An Algebraic Method for Eye Blink Artifacts Detection in Single Channel EEG Recordings

This article presents a parameter estimation algorithm for a magnetic bearing. Such process are inherently unstable systems with strongly nonlinear dynamics. Here, a simplified model of the magnetic bearing is developed. This enables to obtain a linear expression with respect to the unknown parameters. These parameters are measurable with difficulties, and may slightly vary over time. The expression of the estimates is written as a function of integrals of the inputs and outputs of the system. The simulations and the experiments show a fast and robust on-line identification.

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“…Equations (15), (16) and (17) allow to obtain the expressions of the estimate of the parametersλ 1 ,λ 2 etλ 3 :…”

Section: A Estimation Of λ K Parametersmentioning

confidence: 99%

On-line parameter estimation of a magnetic bearing

Delpoux

Floquet

2011

2011 19th Mediterranean Conference on Control &Amp; Automation (MED)

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“…This is a similar approach to the numerical differentiation method applied to electroencephalographic (EGG) recordings for detecting eye blinks [12]. The rate of altitude change is computed sample by sample as the difference of altitude divided by the elapsed time.…”

Section: Despeckle Filtermentioning

confidence: 99%

Filtering Enhanced Traffic Management System (ETMS) Altitude Data

Hielscher¹,

Hansman²

2013

Metrology and Measurement Systems

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Enhanced Traffic Management System (ETMS) stores all the information gathered by the Federal Aviation Administration (FAA) from aircraft flying in the US airspace. The data stored from each flight includes the 4D trajectory (latitude, longitude, altitude and timestamp), radar data and flight plan information. Unfortunately, there is a data quality problem in the vertical channel and the altitude component of the trajectories contains some isolated samples in which a wrong value was stored. Overall, the data is generally accurate and it was found that only 0.3% of the altitude values were incorrect, however the impact of these erroneous data in some analyses could be important, motivating the development of a filtering procedure. The approach developed for filtering ETMS altitude data includes some specific algorithms for problems found in this particular dataset, and a novel filter to correct isolated bad samples (named Despeckle filter). As a result, all altitude errors were eliminated in 99.7% of the flights affected by noise, while preserving the original values of the samples without bad data. The algorithm presented in this paper attains better results than standard filters such as the median filter, and it could be applied to any signal affected by noise in the form of spikes.

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“…This method has already been successfully applied to parameter estimation [2], [15], [16], [18], [19], to abrupt change detections and the efficient identification of time delays [1], [5], [21]. Numerical differentiation of noisy signals may also benefit from this approach, as demonstrated in [17], [20].…”

Section: Introductionmentioning

confidence: 99%

Acceleration feedback via an algebraic state estimation method

Delpoux

Sira‐Ramírez

Floquet

2013

52nd IEEE Conference on Decision and Control

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In many mechanical systems, only accelerations are available for feedback purposes. For example, certain aerospace, positioning systems and force-position controllers in robotic systems, use accelerometers as the only sensing device. This paper presents initial steps towards an algebraic approach for the state estimation based feedback control problem in systems where the highest order derivative of the controlled variable is available. An illustrative case is presented dealing with the trajectory tracking problem for a second order position system on which only the acceleration is available for measurement. Based on an algebraic approach, an on-line algebraic estimator is developed for the unmeasured position and velocity variables. The obtained expressions depend solely on iterated integrals of the measured acceleration output and of the control input. The approach is robust to noisy measurement and it has the advantage to provide fast, on-line, non-asymptotic state estimations in the form of formulae requiring only the input and the output of the system. Based on these estimations, alinearfeedbackcontrollawincludingestimatedpositionerror integrals is designed illustrating the possibilities of acceleration feedback via algebraic state estimation.

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An Algebraic Method for Eye Blink Artifacts Detection in Single Channel EEG Recordings

Cited by 28 publications

References 11 publications

On-line parameter estimation of a magnetic bearing

On-line parameter estimation of a magnetic bearing

Filtering Enhanced Traffic Management System (ETMS) Altitude Data

Acceleration feedback via an algebraic state estimation method

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