Online identification and nonlinear control of the electrically stimulated quadriceps muscle

A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under nonisometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is explicitly designed whereas the model was identified a priori using the developed identification procedure

Continuous state control of blood glucose using discrete-time measurements

In this thesis model-based control algorithms for blood glucose regulation in intensive care units, as well as during hyperinsulinaemic clamps, are designed using a nonlinear model of the glucose-insulin dynamics. The performance of the utilised model is evaluated, and several model parameters are identified offline using data sets obtained during clinical tests at the university hospital Magdeburg. In order to provide real-time applications, a nonlinear state observer for online estimation of the model states and two metabolic parameters is introduced. Subsequently, insulin and glucose output tracking controllers including the inverse nonlinear model are implemented. While the control variable of the insulin controller is insulin, the glucose controller administers glucose. Since the glucose-insulin dynamics are never known exactly, an accurate compensation of the true plant’s nonlinearity is not feasible using these controllers. Therefore, tracking controllers with two degrees of freedom, consisting of nonlinear input/output linearising feedforward control and stabilising linear state feedback control, are implemented. Simulation results using both the control structures referred to above are shown and the controller performances are discussed. Finally, the idea of hybrid blood glucose control, in particular necessary to accomplish a restriction of the control variables, is outlined

Blood glucose control in critical ill patients

Nonlinear hybrid control of blood glucose in critical ill patients has been investigated. Standard control algorithms for blood glucose only adjust the insulin infusion rate for lowering the blood sugar level. Hypoglycaemic situations are critical is this case since no automatic control action can be lunched. To avoid hypoglycaemia, controller performance is usually chosen low what results in large settling times. In the proposed hybrid control scheme, glucose and insulin infusions are administrated. This allows to track a specied blood glucose pro le exactly. The employed controller is model-based and tested in computer simulations

Online Identification of the Electrically Stimulated Quadriceps Muscle Group

In this paper, a new approach for estimating a nonlinear model of the electrically stimulated quadriceps muscle group under non-isometric conditions is investigated. In order to identify the muscle dynamics (stimulation pulse with-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described bya Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank quadriceps dynamics simultaneously

Circadian sleep–wake rhythm disturbances in end-stage renal disease

End-stage renal disease (ESRD) is an increasing health problem worldwide. Given the increasing prevalence of this disease, the high cost of hemodialysis treatment and the burden of hemodialysis on a patient's life, more research on improving the clinical outcomes and the quality of life of hemodialysis-treated patients is warranted. Sleep disturbances are much more prevalent in the dialysis population than in the general population. Several studies investigating the effect and importance of sleep problems on quality of life in dialysis patients revealed that sleep disturbances have a major influence on the vitality and general health of these patients. Sleep disturbances in this patient group are caused both by the pathology of the renal disease and by the dialysis treatment itself. This Review focuses on circadian sleep-wake rhythm disturbances in individuals with ESRD. The possible external and internal influences on sleep-wake rhythmicity in patients with ESRD, such as the effect of dialysis, medications, melatonin and biochemical parameters, are presented. In addition, possible approaches for strengthening the synchronization of the circadian sleep-wake rhythm, such as nocturnal hemodialysis, exogenous melatonin, dialyzate temperature, exogenous erythropoietin, use of bright light and exercise during dialysis treatment, are explored. Further research in this area is warranted, and a greater awareness of sleep problems is needed to improve the quality of life of patients with ESRD