discrete source can be ciphered to another equivalent at the rate of HS bits, and the recipient can
recover the initial code. This theory is applicable with the con- dition that the speed of transmittance is more than HS. Hence,
the bits rate is used as a measurement of the original data in the throughput of S. The Channel Coding will also be given a brief
study by including the data transmittance bits b
א {0, 1} across a network which includes q, a possibility of one failed bit from
one million bits transmitted and C = Cq, where C refers to the capacity. A network cipher includes k data block which is
mapped into n where n is more than k ciphered bits and intro- duces surplus. Data content of a deciphered bit r is referred as:
R = k n
An estimated ˆb of the actual data bits is produced by recipient prior to the transmission of deciphered chain c, with a failure
possibility of:
4.2
4.3
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Hence, the value of p can be brought to the lowest at r C. It is obvious that C is an estimation of network strength and the lev-
el of noise. By understanding the fundamental theory of net- work strength, the next subject of transmission and the process
of medical data will be explored.
4.2.1 Imaging Medical
The science of diagnosis image is commonly applied in x-rays, physical scans and the study of bodily structure, distant opera-
tions as well as in recovering accidents. The simplified proce- dure of diagnosis imaging is depicted in Figure 4.12.It shows
that the common procedure involves the capture, transfer, anal- ysis and the storing of images. For usual diagnosis, image is
copied and kept in archives.
Figure 4.12 Process of Imaging Medical FONG et al 2011
4.4
