| 1. |
- Abdalmoaty, Mohamed, 1986-, et al.
(författare)
-
Continuous Time-Delay Estimation From Sampled Measurements
- 2023
-
Ingår i: IFAC-PapersOnLine. - : Elsevier. - 2405-8963. ; 56:2, s. 6982-6987
-
Tidskriftsartikel (refereegranskat)abstract
- An algorithm for continuous time-delay estimation from sampled output data and a known input of finite energy is presented. The continuous time-delay modeling allows for the estimation of subsample delays. The proposed estimation algorithm consists of two steps. First, the continuous Laguerre spectrum of the output (delayed) signal is estimated from discretetime (sampled) noisy measurements. Second, an estimate of the delay value is obtained via a Laguerre domain model using a continuous-time description of the input. The second step of the algorithm is shown to be intrinsically biased, the bias sources are established, and the bias itself is modeled. The proposed delay estimation approach is compared in a Monte-Carlo simulation with state-of-the-art methods implemented in time, frequency, and Laguerre domain demonstrating comparable or higher accuracy in the considered scenario.
|
|
| 2. |
- Abdalmoaty, Mohamed, 1986-, et al.
(författare)
-
Noise reduction in Laguerre-domain discrete delay estimation
- 2022
-
Ingår i: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 6254-6259
-
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.
|
|
| 3. |
- Aghanavesi, Somayeh, 1981-, et al.
(författare)
-
A multiple motion sensors index for motor state quantification in Parkinson's disease
- 2020
-
Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 189
-
Tidskriftsartikel (refereegranskat)abstract
- Aim: To construct a Treatment Response Index from Multiple Sensors (TRIMS) for quantification of motor state in patients with Parkinson's disease (PD) during a single levodopa dose. Another aim was to compare TRIMS to sensor indexes derived from individual motor tasks. Method: Nineteen PD patients performed three motor tests including leg agility, pronation-supination movement of hands, and walking in a clinic while wearing inertial measurement unit sensors on their wrists and ankles. They performed the tests repeatedly before and after taking 150% of their individual oral levodopa-carbidopa equivalent morning dose.Three neurologists blinded to treatment status, viewed patients’ videos and rated their motor symptoms, dyskinesia, overall motor state based on selected items of Unified PD Rating Scale (UPDRS) part III, Dyskinesia scale, and Treatment Response Scale (TRS). To build TRIMS, out of initially 178 extracted features from upper- and lower-limbs data, 39 features were selected by stepwise regression method and were used as input to support vector machines to be mapped to mean reference TRS scores using 10-fold cross-validation method. Test-retest reliability, responsiveness to medication, and correlation to TRS as well as other UPDRS items were evaluated for TRIMS. Results: The correlation of TRIMS with TRS was 0.93. TRIMS had good test-retest reliability (ICC = 0.83). Responsiveness of the TRIMS to medication was good compared to TRS indicating its power in capturing the treatment effects. TRIMS was highly correlated to dyskinesia (R = 0.85), bradykinesia (R = 0.84) and gait (R = 0.79) UPDRS items. Correlation of sensor index from the upper-limb to TRS was 0.89. Conclusion: Using the fusion of upper- and lower-limbs sensor data to construct TRIMS provided accurate PD motor states estimation and responsive to treatment. In addition, quantification of upper-limb sensor data during walking test provided strong results. © 2019
|
|
| 4. |
- Albaba, Adnan, et al.
(författare)
-
Online Model-Based Beat-by-beat Heart Rate Estimation
- 2020
-
Ingår i: 2020 American Control Conference (ACC). - 9781538682661 - 9781538682678 - 9781538682654 ; , s. 539-544
-
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.
|
|
| 5. |
- Albaba, Adnan, et al.
(författare)
-
Patient-Specific Electrocardiogram Monitoring by Model-Based Stochastic Anomaly Detection
- 2020
-
Ingår i: 2020 European Control Conference (ECC). - 9783907144022 - 9781728188133 ; , s. 735-740
-
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.
|
|
| 6. |
- Bro, Viktor, 1991-, et al.
(författare)
-
Continuous and discrete Volterra-Laguerre models with delay for modeling of smooth pursuit eye movements
- 2023
-
Ingår i: IEEE Transactions on Biomedical Engineering. - : IEEE. - 0018-9294 .- 1558-2531. ; 70:1, s. 97-104
-
Tidskriftsartikel (refereegranskat)abstract
- The mathematical modeling of the human smooth pursuit system from eye-tracking data is considered. Recently developed algorithms for the estimation of Volterra-Laguerre (VL) models with explicit time delay are applied in continuous and discrete time formulations to experimental data collected from Parkinsonian patients in different medication states and healthy controls. The discrete VL model with an explicit time delay and the method for its estimation are first introduced in this paper. The estimated parameters of a second-order VL model are shown to capture the ocular dynamics both in health and disease. The possibility of including the estimated time delay, along with the VL kernel parameters, into the set of the model parameters is explored. The results obtained in continuous VL modeling are compared with those in discrete time to discern the effects due to the sampling enforced by the eye tracker used for data acquisition.
|
|
| 7. |
- Bro, Viktor, et al.
(författare)
-
Laguerre-domain Modeling and Identification of Linear Discrete-time Delay Systems
- 2020
-
Ingår i: IFAC PapersOnline. - : ELSEVIER. - 2405-8963. ; , s. 939-944
-
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.
|
|
| 8. |
- Bro, Viktor
(författare)
-
Volterra Modeling and Estimation of the Human Smooth Pursuit
- 2022
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis treats the mathematical modeling of the human smooth pursuit system using Volterra-Laguerre models. The smooth pursuit system allows for tracking of moving objects. Since it is a complex system including the muscles of the eye, nerves and certain parts of the brain, the system may be impaired if some part is compromised.Eye tracking involves tracking the point of the gaze. When recorded, such coordinates may be used for mathematical modeling of the system controlling the gaze. Volterra models allow for modeling of smooth nonlinear dynamical systems, such as the smooth pursuit system. The input of the system is the position of the tracked object and the output of the system is the point of the gaze. The problem of overparametriztion in Volterra models may be alleviated by expansion of the kernels in some orthonormal basis. Choosing this basis as the set of Laguerre functions yields a Volterra-Laguerre model.This thesis expands on the development of Volterra-Laguerre models for modeling of smooth pursuit in several ways. An approach for finding a minimal model structure using sparse estimation is studied. This allows for a parsimonious but not necessarily low order model. Furthermore the Volterra-Laguerre model is augmented with a delay parameter. Using this, the delay which would otherwise be expressed in the coefficients of the model, is made explicit. The methods proposed are studied both in simulated examples as well as using real eye tracking data from patients with Parkinson's disease and from healthy control subjects.
|
|
| 9. |
- Marin, Robin, et al.
(författare)
-
Bayesian Monitoring of COVID-19 in Sweden
- 2023
-
Ingår i: Epidemics. - : Elsevier. - 1755-4365 .- 1878-0067. ; 45
-
Tidskriftsartikel (refereegranskat)abstract
- In an effort to provide regional decision support for the public healthcare, we design a data-driven compartment-based model of COVID-19 in Sweden. From national hospital statistics we derive parameter priors, and we develop linear filtering techniques to drive the simulations given data in the form of daily healthcare demands. We additionally propose a posterior marginal estimator which provides for an improved temporal resolution of the reproduction number estimate as well as supports robustness checks via a parametric bootstrap procedure.From our computational approach we obtain a Bayesian model of predictive value which provides important insight into the progression of the disease, including estimates of the effective reproduction number, the infection fatality rate, and the regional-level immunity. We successfully validate our posterior model against several different sources, including outputs from extensive screening programs. Since our required data in comparison is easy and non-sensitive to collect, we argue that our approach is particularly promising as a tool to support monitoring and decisions within public health.Significance: Using public data from Swedish patient registries we develop a national-scale computational model of COVID-19. The parametrized model produces valuable weekly predictions of healthcare demands at the regional level and validates well against several different sources. We also obtain critical epidemiological insights into the disease progression, including, e.g., reproduction number, immunity and disease fatality estimates. The success of the model hinges on our novel use of filtering techniques which allows us to design an accurate data-driven procedure using data exclusively from healthcare demands, i.e., our approach does not rely on public testing and is therefore very cost-effective.
|
|
| 10. |
- Medvedev, Alexander, 1958-
(författare)
-
Closed-form expressions for the pure time delay in terms of the input and output Laguerre spectra
- 2024
-
Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 159
-
Tidskriftsartikel (refereegranskat)abstract
- The pure time delay operator is considered in continuous and discrete time under the assumption of the input signal being integrable (summable) with square. Then the input and the output signals are uniquely given by their Laguerre spectra. It is shown that a discrete convolution operator with polynomial Markov parameters constitutes a common description of the delay operator in the continuous and discrete case. Closed-form expressions for the delay value in terms of the output and input Laguerre spectra are derived. The expressions hold for any feasible value of the Laguerre parameter and can be utilized for e.g. building time-delay estimators that allow for non-persistent input. A simulation example is provided to illustrate the principle of Laguerre-domain time-delay modeling and analysis with perfect disturbance rejection.
|
|
