Characterizing Subjective Noisiness in Hospital Lobbies

Chen, Chiung Yao

doi:10.1515/aoa-2015-0026

Cited by 7 publications

(18 citation statements)

References 19 publications

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“…Darbyshire, 34 in a study of noises in intensive care units (ICUs), reported that noise sounds with higher pitches result in higher loudness than those with lower pitches, at least with respect to loudness as quantified by ISO 532-1:2017. 33 In the previous study under consideration here, 9 the noise spectra of the 16 hospital lobbies throughout the daytime (i.e. from 9:00 a.m. to 5:00 p.m.) were very similar in terms of the shape of each octave band, and in terms of higher levels of noise occurring over the middle octave range of 250–500 Hz.…”

Section: Methodsmentioning

confidence: 60%

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Monitoring time-varying noise levels and perceived noisiness in hospital lobbies

Chen

2020

Building Acoustics

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The aim of this study was to verify what statistical attributes are effective descriptors of time-varying noise levels due to road traffic and complex medical routine activities in hospital lobbies. In a psychoacoustic experiment, respondents provided perceived noisiness ratings affected by 12 noise events in hospital lobbies according to the processes recommended by ISO 15666. According to the correlations between subjective and objective survey results, the average LAeq ,15 m induced during the daytime itself was confirmed to be poorly related to subjective noisiness. The three independent variables shown to have the largest effects on perceived noisiness were (1) L min − L max, (2) the effective duration of the normalized autocorrelation function ( τe, h) of all LAeq,15 m from 9:00 a.m. to 5:00 p.m., and (3) the gradient of the cumulative distribution function (0.3–0.7 cumulative rate range). These statistical attributes have been confirmed as useful tools for detecting perceptions of complicated noise sources, but the associated correlations cannot be recovered from the relevant previous studies. Finally, construction noise was confirmed by factor analysis to be the accidental noise source with the highest factor loading (0.779) but a lower variance (<11.5%) than that of the primary factor (38.6%), and it was an average of 8 dB louder than the background noise at any given time. Accordingly, it is a primary confounding variable of the correlation matrixes of the results for independent hospitals verified by normality test.

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Section: Methodsmentioning

confidence: 60%

“…Hence, the statistical approach and the repetitive feature technology were confirmed as useful tools to apply in detailed correlation analysis of the relationships between objective measurements and subjective evaluations of complicated noise as in my previous study. 9…”

Section: Introductionmentioning

confidence: 99%

Monitoring time-varying noise levels and perceived noisiness in hospital lobbies

Chen

2020

Building Acoustics

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“…Some studies consider the statistical indices most commonly employed, such as L 5 , L 10 , L 50 , L 90 , and L 95 (employed in approximately 73% of the studies), and others less common ones, such as L 1 , L 70 , L 30 , and L 33 (used in 12% of the studies). It is noteworthy that 27% of the studies also performed frequency analysis (Carvalhais et al 2015 ; Chen 2015 ; Lahav 2015 ; Ai et al 2017 ; Galindo et al 2017 ; Santos et al 2017 ; Bliefnick et al 2019 ; Loupa et al 2019 ; Hasegawa and Ryherd 2020 ). In addition, 30% performed subjective analysis with questionnaires (Chen 2015 ; Oliveira et al 2015 ; de Araújo Vieira et al 2016 ; Ai et al 2017 ; Santos et al 2017 ; Cho et al 2019 ; Wu et al 2019 ; Zijlstra et al 2019 ; Astin et al 2020 ; Tang et al 2020 ), or used reverberation time measures such as RT 30 , RT 20 (Chen 2015 ; Cho et al 2019 ), or the Speech Intelligibility Index (SII) (Bliefnick et al 2019 ).…”

Section: Resultsmentioning

confidence: 99%

“…In addition, 30% performed subjective analysis with questionnaires (Chen 2015 ; Oliveira et al 2015 ; de Araújo Vieira et al 2016 ; Ai et al 2017 ; Santos et al 2017 ; Cho et al 2019 ; Wu et al 2019 ; Zijlstra et al 2019 ; Astin et al 2020 ; Tang et al 2020 ), or used reverberation time measures such as RT 30 , RT 20 (Chen 2015 ; Cho et al 2019 ), or the Speech Intelligibility Index (SII) (Bliefnick et al 2019 ).…”

Section: Resultsmentioning

confidence: 99%

“…Luetz et al ( 2016 ) adopted ICU room modification measures, achieving noise reductions in the order of 2.8 dB (A). The main measures proposed by the studies for noise reduction in hospitals involve preventive and educational actions (Filus et al 2015 ; Disher et al 2017 ; Santos et al 2017 ; Astin et al 2020 ); use of sound absorbing materials (Chen 2015 ); adoption of barriers and architectural designs (Monazzam et al 2015 ); simulations (Fiedler and Zannin 2015 ; Montes-González et al 2019 ); changes in equipment; physical installations, and procedures (Pirsaheb et al 2016 ; Shield et al 2016 ); and more studies in different locations and hospitals (Hasegawa and Ryherd 2020 ; García-Rivero et al 2020 ).…”

Section: Resultsmentioning

confidence: 99%

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Environmental noise in hospitals: a systematic review

Andrade

Silva

Lima

et al. 2021

Environ Sci Pollut Res

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Graphical abstract Environmental noise has been growing in recent years, causing numerous health problems. Highly sensitive environments such as hospitals deserve special attention, since noise can aggravate patients’ health issues and impair the performance of healthcare professionals. This work consists of a systematic review of scientific articles describing environmental noise measurements taken in hospitals between the years 2015 and 2020. The researchers started with a consultation of three databases, namely, Scopus, Web of Science, and ScienceDirect. The results indicate that for the most part, these studies are published in journals in the fields of medicine, engineering, environmental sciences, acoustics, and nursing and that most of their authors work in the fields of architecture, engineering, medicine, and nursing. These studies, which are concentrated in Europe, the Americas, and Asia, use as reference values sound levels recommended by the World Health Organization. L eq measured in hospital environments showed daytime values ranging from 37 to 88.6 dB (A) and nighttime values of 38.7 to 68.8 dB (A). L eq values for outdoor noise were 74.3 and 56.6 dB (A) for daytime and nighttime, respectively. The measurements were taken mainly inside hospitals, prioritizing more sensitive departments such as intensive care units. There is a potential for growth in work carried out in this area, but research should also include discussions about guidelines for improvement measures aimed at reducing noise in hospitals.

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Delving into Hearing Threshold of the Delay Gap of Initial Reflection in a Room by Using the Response of Cortical Brain Waves

Chen

2023

Preprint

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In this study, the apparent variation range of acoustical parameters were investigated in a concert hall. The initial time delay gap (ITDG) was evaluated in terms of its just noticeable difference (JND) through two instruments, the cello and the trumpet. Even though the IDTG values were prolonged over the measurements and were not significantly varied, an ITDG range of 22 - 220 ms in increments of 91 steps was produced electro-acoustically in an anechoic chamber with a loudspeaker. The result of JNDc ((delta gap/gap) was rated 0.059 and 0.081 at 50% “different” judgement ranges for the cello and trumpet tracks, respectively. The effective duration of the autocorrection function (ACF) of the continuous brainwaves (CBWs) within the alpha (8-13 Hz) frequency range on the left hemisphere responding to 91-step ITDG increments revealed that the continuous ratio minimum Tauee e of CBW was approximately equal to 0.28 s on the trumpet. The continuous ratios of Tauee e_min ((Tauee e_min_rear - Tauee e_min_front)/ Tauee e_min_front) of CBWs were constantly at 0.4. Furthermore, a homologous period of resonance between the subjective JNDc and Tauee e values of the ACF of CBWs in the alpha range allowed us to conclude that the subjective JND of the ITDG in a room is related to the W_IACC value of the interaural cross-correlation function, which reflect the characteristics of source signal themselves and arouse the activities of brain on the right hemisphere (p < 0.01).

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Characterizing Subjective Noisiness in Hospital Lobbies

Cited by 7 publications

References 19 publications

Monitoring time-varying noise levels and perceived noisiness in hospital lobbies

Monitoring time-varying noise levels and perceived noisiness in hospital lobbies

Environmental noise in hospitals: a systematic review

Delving into Hearing Threshold of the Delay Gap of Initial Reflection in a Room by Using the Response of Cortical Brain Waves

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