By Topic

Neural-network compensation methods for capacitive micromachined accelerometers for use in telecare medicine

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
E. I. Gaura ; BIOCORE, Coventry Univ., UK ; R. J. Rider ; N. Steele ; R. N. G. Naguib

Transducers represent a key component of medical instrumentation systems. In this paper, sensors that perform the task of measuring the physical quantity of acceleration are discussed. These sensors are of special significance since, by integrating their output signals, accelerometers can additionally provide measures of velocity and position. Applications for such measurements, and thus of accelerometers, range from early diagnosis procedures for tremor-related diseases (e.g. Parkinson's disease) to monitoring daily patterns of patient activity using telemetry systems. The system-level requirements in such applications are considered, and two novel neural-network transducer designs developed by the authors are presented, which aim to satisfy such requirements. Both designs are based on a micromachined sensing element with capacitive signal pickoff. The first is an open-loop design utilizing a direct-inverse control strategy, while the second is a closed-loop design, where electrostatic actuation is used as a form of feedback. Both transducers are nonlinearly compensated, capable of self-testing, and provide digital outputs.

Published in:

IEEE Transactions on Information Technology in Biomedicine  (Volume:5 ,  Issue: 3 )