An Improved Signal Segmentation Method using Genetic Algorithm

Azami, Hamed; Mohammadi, Karim; Hassanpour, Hamid

doi:10.5120/3586-4967

Cited by 20 publications

(18 citation statements)

References 13 publications

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“…The Savitzky-Golay (S-G) filter is a commonly used low-pass signal within the time domain filter. It is suitable for smoothing continuous signals and has the characteristics of fast calculation and strong operability [27]. Thus, the hyperspectral data preprocessed by S-G filter can effectively utilize the information in adjacent spectra with less noise.…”

Section: Effective Wavelengths Selectionmentioning

confidence: 99%

Rapid and Nondestructive Classification of Cantonese Sausage Degree Using Hyperspectral Images

Wang

2019

Applied Sciences

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Hyperspectral images are widely used in the food industry as a fast and non-destructive analytical technique. Cantonese sausage has a long history and is a very old food production and meat preservation technology. According to the physical and chemical characteristics of the sausage, the Chinese business industry standard SB/t10003-92 divides the sausage into three grades, which are called excellent grade, level 1, and level 2. In this paper, k-means is adopted first to separate two parts of the meat adaptively to improve the discriminant rate. The hyperspectral information of the near-infrared band is extracted by successive projections algorithm (SPA). The multiple linear regression (MLR) and partial least squares regression (PLSR) algorithms are used to classify the sausage grade. The experimental results show that the lean meat and fat of the sausage have different characteristics in the near-infrared band, and the modeling results have higher accuracy and anti-interference after separating lean meat and fat meat. The best model of sausage classification is using SPA-MLR method to model the fat region of Cantonese sausage; the prediction accuracy of which is 100%. It was found that the modeling results of fat were better than lean meat in both PLSR and SPA-MLR, which indicated that there were obvious differences in fat composition among different grades of sausage, and the fat of sausage was more suitable for classification.

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Section: Effective Wavelengths Selectionmentioning

confidence: 99%

Rapid and Nondestructive Classification of Cantonese Sausage Degree Using Hyperspectral Images

Wang

2019

Applied Sciences

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“…As for segmenting signals, [8], [9] and [14] suggest using different variations of Modified Varri, a standard adaptive segmentation technique. [8] proposes to smooth the signal using moving average or Savitzky-Golay filter, which avoids causing shifts in the original signal, prior to using Modified Varri.…”

Section: Related Workmentioning

confidence: 99%

Developing a low dimensional patient class profile in accordance to their respiration-induced tumor motion

2017

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Tumor location displacement caused by respiration-induced motion reduces the efficacy of radiation therapy. Three medically relevant patterns are often observed in the respirationinduced motion signal: baseline shift, ES-Range shift, and D-Range shift. In this paper, for patients with lower body cancer, we develop class profiles (a low dimensional pattern frequency structure) that characterize them in terms of these three medically relevant patterns. We propose an adaptive segmentation technique that turns each respiration-induced motion signal into a multi-set of segments based on persistent variations within the signal. These multi-sets of segments is then probed for base behaviors. These base behaviors are then used to develop the group/class profiles using a modified version of the clustering technique described in [1]. Finally, via quantitative analysis, we provide a medical characterization for the class profiles, which can be used to explore breathing intervention technique. We show that, with i) carefully designed feature sets, ii) the proposed adaptive segmentation technique, iii) the reasonable modifications to an existing clustering algorithm for multi-sets, and iv) the proposed medical characterization methodology, it is possible to reduce the time series respiration-induced motion signals into a compact class profile. One of our co-authors is a medical physician and we used his expert opinion to verify the results.

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“…This is continuously applied until the last sample point of the record Y is reached. With the parameters B, M and segmented record Ys, now it is possible to reconstruct the original record Y, as we can see in (5), where ln represents the length of the line n. = ( . ) +…”

Section: = ∑ =1mentioning

confidence: 99%

“…Signal segmentation process is a very common technique applied in many biomedical digital systems, as wells as analysis of long-term ECG traces [5], [6]. Every application where signal processing is been used, a segmentation process is included.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of Premature Atrial Contraction and Premature Ventricular Contraction on ECG Traces by Applying PLA as Segmentation Process

Gonzalez¹,

Avitia²,

Flores³

et al. 2015

JOIG

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Premature Atrial Contraction (PAC) and Premature Ventricular Contraction (PVC) are two types of ECG arrhythmias that are identified for presenting anomalies in the normal cardiac rhythm, generating alterations in the heart rate that disrupts his mechanic and electric heart activity due to these delayed contractions (premature). Also when a delayed contraction occurs (i.e. PVC or PAC), it generates alterations in heart rate that can produce ventricular tachycardia and eventually sudden cardiac arrest. Piece Wise Linear Algorithm (PLA) is a widely used segmentation process that represents each signal as linear segments with different scopes. In this work we are presenting an evaluation of PLA and the optimal number of segments when this type of segmentation is applied on normal ECG traces and when these ECG traces present PAC or PVC. We established that optimal number of segments is related with the coefficient of determination (R 2), before and after the reconstruction of an ECG trace. Results show that number of segments taken on normal ECG traces differs radically compared when this method was applied on traces with PVC and PAC events.

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An Improved Signal Segmentation Method using Genetic Algorithm

Cited by 20 publications

References 13 publications

Rapid and Nondestructive Classification of Cantonese Sausage Degree Using Hyperspectral Images

Rapid and Nondestructive Classification of Cantonese Sausage Degree Using Hyperspectral Images

Developing a low dimensional patient class profile in accordance to their respiration-induced tumor motion

Reconstruction of Premature Atrial Contraction and Premature Ventricular Contraction on ECG Traces by Applying PLA as Segmentation Process

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