Sound-level Monitoring Earphones With Smartphone Feedback as an Intervention to Promote Healthy Listening Behaviors in Young Adults

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Megan Knoetze ◽  
Faheema Mahomed-Asmail ◽  
Vinaya Manchaiah ◽  
De Wet Swanepoel
Keyword(s):  
Young Adults ◽  
Sound Level ◽  
Listening Behaviors ◽  
Level Monitoring

Health promotion challenges for young adults living with intellectual disability and type 1 diabetes

2021 ◽  
pp. 174462952110327
Author(s):  
Anne L Marks ◽  
Natasha Mahoney ◽  
Yu-Wei Chen ◽  
Reinie Cordier ◽  
Angus Buchanan ◽  
...  
Keyword(s):  
Health Promotion ◽  
Type 1 Diabetes ◽  
Young Adults ◽  
Intellectual Disability ◽  
Barriers And Facilitators ◽  
Self Management ◽  
Service Support ◽  
Health Support ◽  
Level Monitoring

Background: Self-management of type 1 diabetes mellitus (T1DM) can be challenging for people with intellectual disability. Often, parents provide health support due to lack of appropriate services outside the home. The study aim was to identify barriers and facilitators to T1DM self-management for young adults with intellectual disability and the implications for health promotion. Methods: Five male participants with intellectual disability, aged 17–26 years, and seven parents were interviewed between October 2017 and February 2019. Interview data were descriptively analysed. Findings: Two categories for barriers and facilitators were identified: 1) Diabetes self-management is complex (carbohydrate counting, blood glucose level monitoring, insulin therapy); 2) support for diabetes care (reliance on parents and carers, the National Disability Insurance Scheme, mainstream diabetes service support). Conclusions: Parents are critical for the support of people with intellectual disability and T1DM in the absence of disability staff with appropriate health skills.

Relation between Reaction Time and Loudness

1984 ◽  
Vol 27 (2) ◽  
pp. 306-310 ◽  
Author(s):  
Larry E. Humes ◽  
Jayne B. Ahlstrom
Keyword(s):  
Young Adults ◽  
Reaction Time ◽  
Reaction Times ◽  
Growth Function ◽  
Reaction Time Data ◽  
Intensity Function ◽  
Sound Level ◽  
Time Data ◽  
Sound Levels ◽  
Loudness Growth

The loudness of one-third octave bands of noise centered at either 1, 2, or 4 kHz was measured in 10 normal-hearing young adults for sound levels of 50–90 dB SPL. Reaction times (RT) in response to these same stimuli were also measured in the same subjects. A moderate-to-strong correspondence was observed between the slopes for functions depicting the growth of loudness with sound level and comparable slopes for the reaction-time data. The correlation between slopes for the RT-intensity function and the loudness-growth function was comparable in magnitude to the test,retest correlation for the loudness-growth function except at 1 kHz.

Sound level monitoring apparatus

1982 ◽  
Vol 72 (3) ◽  
pp. 1095-1096
Author(s):  
Michael C. Martin ◽  
Ian R. Summers
Keyword(s):  
Sound Level ◽  
Level Monitoring

scholarly journals Missing values reconstruction in sound level monitoring station by means of intelligent computing

2018 ◽  
Vol 157 ◽  
pp. 02042
Author(s):  
Leszek Radziszewski ◽  
Michał Kekez ◽  
Alžbeta Sapietová
Keyword(s):  
Missing Values ◽  
Regression Tree ◽  
Sound Level ◽  
Training Dataset ◽  
Intelligent Computing ◽  
Sound Levels ◽  
Level Data ◽  
Short Period ◽  
Computational Intelligence Methods ◽  
Level Monitoring

The aim of the paper was to reconstruct the missing data by applying the model which describes variability of sound level in the whole period from 2013 to 2016. To build the model, the computational intelligence methods, like fuzzy systems, or regression trees can be used. The latter approach was applied and we built the model with Cubist regression tree software, using equivalent sound levels recorded in 2013. For the reconstruction of sound level data in short period of time (several days), time series values and day_of_week values together should be used in the training dataset. For the reconstruction of sound level data in long period of time (several months) day_of_week values should be used in the training dataset.

Applicability of MEMS microphones for environmental sound level monitoring

2021 ◽  
Vol 263 (6) ◽  
pp. 875-885
Author(s):  
James Oatley ◽  
Craig Storey
Keyword(s):  
Integration Method ◽  
Sound Level ◽  
Monitoring Systems ◽  
Environmental Sound ◽  
Sound Localisation ◽  
Type Approval ◽  
Mems Microphone ◽  
Mems Technology ◽  
Mems Microphones ◽  
Level Monitoring

This paper explores the challenges associated with the integration of MEMS microphone technology into IEC 61672 classified or type-approved environmental sound level monitors. A comparison is drawn between MEMS microphones and electret condenser capsule microphones to highlight key performance differences within the technologies, and a basic integration method for both technologies is suggested. A review of the IEC 61672 and type-approval standards is conducted against the suggested integration method for a MEMS microphone; key shortcomings are reported and objectively reviewed. Development trends for MEMS microphones are explored, providing key insights into the progression of the technology against electret condenser capsule microphones. Furthermore, the evolution of environmental sound level monitoring systems is explored with a key focus on networked and sound localisation technology. The importance of MEMS microphones within the evolution of environmental sound level monitoring systems is presented alongside key arguments for the practical suitability of MEMS technology over electret condenser capsule technology.

scholarly journals Sound Level Monitoring at Live Events, Part 1–Live Dynamic Range

2021 ◽  
Vol 69 (11) ◽  
pp. 782-792
Author(s):  
Adam J. Hill ◽  
Johannes Mulder ◽  
Jon Burton ◽  
Marcel Kok ◽  
Michael Lawrence
Keyword(s):  
Dynamic Range ◽  
Sound Level ◽  
Level Monitoring
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