A Biosystems Approach to Industrial Patient Monitoring and Diagnostic Devices

Preface
1. Medical Devices
1.1 Medical Device Industry
1.2 Medical Instrumentation
1.3 Patient Monitoring Devices
1.3.1 Nellcor Disposable Model
1.4 Diagnostic Devices
1.5 Conclusion
References
2. System Theory
2.1 System Theory for Physiologic Signals
2.2 Filters
2.2.1 Frequency Selective Filters
2.2.2 Pseudorandom Binary Sequence
2.2.2.1 PRBS Properties
2.2.2.2 Filter Construction
2.2.2.3 PRBS Example
2.2.3 Adaptive Filters
2.2.3.1 Adaptive Filter Properties
2.2.3.2 Filter Construction
2.2.3.3 Adaptive Filter Example
2.2.4 Wavelet Transforms
2.2.4.1 Wavelet Transform Properties
2.2.4.2 Filter Construction
2.2.4.3 Wavelet Transform Example
2.3 Modeling
2.3.1 The ARMAX Model
2.3.1.1 Model Identifiability
2.3.1.2 Parameter Estimation
2.3.1.3 Model Validation
2.3.1.4 ARMAX Model Example
2.3.2 Artificial Neural Networks
2.3.2.1 Parameter Estimation
2.3.2.2 Model Validation
2.3.2.3 Artificial Neural Network Example
2.3.3 Fuzzy Models and Control
2.3.3.1 Parameter Estimation
2.3.3.2 Model Validation
2.3.3.3 Fuzzy Control Example
References
3. Patient Monitoring Devices
3.1 Masimo Pulse Oximetry
3.1.1 Pulse Oximetry Calculations
3.1.2 Adaptive Filtering in Masimo Software
3.1.3 Clinical Results
3.1.4 Conclusion
3.2 Interflo Medical Continuous Thermodilution
3.2.1 Thermodilution Calculations
3.2.2 PRBS in Interflo Medical Software
3.2.3 Clinical Results
3.2.4 Conclusion
3.3 CardioDynamics Impedance Cardiography
3.3.1 Impedance Cardiography Calculations
3.3.2 Wavelet Transforms in CardioDynamics Software
3.3.3 Clinical Results
3.3.4 Conclusion
3.4 Aspect Medical Depth of Anesthesia Monitoring
3.4.1 Depth of Anesthesia Monitoring
3.4.2 System Identification in Aspect Medical Software
3.4.3 Clinical Results
3.4.4 Conclusion
References
4. Diagnostic Devices
4.1 Neopath Cervical Cancer Screening
4.1.1 Pap Smear Screening
4.1.2 Fuzzy Models in Neopath Software
4.1.3 Clinical Results
4.1.4 Conclusion
References
Conclusion
Author Biography