Abstract
Original language | English |
---|---|
Pages (from-to) | 83-96 |
Number of pages | 14 |
Journal | Systems Science |
Volume | 26 |
Issue number | 3 |
Publication status | Published - 2000 |
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Keywords
- Acceleration measurement
- Diagnosis
- Diseases
- Medical applications
- Position measurement
- Sensors
- Velocity measurement
- Electrostatic actuation
- Open loop design
- Smart accelerometers
- Telecare medicine
- Closed loop design
- Accelerometers
Cite this
Neural network based smart accelerometers for use in telecare medicine. / Gaura, E.I.; Rider, R.J.; Steele, N.; Naguib, R.N.G.
In: Systems Science, Vol. 26, No. 3, 2000, p. 83-96.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Neural network based smart accelerometers for use in telecare medicine
AU - Gaura, E.I.
AU - Rider, R.J.
AU - Steele, N.
AU - Naguib, R.N.G.
PY - 2000
Y1 - 2000
N2 - 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 signal, accelerometers can additionally provide a measure of velocity and position. Applications for such measurements and thus of accelerometers, range from early diagnosis procedures for tremor-related diseases (e.g. Parkinsons) 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 pick-off. The first is an open-loop design utilising a direct inverse control strategy, whilst 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-test and provide digital outputs.
AB - 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 signal, accelerometers can additionally provide a measure of velocity and position. Applications for such measurements and thus of accelerometers, range from early diagnosis procedures for tremor-related diseases (e.g. Parkinsons) 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 pick-off. The first is an open-loop design utilising a direct inverse control strategy, whilst 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-test and provide digital outputs.
KW - Acceleration measurement
KW - Diagnosis
KW - Diseases
KW - Medical applications
KW - Position measurement
KW - Sensors
KW - Velocity measurement
KW - Electrostatic actuation
KW - Open loop design
KW - Smart accelerometers
KW - Telecare medicine
KW - Closed loop design
KW - Accelerometers
M3 - Article
VL - 26
SP - 83
EP - 96
JO - Systems Science
JF - Systems Science
SN - 0137-1223
IS - 3
ER -