Noise-Robust Algorithm for PPG Signal Measurement

Kim, Minho; Kim, Tae-Wook; Jang, Sung-Hwan; Ban, Dahee; Min, Byungseok; Kwon, Sungoh

doi:10.7840/kics.2013.38c.12.1085

Cited by 2 publications

(3 citation statements)

References 8 publications

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“…erefore, to recognize and determine the user emotions, many studies are being conducted using biological signals, which are physiological responses. By extracting the signal features from biological signals, a psychological emotional state can be determined [14][15][16][17][18].…”

Section: Emotional Responses and Physiological Signalsmentioning

confidence: 99%

“…Furthermore, a study that measured the biological signals of an EEG and an electrocardiograph (ECG) displayed the emotional states of tension, irritation, anger, joy, and surprise on the power spectrum graph of the signals [24,25]. However, to measure EEG signals, the electrical activities of the brain can be measured only by accurately attaching a sensor to a fixed position on the head; consequently, user discomfort occurs owing to movement limitations [13,[15][16][17][18][19][20][21][22].…”

Section: Emotional Responses and Physiological Signalsmentioning

confidence: 99%

“…When a light is projected onto an area of the human body with thin skin, such as the tip of a finger or an ear lobe, some of the light is absorbed in the blood, bone, and tissue, and the remaining light penetrates the skin. erefore, a change in the intensity of the penetrated light can be said to be a reflection of the change in blood flow [14][15][16][17]. Here, PPG signals can be measured because the amount of light absorbed by the skin, according to heart contraction and relaxation, differs owing to changes in blood flow.…”

Section: Implementation Of Mobile Emotional Content Playermentioning

confidence: 99%

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Real-Time Mobile Emotional Content Player Using Smartphone Camera-Based PPG Measurement

Lee

Kim

2019

Mobile Information Systems

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A real-time mobile content player was developed that can recognize and reflect emotions in real time using a smartphone. To determine effective awareness, a photoplethysmogram (PPG), which is a biological signal, was measured to recognize emotional changes in users presented with content intended to induce an emotional response. To avoid the need for a separate sensor to measure the PPG, PPG signals were extracted from the red (R) values of images acquired by the rear camera of a smartphone. To reflect an emotion, the saturation (S) and brightness (V) levels, which are related to the ambience of a content, are changed to reflect the emotional changes of the user within the content itself in real time. Arousal- and relaxation-inducing scenarios were conducted to validate the effectiveness. The sample t-test results show that the average peak-to-peak interval (PPI), which is the time interval between the peaks of PPG signals, was significantly low when viewing the content under the arousal-inducing scenario as compared to when watching regular content, and it was determined that the emotion of the user was led to a state of arousal. Ten university students (five males and five females) participated in the experiment. The users had no cardiac disease and were asked not to drink or smoke before the experiment. The average PPI was significantly higher when the content was viewed in the relaxation-inducing scenario compared to regular content, and it was determined that the emotion of the user was induced to a state of relaxation. The designed emotional content player was confirmed to be an interactive system, in which the video content and user concurrently affect each other through the system.

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Section: Emotional Responses and Physiological Signalsmentioning

confidence: 99%

Section: Emotional Responses and Physiological Signalsmentioning

confidence: 99%

Section: Implementation Of Mobile Emotional Content Playermentioning

confidence: 99%

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Real-Time Mobile Emotional Content Player Using Smartphone Camera-Based PPG Measurement

Lee

Kim

2019

Mobile Information Systems

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User-Adaptive Movement Noise Detection Algorithm Using Wavelet Transform

Ban¹,

Kwon

2015

The Journal of Korean Institute of Communications and Informati

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In this paper, we propose an algorithm to detect movement noise in PPG(Photoplethysmography) measurements.Movement noise significantly deteriorate PPG signals in measurement, so that a movement noise detection algorithm is critical before using measured PPG signals for applications such as diagnosis. To detect movement noise, we apply wavelet transform to PPG signals instead of short-time Fourier transform and decide if the measured signlas include movement noise. To that end, we adaptively choose a wavelet, which is the most similar to the subject's PPG pattern. In the case when movement noise is intentionally added in the 20% and 30% of the total experiment time, our algorithm detects time-slots including movement and outperforms previous works.

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Noise-Robust Algorithm for PPG Signal Measurement

Cited by 2 publications

References 8 publications

Real-Time Mobile Emotional Content Player Using Smartphone Camera-Based PPG Measurement

Real-Time Mobile Emotional Content Player Using Smartphone Camera-Based PPG Measurement

User-Adaptive Movement Noise Detection Algorithm Using Wavelet Transform

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