The sensor validation or SEVA project (Henry and Clarke 1991; Henry an
d Clarke 1993) promotes the use of intelligence in 'smart' sensors and
the use of standard metrics to efficiently communicate self-diagnosti
cs to the outside world. The standard metrics describe the status of t
he sensor including on-line uncertainty and a status flag to describe
how the current validated measurement value has been derived. The end
result is to provide a compact generic description of the quality of a
measurement to the controller, with which decisions as to how to use
the measurement can be made. This paper proposes the use of SEVA princ
iples in the interpretation of data from biomedical instrumentation, i
n order to aid the decision-making process, particularly in critical c
are. For these purposes the pulse oximeter and polarographic oxygen te
nsion meter will be used as working examples of typical 'intelligent s
ensors' because they make use of a microprocessor to perform self-diag
nostics, as well as implementing measurement algorithms. Copyright (C)
1997 Elsevier Science Ltd.