First of all, thanks for helping us by gathering sound and heart rate data in New York during the 2023 study trip! Your data significantly improves our understanding of the impact of sound on health.

Data insights

The following shows some insights into the data you have collected. It will be updated with more insights during the next couple of weeks - so check in again later! For example, I’ll make sure you can identify your own data in the plots.

If you have any questions, would like your own copy of your data, or even want to do a project with us feel free to write me on .

For reference, you can find more details about the hearing-aid data we log and some insights in the following articles:

“The everyday acoustic environment and its association with human heart rate: evidence from real-world data logging with hearing aids and wearables.” Royal Society open science (2021)

“Real-world hearing aid usage patterns and smartphone connectivity.” Frontiers in Digital Health (2021)

“Application of big data to support evidence-based public health policy decision-making for hearing.” Ear and hearing (2020)

Sound Loudness, Sound Clarity, Stress, and trip information

Check the box for which data you would like to see.

Please note that “Events” are approximated without considering delays we encountered. As you can see, GPS coordinates are not always precise!

Sound and heart rate time-series

The following shows your heart rate and noise floor over time. The noise floor is estimated from the hearing aids by considering the bottom envelope of the fluctuating sound pressure level in 16 frequency bands. It represents how much background noise is present.

How much noise did you accumulate?

The following shows your noise dose in percentage of the daily recommended levels (=100%). Short-term noise exposure with high intensity can cause temporary hearing damage and hearing loss, but exposure to lower noise intensity over time can be equally harmful, albeit, less noticeable.

In the plot, individual noise dose accumulation are shown with black traces, and the group average are shown with the solid magenta line.

There are several interesting insights from the noise dose accumulation. For example, the 100% crossing point are reached very early on day one due to the constant high-level noise experienced in the flight. In addition, the variance (spread of individual traces) seems largest on day 4, which is probably due to the fact that sound exposure and behavior while visiting Coney Island and Luna Park are diverse.

Noise-induced stress

Being in noisy conditions while communicating or listening to something leads to elevated stress. Typically, we measure this by associating the short-term sound pressure (SPL) and signal-to-noise (SNR) levels in decibel with short-term changes in heart rate. On a typical day, around 5-10% of changes in heart rate are caused by changes in the sound condition, represented by SPL and SNR. The general pattern is that higher SPL leads to higher heart rate, while higher SNR leads to lower heart rate.

Here, we apply a linear mixed-effects model to predict heart rate by SPL and SNR in interaction with Date. This is to investigate how much the ambient sound impacted your heart rate and if this differed among the days of the trip. The model also includes random effects intercepts for individuals and for each hour of the day (i.e., to control for inter-individual differences and circadian rhythms in heart rate).

Results are presented as model predictions - i.e, your heart rate as a function of SPL and SNR.

Evidently, heart rate was elevated when the SPL increased to around 45% of it’s maximum and then decreased again. This suggests that the strongest stress reactions were not for the loudest environments but rather for intermediate levels. The reasons for this could be that the loudest environments were associated with noise that did not interfere with communication (e.g., passively listening to loud music or enjoying the view of the Statue of Liberty in loud ferry noise).

For the SNR, the “classic” trend is observed: low SNR (i.e., noisy environments) are related with elevated heart rate, and the better (higher) SNR becomes, the lower the heart rate, which most likely is because communicating and listening require less effort when SNR is high.

More details

You collected data using:

– A commercially available hearing aid (Oticon Opn S)

– A commercially available wearable (Garmin vivosmart 4)

– An iPhone with iOS 14 or higher

Every 20 seconds, the hearing aid sends estimates of the sound environment to the iPhone via Bluetooth while the wearable sends information about the instantaneous heart rate (also via Bluetooth) at each detected heart beat. Your sound-locked heart rate is then estimated as the mean heart rate within the same time interval as the sound-data logs.
The sound environment is divided up in two dimensions: SOund pressure levels (Loudness) and Signal-to-noise levels (Clarity).
Loudness represents the pressure of the sound wave on your ear-drum. SPL is usually measured in decibel (dB), which is a number that indicates how much more pressure you experience from the basic air pressure during complete quiet (SPL = 0 dB). In addition, as the sound wave consists of signals in many different frequencies, the SPL is usually an average across all frequencies we can hear (20 to 20000 Hz). In this analysis, we use “a-weighted SPL” (dBA), which just means that the averaging across frequencies is weighted by a function resembling what the human auditory system does.

Clarity is the difference in loudness (in dBA) between background noise and sound sources - for example a speaker you are trying to listen to. The hearing aid constantly measures the background noise loudness level by classifying if an incoming sound is noise or not (based on machine learning). We can then subtract this noise level from the overall loudness level and derive a value representing the signal-to-noise ratio - that is, how much louder is the interesting sound signal (e.g., speech) compared to the noise.

Lastly, noise-induced “stress” is defined as the change in heart rate cased by an extrinsic factor related to the sound environment. For example, an increase in Loudness is usually followed by a stress reaction represented by an increase in heart rate. Thus, stress can take on positive values (i.e. a stress reaction) or negative values (i.e. a relaxing reaction) depending on the sound you are exposed to (and what you are doing). ```