Munhum Park

Analysis of the soundscape in an intensive care unit based on the annotation of an audio recording.

The acoustic environments in hospitals, particularly in intensive care units (ICUs), are characterized by frequent high-level sound events which may negatively affect patient outcome. Many studies performed acoustic surveys, but the measurement protocol was not always reported in detail, and the scope of analysis was limited by the selected mode of sound level meters. Fewer studies systematically investigated the noise sources in ICUs by employing an observer in the patient room, which may potentially bias the measurement. In the current study, the soundscape of an ICU was evaluated where acoustic parameters were extracted from a ∼67-h audio recording, and a selected 24-h recording was annotated off-line for a source-specific analysis. The results showed that the patient-involved noise accounted for 31% of the acoustic energy and 11% of the predicted loudness peaks (PLPs). Excluding the patient-involved noise, the remaining acoustic energy was attributed to staff members (57%), alarms (30%), and the operational noise of life-supporting devices (13%). Furthermore, the contribution of each noise category to the PLPs was found to be more uneven: Staff (92%), alarms (6%), and device noise (2%). The current study suggests that most of the noise sources in ICUs may be associated with modifiable human factors.

Noise pollution in the ICU: time to look into the mirror

No abstract

Irrelevant speech effect under stationary and adaptive masking conditions

The irrelevant speech effect was investigated in this study where the serial-recall task was performed under six different conditions: Silence, speech-only, noise-only, speech masked by a stationary noise at two different signal-to-noise ratios (SNRs), and speech masked by an adaptive noise. Measured in five test blocks distributed throughout the four test days, the error rate of the serial-recall task under the silence condition sharply decreased in the first few test blocks, halved after completing about seven blocks. When the adaptive masking scheme was used, the error rate of the serial-recall test was reduced compared to the speech-only condition (by 9%) and to the lower-SNR stationary noise (by 4.4%). However, the serial-recall performance was not significantly different between the stationary and the adaptive maskers when the average sound level was carefully matched. Speech Transmission Index (STI) and the correlation coefficient of power spectra were used as the estimators of the temporal and spectral distinctiveness between sound tokens, respectively. The comparison to the test results implied that the frequency-domain estimator may be a better predictor of the relative ISE especially for a non-stationary masker, although it was also suggested that such estimators may have to be combined possibly with an appropriate weighting.

A model of sound localisation applied to the evaluation of systems for stereophony

In this paper, a model of human sound localisation is described, and its prediction is compared to the results of listening tests. The model takes binaural signals as the input, processing them in a series of signal processing modules, which simulate the peripheral, binaural and the central stages of spatial hearing. In particular, the central processor of the model considers the excitation-inhibition (EI) cell activity patterns as the internal representation of available cues, and the source location estimates are obtained by using a simple pattern-matching procedure. In the listening tests, stereophonic images were presented to the listeners front, where the stimulus was either broadband or 1/3 octave band noise at 7 centre frequencies from 0.5 kHz to 6 kHz. The subjective responses compared well to the model prediction across frequency except for some cases where the image location was overestimated. Also, the prediction for the localisation of broadband phantom images agreed well with the test results, where the model prediction was integrated across frequency according to a tentatively suggested weighting function. Although the neuroscientific background is weak for the model, the good agreement with the subjective responses suggests that the model is worth investigating further.

The influence of APACHE II score on the average noise level in an intensive care unit: an observational study

BackgroundNoise levels in hospitals, especially in intensive care units (ICUs) are known to be high, potentially affecting not only the patients’ well-being but also their clinical outcomes. In an observational study, we made a long-term measurement of noise levels in an ICU, and investigated the influence of various factors on the noise level, including the acute physiology and chronic health evaluation II (APACHE II) score.MethodsThe average noise level was continuously measured for three months in all (eight) patient rooms in an ICU, while the patient data were also registered, including the APACHE II score. The 24-hour trend of the noise level was obtained for the patients of length-of-stay (LOS) ≥1 day, which was compared to the timeline of the ICU routine events. For the patients with LOS ≥4 days, the average noise levels in the first four days were analyzed, and regression models were established using the stepwise search method based on the Akaike information criterion.ResultsFeatures identified in the 24-hour trends (n = 55) agreed well with the daily routine events in the ICU, where regular check-ups raised the 10-minute average noise level by 2~3 dBA from the surrounding values at night, and the staff shift changes consistently increased the noise level by 3~5 dBA. When analyzed in alignment with the patient’s admission (n=22), the daytime acoustic condition improved from Day 1 to 2, but worsened from Day 2 to 4, most likely in relation to the various phases of patient’s recovery. Regression analysis showed that the APACHE II score, room location, gender, day of week and the ICU admission type could explain more than 50 % of the variance in the daily average noise level, LAeq,24h. Where these factors were argued to have causal relations to LAeq,24h, the APACHE II score was found to be most strongly correlated: LAeq,24h increased by 1.3~1.5 dB when the APACHE II score increased by 10 points.ConclusionsPatient’s initial health condition is one important factor that influences the acoustic environment in an ICU, which needs to be considered in observational and interventional studies where the noise in healthcare environments is the subject of investigation.

Binaural Hearing and Systems for Sound Reproduction

Recent developments in models of binaural hearing can be usefully adapted and extedned to provide design tools for engineers engaged in the design of systems for sound reproduction. The particular focus of the work described is upon the development of models that give good statistical predictions of human sound localisation, based upon knowledge of the fluctuating acoustic pressures at the ears. Such models can be applied successfully to the prediction of stereophonic image localisation and reveal a number of important features of localisation relevant to audio system design. Developments will also be described in loudspeaker based systems for binaural reproduction that are finding their way into practical use. Binaural hearing models can be used to provide a preliminary evaluation of the performance of alternative designs. Finally, a brief review will be presented of multi‐channel loudspeaker‐based systems aimed at “full field” sound reproduction. Again, models of localisation provide some useful guidanc...

Trends of the acoustic condition in an intensive care unit based on a long-term measurement

Noise levels in hospitals, especially in intensive care units (ICUs), are often very high, potentially influencing the patients’ well-being and recovery processes, where the undesirable acoustic environment is also considered to be one of the risk factors contributing to ICU delirium. In the current study, a continuous measurement was taken for 3 months in 8 single-bed patient rooms in an ICU, of which the results were analyzed in synchrony with the admission of 106 patients. On average, the A-weighted energy-equivalent sound pressure level (LAeq) in patient rooms varied significantly with the time of day (p < 0.001), but was not dependent on the day of week (p = 0.448). Furthermore, analysis of noise levels in occupied versus unoccupied rooms indicated the dominance of room-internal sources in the former and room-external sources in the latter periods. During the first four days of patients’ ICU stay, the acoustic condition improved slightly from day 1 to day 2, but the noise level rebounded from day 2, ...

An auditory process model for sound localization

An auditory process model for sound localization in the horizontal plane is presented in this paper. Based on equalization-cancellation (EC) theory, the binaural processor produces excitation-inhibition (EI) cell activity patterns at each frequency band, which are, then, combined by the central processor employing simple template-matching method. Gain and delay errors have been introduced at the end of the peripheral process in order to accommodate the imperfection possibly present in human EC process. These parameters have been adjusted to fit the model performance to that of human listeners described in a few published subjective experiments. A certain value of the gain error has been found to give an acceptable model prediction in terms of the mean error and standard deviation.