Detection of smoking, gender and starvation - satiety using photoplethysmogram signals

Korkmaz, Onur Erdem; Aydemir, Önder; Öztürk, Mehmet

doi:10.1109/siu.2017.7960537

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…In another study, Korkmaz et al determined smoking/ non-smoking, male/female and starvation/toughness statuses of 66 participants using 60 s (approximately 60 periods) PPG signals. They respectively obtained 73.7%, 72.8% and 65.8% classification accuracy (CA) rates [9]. In another PPG based cardiovascular disease study, Prabhakar et al applied their proposed method to 7 s PPG signals for the detection of cardiovascular disease and achieved a classification accuracy rate of 99.48% for the dataset collected from 42 subjects [10].…”

Section: Introductionmentioning

confidence: 99%

Determination of hypertension disease using chirp z-transform and statistical features of optimal band-pass filtered short-time photoplethysmography signals

Aydemir¹,

Şahin²,

Aydemir³

2020

Biomed. Phys. Eng. Express

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Hypertension is the condition where the normal blood pressure is high. This situation is manifested by the high pressure of the blood in the vein towards the vessel wall. Hypertension mostly affects the brain, kidneys, eyes, arteries and heart. Therefore, the diagnosis of this common disease is important. It may take days, weeks or even months for diagnosis. Often a device, called a blood pressure holter, is connected to the person for 24 or 48 h and the person’s blood pressure is recorded at certain intervals. Diagnosis can be made by the specialist physician considering these results. In recent years, various physiological measurement techniques have been used to accelerate this time-consuming diagnostic phase and intelligent models have been proposed. One of these techniques is photopletesmography (PPG). In this study, a model for the detection of hypertension disease in individuals was proposed using chirp z-transform and statistical features (total band power, autoregressive model parameters, standard deviation of signal’s derivative and zero crossing rate) of optimal band-pass filtered short-time PPG signals. The proposed method was successfully applied to 657 PPG trials, which each of them had only 2.1 s signal length and achieved a classification accuracy rate of 77.52% on the test data. The results showed that the diagnosis of hypertension can be performed effectively by chirp z-transform and statistical features and support vector machine classifier using optimal frequency range of 1.4–6 Hz.

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Section: Introductionmentioning

confidence: 99%

Determination of hypertension disease using chirp z-transform and statistical features of optimal band-pass filtered short-time photoplethysmography signals

Aydemir¹,

Şahin²,

Aydemir³

2020

Biomed. Phys. Eng. Express

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Investigating the impact of smoking habits through photoplethysmography analysis

Qananwah,

Khader,

Al-Hashem

et al. 2024

Physiol. Meas.

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Smoking is widely recognized as a significant risk factor in the progression of arterial stiffness and cardiovascular diseases. Valuable information related to cardiac arrhythmias and heart function can be obtained by analyzing biosignals such as the electrocardiogram (ECG) and the photoplethysmogram (PPG). The PPG signal is a non-invasive optical technique that can be used to evaluate the changes in blood volume, and thus it can be linked to the health of the vascular system. Objective. In this study, the impact of three smoking habits -cigarettes, shisha, and electronic cigarettes (e-cigarettes)- on the features of the PPG signal were investigated. Approach. The PPG signals are measured for 45 healthy smokers before, during, and after the smoking session and then processed to extract the morphological features. Quantitative statistical techniques were used to analyze the PPG features and provide the most significant features in the three smoking habits. The impact of smoking is observed through significant changes in the features of the PPG signal, indicating blood volume instability. Main results. The results revealed that the three smoking habits influence the characteristics of the PPG signal significantly, which persist even after 15 minutes of smoking. Among them, shisha has the greatest impact on PPG features, particularly on heart rate, systolic time, augmentation index, and peak pulse interval change. In contrast, e-cigarettes have the least effect on PPG features. Interestingly, smoking electronic cigarettes, which many participants use as a substitute for traditional cigarettes when attempting to quit smoking, has nearly a comparable effect to regular smoking. Significance. The findings suggest that individuals who smoke shisha are more likely to develop cardiovascular diseases at an earlier age compared to those who have other smoking habits. Understanding the variations in the PPG signal caused by smoking can aid in the early detection of cardiovascular disorders and provide insight into cardiac conditions. This ultimately contributes to the prevention of the development of cardiovascular diseases and the development of a health screening system.

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Gender Recognition from PPG Signals of People with Different Blood Pressure

Aydemir

Şahin

Aydemir

2021

2021 29th Signal Processing and Communications Applications Conference (SIU)

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Detection of smoking, gender and starvation - satiety using photoplethysmogram signals

Cited by 3 publications

References 11 publications

Determination of hypertension disease using chirp z-transform and statistical features of optimal band-pass filtered short-time photoplethysmography signals

Determination of hypertension disease using chirp z-transform and statistical features of optimal band-pass filtered short-time photoplethysmography signals

Investigating the impact of smoking habits through photoplethysmography analysis

Gender Recognition from PPG Signals of People with Different Blood Pressure

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