Smart sensing systems
that integrate the latest signal processing techniques with IT tools to
automatically interpret time series data and output information in a form suited
to clinical use need to support the busy practice of medicine. Increased
throughput of patients will widen access to the processes of screening,
diagnostics and therapy. In all cases, a smart sensing system needs to
discriminate the possible series of conditions related to the application range.
Sensors should be mechanically simple and robust to suit the arduous medical
working environment while also being cost-effective through enabling staff to
work efficiently.
At
one level smart sensing instruments are needed to
provide information output to assist in diagnosis and monitoring in critical
care rather than outputting data which requires time consuming processing by
clinical staff. A system may track the state of a patient and alert changes in
state, or critical stages, and may form part of a bed chair or instrument used
to help the patient or clinician.
At
the opposite level of operation in healthcare, smart sensing systems can empower
patients to monitor themselves. In these applications the devices would need to
be intuitive to use and indeed the patient may not be informed on its operation
as it may be integrated into a device used in daily living, such as a walking
aid or mat.
Already monitoring
devices to measure temperature or CDV metrics are commercially available.
However, these produce values that on their own do not provide information on
well being, progression on a pathology, or discriminate pathologies. Smart
sensing systems could also provide elementary advice or improvements in
technique or ritual in daily living. Information is not only an important form
of output to be directly useful in clinical work or to advise patients remotely,
it has the potential toprovide for efficient storage
of types of event or condition and can be transmitted more efficiently than
data. This is compatible with devices for remote use and links to health
information systems on the internet.
The research
presented here describes two examples:
Main University navigation links
