Page 402 - Control Theory in Biomedical Engineering

Index 369

Continuous glucose monitoring (CGM) CVDs. See Cardiovascular diseases (CVDs)
sensor, 63–64 Cytokines, 84np
Continuous subcutaneous insulin infusion with adoptive cellular immunotherapy,
(CSII), 63 84–85
Continuous-time vs. discrete-rime models, IL-2 and interferon-alpha (INF-α),
9–10 84–85
Continuum metastructural test Cytotoxic T lymphocyte (CTL), 30
chiral structure tests, 336, 338f
double arrow honeycomb structure tests, D
336, 337f Data-driven modeling (DDM), 7–9,
mechanical test specifications, 332–333, 10f,64
332f da Vinci surgical system, 156–157,
missing rib structure tests, 333–335, 335f 156–158f, 166, 171–173, 173f
re-entrant honeycomb structure tests, DDM. See Data-driven modeling
333, 334f (DDM)
star structure tests, 336, 339f Decision support system (DSS), 105–107
Continuum robots, 161 Delay differential equations (DDEs),
Control approaches, exoskeletons, 85–87
253–256 Hamiltonian, 97–98
active-assisted and active modes therapy, Matlab program for optimal control,
253–254 98–102
adaptive visual or image-based tracking numerical simulations, 98
control, 255–256 optimal control problem, 96–98
approximation-based control strategies, Pontryagin’s maximum principle, 97–98
255 time-delays, 96–97
backstepping technique, 255 Dendritic cells, 30
decentralized adaptive control, 255 Deterministic vs. stochastic models, 9–10
Lyapunov theory, 254–255 Detrended fluctuation analysis (DFA), 268,
passive physical therapy, 253–254 278, 281–282
sensors and actuators, 253 stride length, 278, 279f
stability of system, 254–255 stride position, 280, 280f
time delay estimation, 254–255 stride time, 278, 279f
of uncertain nonlinear dynamics, 254 stride velocity, 278, 280f
Control therapy Direct control, electromyography, 215
adaptive control, 30–31 Direct nasopharyngoscopy, 287–288
fuzzy logic control, 31 Direct-neural stimulation, 221–222
optimal control, 30 Double arrowhead structure
Corpus luteum, 27–28 auxetic behavior of, 331–332, 331f
CR. See Chylomicron remnants (CR) computer aided design of, 331f
CTAN, 235np Dynamical models, Kalman filter, 132
CTL. See Cytotoxic T lymphocyte (CTL)
Cursive writing, electromyography E
experimental approach, 135–138, 136t, Effectors, 24, 25f,25t
138t, 139f Electrocardiogram (ECG), 105–107
Murata-Kosaku-Sano model, 139–140, feature extraction, 111–114, 112–113f
140f signal filtering, 110, 111f
robust handwriting characterization, Electro/magneto-rheological (ER/MR)
140–145, 142–144f fluids, 318–319, 319f