Project Objectives

Increasingly the analysis of a patient‘s physiological state is required long term, during
day to day activities in order to precise a diagnosis or to evaluate the efficacy of an
on-going treatment. Wearable sensors can significantly benefit mankind however
today’s solutions invade the user‘s normal life. The sensors require removal,
replacement and reconfigurement for battery recharging and are often too large,
unfriendly and difficult to use.
Zero power medical devices will revolutionise sensor usage, where new software and
hardware architectures will lead to more compact lower power demands. Energy will be
harvested from natural sources (body heat, body motion, solar) such that recharging is
no longer a prime necessity. As a result users will experience a plug and play near
transparent “forever on” usage pattern and forget the fact they are wearing these
sensors thereby enabling very long data capture periods not feasible today.
The WIZPA project will support this zero power technology paradigm and apply them in
realistic, demanding and extremely relevant use cases: the early prediction of
Alzheimer’s Disease (AD) in the elderly and the diagnosis of epilepsy (EP) in young
children.
The research follows a layered approach starting with the design, development and
fabrication of the natural energy harvesting sources. Having integrated these into the
wearable sensors the energy will undergo optimised energy conversion and storage.
The sensors will leverage very low power microprocessor and sensing circuitry
optimised for bio-signals and fabricated to fit into highly ergonomic devices. A new
approach to energy aware software design and multi sensor integration will ensure
sensors operate at maximum quality of service for a given energy profile.
The sensors will include a 24 channel EEG, a three channel ECG and a novel patient
environment monitor. They will interoperate on a body area network performing a
multi-parametric analysis and fusion resulting in a more complex medical analysis
than using three sensors separately. Using state of the art algorithms, the system will
allow health care workers to more effectively diagnose AD and EP. The sensors will be
tested with real patients and will be evaluated to determine their clinical and user
satisfaction.
Since care at home is the primary medical motivation the industrial partners will
ensure a generic approach to health care at home, captured in a flexible friendly Home
software application, as well as a user centred design approach putting the user‘s
needs at the centre of the sensors‘ ergonomic design.

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