Prioritization of Patient Vital Signs Transmission Using Wireless Body Area Networks - E-Healthcare Systems and Wireless Communications - page 261

has focused on prioritizing the transmission of
healthcare data over the wireless network in the
electromagnetic interference (EMI) environment
under the constraints of both the patient condition
and the data content, i.e., the type of measurement
(temperature, O 2 saturation, blood pressure and
pulse, heart rate variability, etc.), which is critical
in emergency services.
Different types of healthcare data are of dif-
ferent importance during in-hospital triage, as
shown in Table 1. Here delay is the time from
source sensors to destination medical devices such
as medical terminals, Personal Digital Assistants
(PDAs), and cell phones, i.e., the end-to-end
(e2e) delay. In an in-hospital environment, proper
prioritization of critical vital signs is crucial for
efficient and real-time triage. Obviously, vital signs
from patients in critical situation should be served
first with guaranteed service quality. Patients in
different emergency conditions have different
service requirements: a patient who needs more
immediate service should be given higher priority,
i.e., his/her vital signs should be transmitted with
higher e2e reliability and lower delay.
In order to provide a networking solution that
performs real-time in-hospital triage on multiple
patients under EMI environment, in this chapter
we propose a new interference-aware WBAN
system that continuously monitors vital signs of

multiple patients and prioritizes data transmission
based on patient's condition and data content.
Based on the patient's condition, which in this
chapter we assume to be already diagnosed, pa-
tients are categorized into three classes, “ Red ”,
“ Yellow ”, and “ Green ”, each indicating the level
of treatment needed, i.e., “ immediate ”, “ delayed ”,
and “ minimal ”, respectively. Categorization of
one patient into one of these three classes can be
achieved by using data aggregation algorithms
within one BAN. Moreover, these algorithms
should jointly consider all the vital signs taken
from one patient since using only few vital signs
is generally not sufficient to perform the diagno-
sis of a patient.
For example, injury severity assessment of
neurological status (e.g., level of consciousness
and motor activity) should be made by looking at
both vital signs such as pulse, blood pressure, and
respiratory rate, as well as the movement activi-
ties (normal vs. abnormal). We have proposed a
solution to classify the movements of a patient
using multiple sets of tri-axial accelerometers
(using IMote2 and Shimmer sensors) attached to
different parts of the body in (Varkey & Pompili,
2009), which will be further extended for patient
status classifications.
In this chapter, we focus on the e2e transmis-
sion of vital signs instead of patient status clas-

Table 1. Bit Rate and Delay Requirements of Healthcare Data (IEEE EMBS, 2008)

Data Source Bit Rate [bps] Delay [s] Sampling Rate [Hz]

Electrocardiogr am (ECG) 1 - 8 <10 63 - 500

Blood Pres-
sure [mmHg]

Arterial Line 1k 10 - 30 63

CVP (Central Venous Catheter) 1k >120 63

Non-invasive Cuff 0.05 30-120 0.025

Cardiac Output [L/min] 1k <10 63

Pulse Oximeter SpO 2 Saturation [%] 1k <10 63

Patient ID Band 0.05 >120 0.0002

Inter-cranial Br ain Pressure [mmHg] 16 10 - 30 1

CO 2 Concentration (for respiration monitoring) [ppm] 1k 30 - 120 63

Temperature [ºC ] 0.3 >120 0.02