scholarly journals The everyday acoustic environment and its association with human heart rate: evidence from real-world data logging with hearing aids and wearables

2021 ◽  
Vol 8 (2) ◽  
pp. 201345
Author(s):  
Jeppe H. Christensen ◽  
Gabrielle H. Saunders ◽  
Michael Porsbo ◽  
Niels H. Pontoppidan
Keyword(s):  
Heart Rate ◽  
Hearing Aids ◽  
Real World ◽  
Data Logging ◽  
Short Term ◽  
Real World Data ◽  
Acoustic Characteristics ◽  
World Data ◽  
Ambient Sound ◽  
Mean Heart Rate

We investigate the short-term association between multidimensional acoustic characteristics of everyday ambient sound and continuous mean heart rate. We used in-market data from hearing aid users who logged ambient acoustics via smartphone-connected hearing aids and continuous mean heart rate in 5 min intervals from their own wearables. We find that acoustic characteristics explain approximately 4% of the fluctuation in mean heart rate throughout the day. Specifically, increases in ambient sound pressure intensity are significantly related to increases in mean heart rate, corroborating prior laboratory and short-term real-world data. In addition, increases in ambient sound quality—that is, more favourable signal to noise ratios—are associated with decreases in mean heart rate. Our findings document a previously unrecognized mixed influence of everyday sounds on cardiovascular stress, and that the relationship is more complex than is seen from an examination of sound intensity alone. Thus, our findings highlight the relevance of ambient environmental sound in models of human ecophysiology.

scholarly journals The everyday acoustic environment and its association with human heart rate: evidence from real-world data logging with hearing aids and wearables

2020 ◽  
Author(s):  
Jeppe H. Christensen ◽  
Gabrielle H. Saunders ◽  
Michael Porsbo ◽  
Niels H. Pontoppidan
Keyword(s):  
Heart Rate ◽  
Hearing Aids ◽  
Real World ◽  
Data Logging ◽  
Environmental Sound ◽  
Real World Data ◽  
Heart Rates ◽  
World Data ◽  
Ambient Sound ◽  
Mean Heart Rate

AbstractWe investigate the longitudinal association between multidimensional characteristics of everyday ambient sound and continuous mean heart rate. We used in-market data from hearing aid users who logged ambient acoustics via smartphone-connected hearing aids and continuous heart rate from their own wearables.We find that ambient acoustic characteristics explain approximately 4% of the fluctuation in mean heart rate throughout the day. Specifically, increases in ambient sound pressure intensity are significantly related to increases in mean heart rates, corroborating prior laboratory and short-term real-world data. In addition, however, and not previously recognized, increases in the ambient sound quality - that is, the difference between sound signal and noise - are associated with decreases in mean heart rates.Our findings document a mixed influence of everyday sounds on cardiovascular stress, and that the relationship is more complex than is seen from examination of sound intensity alone. Thus, our findings highlight the relevance of ambient environmental sound in models of human ecophysiology.

Recent Advances in Short-term Wind Power Forecasting:Modeling Methods and Real-world Data

2019 ◽  
Author(s):  
Haijian Shao ◽  
Xing Deng ◽  
Yaming Ren ◽  
Xia Wang ◽  
Lu Zhang
Keyword(s):  
Wind Power ◽  
Real World ◽  
Short Term ◽  
Real World Data ◽  
World Data ◽  
Recent Advances

Short-term effectiveness and safety of tofacitinib in ulcerative colitis - real world data from tertiary medical centers in Israel

2021 ◽  
Author(s):  
Irit Avni-Biron ◽  
Ariella Bar-Gil Shitrit ◽  
Benjamin Koslowsky ◽  
Asaf Levartovsky ◽  
Uri Kopylov ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Real World ◽  
Short Term ◽  
Real World Data ◽  
World Data ◽  
Medical Centers

scholarly journals Clustering Users Based on Hearing Aid Use: An Exploratory Analysis of Real-World Data

2021 ◽  
Vol 3 ◽  
Author(s):  
Alessandro Pasta ◽  
Tiberiu-Ioan Szatmari ◽  
Jeppe Høy Christensen ◽  
Kasper Juul Jensen ◽  
Niels Henrik Pontoppidan ◽  
...  
Keyword(s):  
Hearing Aids ◽  
Real World ◽  
Hearing Aid ◽  
Objective Data ◽  
Data Logging ◽  
Real World Data ◽  
Hearing Aid Use ◽  
User Clustering ◽  
Usage Patterns ◽  
Typical Day

While the assessment of hearing aid use has traditionally relied on subjective self-reported measures, smartphone-connected hearing aids enable objective data logging from a large number of users. Objective data logging allows to overcome the inaccuracy of self-reported measures. Moreover, data logging enables assessing hearing aid use with a greater temporal resolution and longitudinally, making it possible to investigate hourly patterns of use and to account for the day-to-day variability. This study aims to explore patterns of hearing aid use throughout the day and assess whether clusters of users with similar use patterns can be identified. We did so by analyzing objective hearing aid use data logged from 15,905 real-world users over a 4-month period. Firstly, we investigated the daily amount of hearing aid use and its within-user and between-user variability. We found that users, on average, used the hearing aids for 10.01 h/day, exhibiting a substantial between-user (SD = 2.76 h) and within-user (SD = 3.88 h) variability. Secondly, we examined hearing aid use hourly patterns by clustering 453,612 logged days into typical days of hearing aid use. We identified three typical days of hearing aid use: full day (44% of days), afternoon (27%), and sporadic evening (26%) day of hearing aid use. Thirdly, we explored the usage patterns of the hearing aid users by clustering the users based on the proportion of time spent in each of the typical days of hearing aid use. We found three distinct user groups, each characterized by a predominant (i.e., experienced ~60% of the time) typical day of hearing aid use. Notably, the largest user group (49%) of users predominantly had full days of hearing aid use. Finally, we validated the user clustering by training a supervised classification ensemble to predict the cluster to which each user belonged. The high accuracy achieved by the supervised classifier ensemble (~86%) indicated valid user clustering and showed that such a classifier can be successfully used to group new hearing aid users in the future. This study provides a deeper insight into the adoption of hearing care treatments and paves the way for more personalized solutions.

Hearing Aids in the Real World: Typical Automatic Behavior of Expansion, Directionality, and Noise Management

2011 ◽  
Vol 22 (01) ◽  
pp. 034-048 ◽  
Author(s):  
Shilpi Banerjee
Keyword(s):  
Hearing Aids ◽  
Real World ◽  
Hearing Aid ◽  
Published Data ◽  
Data Logging ◽  
High Input ◽  
Real World Data ◽  
The Real ◽  
Input Level ◽  
Noise Management

Background: Automatic DSP (digital signal processing) features, widely available in hearing aids today, are useful because they alleviate the need for the hearing aid wearer to manually adjust the hearing aid as listening conditions change. Although the theoretical basis for the design of these features may be sound, little is known about their behavior in the real world. Data logging offers a glimpse into the life of the individual hearing aid wearer, but there are no published data to date that provide a frame of reference for the interpretation of this information. Further, data logging in hearing aids provides only aggregate summaries for individual features, ignoring complex interactions including the differences between the left and right sides of a bilateral pair. Purpose: The purpose of this study was to determine the typical behavior of three automatic DSP hearing aid features—expansion, directionality, and noise management—in daily life. Data Collection and Analysis: Ten individuals with hearing impairment were fitted bilaterally with BTE (behind the ear) hearing aids. The hearing aids were programmed for the individual's hearing loss with expansion, directionality, and noise management set to activate automatically. A PDA (personal digital assistant) logged the input level and status of expansion, directionality, and noise management from both devices at 5 sec intervals. Data were gathered in this manner over a period of 4–5 wk. Results: A total of 741 hr of hearing aid use were logged, 50% of which were spent in environments no louder than 50 dB SPL. Expansion, directionality, and noise management were active 45, 10, and 21% of the time, respectively; the median amount of gain reduction for noise management was ˜1 dB. Although expansion and noise management were always active at the low and high input levels, respectively, activation of directionality never exceeded 50%. Expansion and noise management were sometimes active simultaneously, as were directionality and noise management. Bilateral agreement in feature activation typically exceeded 80%, except when the input level was at the cusp of a threshold for activation of a specific feature and at high input levels.

Abstract #946: Assessment of Acromegaly Patients with and Without Diabetes Treated with Lanreotide Depot: 2-Year Real World Data

2016 ◽  
Vol 22 ◽  
pp. 219
Author(s):  
Roberto Salvatori ◽  
Olga Gambetti ◽  
Whitney Woodmansee ◽  
David Cox ◽  
Beloo Mirakhur ◽  
...  
Keyword(s):  
Real World ◽  
Real World Data ◽  
World Data
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