scholarly journals Effects of low-frequency noise from wind turbines on heart rate variability in healthy individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chun-Hsiang Chiu ◽  
Shih-Chun Candice Lung ◽  
Nathan Chen ◽  
Jing-Shiang Hwang ◽  
Ming-Chien Mark Tsou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wind Turbines ◽  
Mixed Model ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Residential Communities ◽  
Field Campaigns ◽  
The Relationship

AbstractWind turbines generate low-frequency noise (LFN, 20–200 Hz), which poses health risks to nearby residents. This study aimed to assess heart rate variability (HRV) responses to LFN exposure and to evaluate the LFN exposure (dB, LAeq) inside households located near wind turbines. Thirty subjects living within a 500 m radius of wind turbines were recruited. The field campaigns for LFN (LAeq) and HRV monitoring were carried out in July and December 2018. A generalized additive mixed model was employed to evaluate the relationship between HRV changes and LFN. The results suggested that the standard deviations of all the normal to normal R–R intervals were reduced significantly, by 3.39%, with a 95% CI = (0.15%, 6.52%) per 7.86 dB (LAeq) of LFN in the exposure range of 38.2–57.1 dB (LAeq). The indoor LFN exposure (LAeq) ranged between 30.7 and 43.4 dB (LAeq) at a distance of 124–330 m from wind turbines. Moreover, households built with concrete and equipped with airtight windows showed the highest LFN difference of 13.7 dB between indoors and outdoors. In view of the adverse health impacts of LFN exposure, there should be regulations on the requisite distances of wind turbines from residential communities for health protection.

Effects of low-frequency noise from wind turbines on heart rate variability in healthy individuals

2021 ◽  
Author(s):  
Chun-Hsiang Chiu ◽  
Shih-Chun Candice Lung ◽  
Nathan Chen ◽  
Jing-Shiang Hwang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wind Turbines ◽  
Mixed Model ◽  
Low Frequency ◽  
Clean Energy ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Residential Areas ◽  
Worst Case

Abstract Background: Wind power has been applied around the world as a source of clean energy. However, wind turbines generate low-frequency noise (LFN, 20-200 Hz), which poses health risks to nearby residents. This study aimed to assess heart rate variability (HRV) response to LFN exposure and to evaluate the LFN exposure (dB, LAeq) inside households located near wind turbines. Methods: Thirty subjects living within a 500 m radius of wind turbines were recruited. The field campaigns for LFN (LAeq) and HRV monitoring were carried out in July and December 2018. A generalized additive mixed model was employed to evaluate the relationship between HRV changes and LFN. Results: The results suggested that the standard deviations of all normal to normal R-R intervals reduced significantly by 3.39% with a 95% CI = (0.15%, 6.52%) per 7.86 dB (LAeq) of LFN in the exposure range of 38.2-57.1 dB (LAeq)—i.e., a 0.43% reduction per 1 dB (LAeq). The results of household monitoring showed that the indoor LFN exposure (LAeq) ranged between 30.7 and 43.4 dB (LAeq) at a distance of 124-330 m from wind turbines. The worst case had 99.6%, 89.1%, and 96.8% at daytime, evening, and nighttime, respectively, exceeding the LFN standards of the Taiwan Environmental Protection Administration. Moreover, households built with concrete and equipped with airtight windows showed the highest LFN difference of 13.7 dB between indoors and outdoors. Conclusion: This work is the first study assessing the HRV impacts from turbine LFN in Asia, where wind turbines installed within short distances from residential areas. In view of the adverse health impacts of LFN exposure, there should be regulations on the requisite distances of wind turbines from residential communities for health protection.

Detrended Fluctuation Analysis of Heart Rate Variability in Noise Exposure

2014 ◽  
Vol 1044-1045 ◽  
pp. 1129-1134 ◽  
Author(s):  
Shih Tsung Chen ◽  
Li Ho Tseng ◽  
Yuan Po Lee ◽  
Hong Zhun Wu ◽  
Chia Yi Chou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Detrended Fluctuation Analysis ◽  
Low Frequency ◽  
Fluctuation Analysis ◽  
Frequency Noise ◽  
Cardiovascular Activity ◽  
Low Frequency Noise ◽  
Rr Intervals ◽  
Detrended Fluctuation

During the past two decades, most studies have employed questionnaires to characterize the effects of noise on behavior and health. Developments in physiological techniques have provided a noninvasive method for recording cardiovascular autonomic activity by using an electrocardiogram (ECG). We investigated cardiovascular activity changes in exposure to exposure to low-frequency noise for various noise intensities by using detrended fluctuation analysis (DFA) of heart rate variability (HRV). We hypothesized that distinct noise intensities would affect cardiovascular activity, which would be reflected in the HRV and DFA parameters. A total of 17 healthy volunteers participated in this study. The test intensities of noises were no noise, 70-dBC, 80-dBC, and 90-dBC. Each noise was sustained for 5 minutes and the ECG was recorded simultaneously. The cardiovascular responses were evaluated using DFA of the beat-to-beat (RR) intervals obtained from ECG signals. The results showed that the mean RR intervals variability and mean blood pressure did not substantially change relative to the noises. However, the short-term scaling exponent (α1) of the DFA of the background noise (no noise) condition was lower than the 70-dBC, 80-dBC and 90-dBC noises (P< 0.05, repeated measures analysis of variance). The α1of 90-dBC noise was significantly higher than the α1of BN condition according to a Mann–Whitney U test (P< 0.01). We concluded that exposure to low-frequency noise significantly affects the temporal correlations of HRV, but it does not influence RR intervals variability.

Spectral Characteristics of Heart Rate Variability in Noise Exposure

2014 ◽  
Vol 1079-1080 ◽  
pp. 515-521
Author(s):  
Li Ho Tseng ◽  
Ching Chang Yang ◽  
Yuan Po Lee ◽  
Hong Zhun Wu ◽  
Chia Yi Chou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Background Noise ◽  
Low Frequency ◽  
Cardiovascular Responses ◽  
Frequency Noise ◽  
Cardiovascular Activity ◽  
Low Frequency Noise ◽  
Noise Levels

Ecological studies have shown that the chronic effects of exposure to environmental noise cause annoyance. However, in the past, most studies have used questionnaires to evaluate the effects of noise pollution on psychosomatic responses. This study investigated cardiovascular activity changes in exposure to low-frequency noise at various noise intensities. The authors hypothesized that distinct noise intensities affect cardiovascular activity, which would be reflected in the spectral analysis parameters. The evaluation intensities of low frequency noises (from 20 to 200 Hz) were background noise (BN), 70-dBC, 80-dBC, and 90-dBC. The electrocardiographic (ECG) data was recorded for 5 minutes under various noise levels. The cardiovascular responses were evaluated using spectral analysis of the beat-to-beat (RR) intervals obtained from ECG signals. The results showed that the average blood pressure and mean RR interval variability did not substantially change relative to the noise levels. However, the low-frequency (LF) power and the ratio of LF power to high-frequency power (LF/HF) from ECG under the BN condition were significantly lower than the 80-dBC, and 90-dBC noise levels. In addition, the normalized LF of the background noise condition was significantly lower than the low-frequency of the noise levels at various intensities. In conclusion, the frequency-domain-based measures appear to be a powerful tool for exposure to low-frequency noise, even in short-term heart rate variability time series.

scholarly journals The Relationship between Vibratory Sensation and Body Surface Vibration Induced by Low-Frequency Noise

2002 ◽  
Vol 21 (2) ◽  
pp. 87-100 ◽  
Author(s):  
Yukio Takahashi ◽  
Kazuo Kanada ◽  
Yoshiharu Yonekawa
Keyword(s):  
Body Surface ◽  
Mechanical Vibration ◽  
Low Frequency ◽  
The Body ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Vibration Acceleration ◽  
Surface Vibration ◽  
Human Body Surface ◽  
The Relationship

Human body surface vibration induced by low-frequency noise was measured at the forehead, the chest and the abdomen. At the same time, subjects rated their vibratory sensation at each of these locations. The relationship between the measured vibration on the body surface and the rated vibratory sensation was examined, revealing that the vibratory sensations perceived in the chest and abdomen correlated closely with the vibration acceleration levels of the body surface vibration. This suggested that a person exposed to low-frequency noise perceives vibration at the chest or abdomen by sensing the mechanical vibration that the noise induces in the body. At the head, on the other hand, it was found that the vibratory sensation correlated comparably with the vibration acceleration level of the body surface vibration and the sound pressure level of the noise stimulus. This finding suggested that the mechanism of perception of vibration in the head is different from that of the perception of vibratory sensation in the chest and the abdomen.

Low frequency noise and infrasound from wind turbines

2011 ◽  
Vol 59 (2) ◽  
pp. 135 ◽  
Author(s):  
Robert D. O’Neal ◽  
Robert D. Hellweg ◽  
Richard M. Lampeter
Keyword(s):  
Wind Turbines ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise

scholarly journals Development of an on-site system for measuring the low-frequency noise and complainant’s responses

2018 ◽  
Vol 37 (2) ◽  
pp. 373-384
Author(s):  
Hiroshi Sato ◽  
Jongkwan Ryu ◽  
Kenji Kurakata
Keyword(s):  
Time Trends ◽  
Sound Pressure ◽  
Low Frequency ◽  
Dominant Frequency ◽  
Pressure Level ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Measurement Results ◽  
Frequency Components ◽  
The Relationship

An on-site system for measuring low-frequency noise and complainant's responses to the low-frequency noise was developed to confirm whether the complainant suffer from the environmental noise with low-frequency components. The system suggests several methods to find the dominant frequency and major sound pressure level spectrum of the noise causing annoyance. This method can also yield a quantified relationship (correlation coefficient and percentage of response to the noise) between physical noise properties and the complainant’s responses. The advantage of this system is that it can easily find the relationship between the complainant’s response to the acoustic event of the houses and the physical characteristics of the low-frequency noise, such as the time trends and frequency characteristics. This paper describes the developed system and provides an example of the measurement results.

Proposed Criteria for Low Frequency Industrial Noise in Residential Communities

2005 ◽  
Vol 24 (2) ◽  
pp. 97-105 ◽  
Author(s):  
George F. Hessler
Keyword(s):  
United States ◽  
Low Frequency ◽  
The United States ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Residential Areas ◽  
Noise Sources ◽  
Residential Communities ◽  
Open Cycle ◽  
Industrial Sources

There is a need in the United States for some Federal or prominent standards organization to publish limits in residential areas for low frequency noise attributable to industrial sources. This paper proposes maximum limits based on experience in investigating and solving low frequency noise problems, principally from open cycle combustion turbine installations The author believes the recommended C-weighted limits in this paper are applicable to most common steady low-frequency noise sources in addition to combustion turbines due to the combined tonal and broadband character of the sound. It is hoped standardizing bodies can add this reference to the larger body of literature to arrive at a workable sorely-needed standard.

scholarly journals Effect of moderate physical exercises on the relationship of variability of the heart rhythm with the level of blood pressure and hemodynamic functions in women with essential hypertension

2020 ◽  
pp. 64-73
Author(s):  
Б.И. Кузник ◽  
Ю.Н. Смоляков ◽  
Е.С. Гусева ◽  
С.О. Давыдов ◽  
И.В. Файн
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Blood Flow ◽  
Heart Rate Variability ◽  
Essential Hypertension ◽  
High Frequency ◽  
Low Frequency ◽  
Mean Square ◽  
Positive Correlations ◽  
The Relationship

Цель исследования - выявление взаимосвязи между показателями вариабельности сердечного ритма (ВСР), кровяным давлением и гемодинамическими функциями у женщин, страдающих гипертонической болезнью (ГБ) и находящихся на медикаментозной терапии (ГБ-1), либо в дополнение к этому, проходящих регулярные курсы кинезитерапии (ГБ-2). Методика. Наблюдения проведены на 72 женщинах, страдающих артериальной гипертензией II стадии. В группу ГБ-1 вошли 37 женщин с ГБ, находящихся на медикаментозной терапии, в группу ГБ-2 - 35 женщин с ГБ, которые, помимо медикаментозной терапии, регулярно проходили на протяжении 2-3 лет по 3-4 полуторамесячных курса кинезитерапии (управляемые умеренные физические нагрузки). Для изучения гемодинамики был использован датчик динамического рассеяния света (miniature Dynamic Light Scattering - mDLS) от Elfi-Tech (Rehovot, Israel), измеряющий сигналы, инициированные кожным кровотоком, и использующий методику разложения сигнала на частотные компоненты, связанные с разными гемодинамическими источниками. Из пульсовой компоненты mDLS сигнала извлекалась информация о вариабельности RR-интервалов и рассчитывались индикаторы вариабельности сердечного ритма. Введен показатель «гемодинамический индекс» (Hemodynamic Index - HI). Зависимость HI от скорости сдвига интерпретируется путем сопоставления каждой полосе частот определенной скорости сдвига (HI1 - низкочастотный, HI2 - промежуточный, HI3 - высокочастотный). Использованы следующие относительные (RHI, Relative Hemodynamic Index) и осцилляторные (OHI, Oscillatory Hemodynamic Indexes) гемодинамические индексы: нейрологический (NEUR), Майера (MAYER), дыхательный (RESP) и пульсовой (PULSE). ВСР показатели включали: HR (Heart Rate), PWR (Power) - общую мощность колебаний, LF (Low Frequency), HF (High Frequency), SDNN (Standard Deviation of the Normal-to-Normal), RMSSD (Root Mean Square of the Successive Differences), а также индексы: CVI (Cardiac Vagal Index) и CSI (Cardiac Sympathetic Index). Результаты. У женщин, находящихся исключительно на медикаментозной терапии (ГБ-1), выявляются отрицательные взаимосвязи LF и LF/HF с систолическим, средним и пульсовым давлением. При ГБ-2 проявляются отрицательные связи PWR, LF, HF с пульсовым давлением. При ГБ-1 обнаружены положительные взаимосвязи между HR и гемодинамическими индексами HI1, RHI2 и отрицательная взаимосвязь с RHI3, а также между RMSSD и RHI3 и между HF и HI1/HI3. У пациенток ГБ-2 обнаружена отрицательная корреляция SDNN и RHI1, а также PWR и RHI1; положительные взаимосвязи между PWR и HI2, HI3, RHI2, HF и RHI3 и LF/HF с HI1/HI3; отрицательные связи HF c HI1/HI3 и с RHI1, а также между LF/HF и RHI3, CSI и RHI3. У больных ГБ-1 имеются прямые связи между SDNN, PWR, LF, HF, CVI и NEUR_HI1, что свидетельствует о действии этих факторов на эндотелиальный кровоток (HI1). В группе ГБ-2 установлено наличие лишь положительных связей между LF, HF и NEUR_HI3. У больных ГБ-1 на уровень АД влияют все без исключения осцилляторные ритмы, которые могут оказывать как отрицательное (с MAYER_HI1, PULSE_HI2), так и положительное (MAYER_HI2, RESP_HI3) влияние. У больных ГБ-2 взаимосвязи АД с осцилляторными индексами не обнаружены. Заключение. Уменьшение в группе ГБ-2 по сравнению с больными группы ГБ-1 числа факторов, влияющих на АД и гемодинамику, носит более совершенный и благоприятный характер, что и обеспечивает более быструю и устойчивую нормализацию артериального давления. Aim. To study the relationship between heart rate variability (HRV), blood pressure and hemodynamic functions in women with essential hypertension (EH) receiving a drug therapy alone (EH-1) or in combination with regular courses of kinesitherapy (EH-2). Methods. The study included 72 women with EH. The EH-1 group consisted of 37 women with stage II arterial hypertension. The EH-2 group consisted of 35 women with stage II arterial hypertension who underwent 3-4 1.5-month courses of kinesitherapy (controlled moderate physical activity) on a regular basis for 2-3 years. Hemodynamics was studied with a miniature Dynamic Light Scattering (mDLS) sensor from Elfi-Tech (Rehovot, Israel), which measures signals initiated by the skin blood flow by decomposing the signal into frequency components associated with different hemodynamic sources. Information on the RR interval variability was extracted from the pulse component of mDLS signal, and indicators of heart rate variability were calculated. A Hemodynamic Index (HI) was introduced. The HI dependence on shear rate was interpreted by matching each frequency band with a specific shear rate (HI1, low-frequency; HI2, intermediate; HI3, high-frequency). The following relative (RHI, Relative Hemodynamic Index) and oscillatory (OHI, Oscillatory Hemodynamic Indexes) indexes were used: neurological (NEUR), Mayer (MAYER), respiratory (RESP), and pulse (PULSE) ones. The HRV indexes included HR (Heart Rate), PWR (Power, total oscillation power), LF (Low Frequency), HF (High Frequency), SDNN (Standard Deviation of the Normal-to-Normal), RMSSD (Root Mean Square of the Successive Differences). CVI (Cardiac Vagal Index), and CSI (Cardiac Sympathetic Index). Results. In women who were on drug therapy alone (EH-1), negative relationships were found for LF and LF/HF with systolic, mean and pulse pressure. For EH-2, PWR, LF, and HF negatively correlated with pulse pressure. For EH-1, HR positively correlated with the hemodynamic indices HI1 and RHI2 and negatively correlated with RHI3; RMSSD negatively correlated with RHI3; and HF negatively correlated with HI1/HI3. For patients with EH-2, negative correlations were observed for SDNN and RHI1, PWR and RHI1; positive correlations were found between PWR and HI2; HI3, RHI2, HF and RHI3; and between LF/HF and HI1/HI3. HF negatively correlated with HI1/HI3 and with RHI1. LF/HF negatively correlated with RHI3, and CSI negatively correlated with RHI3. In patients with EH-1, SDNN, PWR, LF, HF, CVI, and NEUR_HI1 were directly related, which indicated an effect of these factors on the endothelial blood flow (HI1). In the EH-2 group, only positive correlations were found between LF, HF, and NEUR_HI3. In EH-1 patients, all oscillatory rhythms influenced BP; this influence could be both negative (for MAYER_HI1, PULSE_HI2) and positive (for MAYER_HI2, RESP_HI3). In EH-2 patients, no relationship was found between blood pressure and oscillatory indices. Conclusion. The smaller number of factors influencing blood pressure and hemodynamics in the EH-2 group compared to the EH-1 group was more beneficial and favorable, which ensured faster and steadier normalization of blood pressure.

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