| 1. |
- Abdalmoaty, Mohamed, 1986-, et al.
(författare)
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Noise reduction in Laguerre-domain discrete delay estimation
- 2022
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Ingår i: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 6254-6259
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a stochastic framework for a recently proposed discrete-time delay estimation method in Laguerre-domain, i.e. with the delay block input and output signals being represented by the corresponding Laguerre series. A novel Laguerre-domain disturbance model allowing the involved signals to be square-summable sequences is devised. The relation to two commonly used time-domain disturbance models is clarified. Furthermore, by forming the input signal in a certain way, the signal shape of an additive output disturbance can be estimated and utilized for noise reduction. It is demonstrated that a significant improvement in the delay estimation error is achieved when the noise sequence is correlated. The noise reduction approach is applicable to other Laguerre-domain problems than pure delay estimation.
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| 2. |
- Albaba, Adnan, et al.
(författare)
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Online Model-Based Beat-by-beat Heart Rate Estimation
- 2020
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Ingår i: 2020 American Control Conference (ACC). - 9781538682661 - 9781538682678 - 9781538682654 ; , s. 539-544
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Konferensbidrag (refereegranskat)abstract
- A method for estimating the instantaneous heart rate (HR) using the morphological features of one electrocardiogram (ECG) cycle (beat) at a time is proposed. This work is not aimed at introducing an alternative way for HR estimation, but rather illustrates the utility of model-based ECG analysis in online individualized monitoring of the heart function. The HR estimation problem is reduced to fitting one parameter, whose value is related to the nine parameters of a realistic nonlinear model of the ECG and estimated from data by nonlinear least-squares optimization. The method feasibility is evaluated on synthetic ECG signals as well as signals acquired from MIT-BIH databases at Physionet website. Moreover, the performance of the method was tested under realistic free-moving conditions using a wearable ECG and HR monitor with encouraging results.
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| 3. |
- Albaba, Adnan, et al.
(författare)
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Patient-Specific Electrocardiogram Monitoring by Model-Based Stochastic Anomaly Detection
- 2020
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Ingår i: 2020 European Control Conference (ECC). - 9783907144022 - 9781728188133 ; , s. 735-740
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Konferensbidrag (refereegranskat)abstract
- A novel model-based method for patient-specific detection of deformed electrocardiogram (ECG) beats is proposed and tested. Five parameters of a patient-specific nonlinear ECG model are estimated from data by nonlinear least-squares optimization. The normal variability of the model parameters is captured by estimated probability density functions. A binary classifier, based on stochastic anomaly detection methods, along with a pre-tuned classification threshold, is employed for detecting the abnormal ECG beats. We demonstrate the utility of the proposed approach by validating it on annotated arrhythmia data recorded under clinical conditions.
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| 5. |
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| 6. |
- Björk, Marcus, 1985-, et al.
(författare)
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Dynamic models with quantized output for modeling patient response to pharmacotherapy
- 2010
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Ingår i: Proc. International Conference on Control Applications. - Piscataway, NJ : IEEE. - 9781424453627 ; , s. 1029-1034
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Konferensbidrag (refereegranskat)abstract
- This article presents a way of modeling patient response to a pharmacotherapy by means of dynamic models with quantized output. The proposed modeling technique is exemplified by treatment of Parkinson's disease with Duodopa ®, where the drug is continuously administered via duodenal infusion. Titration of Duodopa ® is currently performed manually by a nurse judging the patient's motor symptoms on a quantized scale and adjusting the drug flow provided by a portable computer-controlled infusion pump. The optimal drug flow value is subject to significant inter-individual variation and the titration process might take up to two weeks for some patients. In order to expedite the titration procedure via automation, as well as to find optimal dosing strategies, a mathematical model of this system is sought. The proposed model is of Wiener type with a linear dynamic block, cascaded with a static nonlinearity in the form of a non-uniform quantizer where the quantizer levels are to be identified. An identification procedure based on the prediction error method and the Gauss-Newton algorithm is suggested. The datasets available from titration sessions are scarce so that finding a parsimonious model is essential. A few different model parameterizations and identification algorithms were initially evaluated. The results showed that models with four parameters giving accurate predictions can be identified for some of the available datasets.
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| 8. |
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| 9. |
- Bro, Viktor, et al.
(författare)
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Identification of continuous Volterra models with explicit time delay through series of Laguerre functions
- 2019
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Ingår i: Proc. 58th IEEE Conference on Decision and Control. - : IEEE. - 9781728113982 ; , s. 5641-5646
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Konferensbidrag (refereegranskat)abstract
- The problem of estimating nonlinear time-delay dynamics captured by continuous Volterra models from input-output data is treated. The delayed Volterra kernels are seen as impulse responses of linear time-invariant systems with time delay. Analytical expressions for the Laguerre series, where the Laguerre coefficients of the finite-dimensional part are admixed with the terms due to the delay, are provided. By utilizing the linearity of Volterra-Laguerre models in the unknown parameters, the model is estimated by a nonlinear least-squares method. An application of the proposed approach to the problem of Volterra modelling of the human smooth pursuit system from eye-tracking data is provided. The proposed approach demonstrates consistently accurate performance on both simulated and experimental data.
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| 10. |
- Bro, Viktor, et al.
(författare)
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Laguerre-domain Modeling and Identification of Linear Discrete-time Delay Systems
- 2020
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Ingår i: IFAC PapersOnline. - : ELSEVIER. - 2405-8963. ; , s. 939-944
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Konferensbidrag (refereegranskat)abstract
- A closed-form Laguerre-domain representation of discrete linear time-invariant systems with constant input time delay is derived. It is shown to be useful in a I-2 -> I-2 system identification setup (with I-2 denoting square-summables signals) often arising in biomedical applications, where the experimental protocol does not allow for persistent excitation of the system dynamics. The utility of the proposed system representation is demonstrated on a problem of drug kinetics estimation from clinical data.
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