First of all, thank you for helping us by gathering sound and heart rate data in New York during the 2022 study trip! Your data significantly improves our understanding of the impact of sound health.
The following shows some insights into the data you have collected. If you have any questions or would like your own copy of your data, feel free to write me on jych@eriksholm.com.
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 from -5 seconds to +5 seconds centered on each
sample of the sound environment.
The sound environment is divided
up in two dimensions: Loudness and Clarity.
Loudness is also known
as sound pressure level (SPL) and 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 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, sound-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).
We can therefore simply count the number of data logs to learn how many hours of data gathering (i.e. logging) you have performed. The figure below shows how this is distributed over the days during the trip with colors to indicate which Team the data came from. Note, the heart rate data is normalized so that the numbers indicate a %-change from your individual mean heart rate across the whole trip.
On average, you collected more than 16 hours of data per hour across the four days. If all of you had full connectivity this number would have been 24. But considering the “real world” nature of the data collection it is still impressive that close to 70% of the maximum available data were collected across four full days!
Next, we look at the noise dose you accumulated each day of the trip.
Being in loud sound environments for longer periods of time increase the
total noise dose you are exposed to. The noise dose is calculated as the
accumulated noise in relation to a 8 hour working day. This means that
100% is the recommended maximum to avoid occupational health effects
from noise. For example, the limit of 100% is reached in 4 hours if you
are exposed to 88 dBA noise and in only 1 hour if the noise is constant
94 dBA.
The average noise accumulation represents the joint exposure across
all Audio Explorers. Shared events (for example our dinners) therefore
contributes more to the accumulation than individual noisy events (some
of you might have been in more noisy environments during free time than
others). Nevertheless, the noise dose and the stress levels (color from
green to red) represent expected levels when visiting New York and
participating in the Audio Explorers study trip!
We can also look
at the contribution to the shared noise dose from each team
individually. This is shown in the bottom plot. When the accumulation
seems to drop, this indicate that one or more team members stopped
gathering data (maybe due to connectivity issues).
Evidently, the most noisy and stressing day was on Day 3. This makes sense since this was the day we went to the amusement park at Coney Island and enjoyed a Drag Queen show starting around 18:00.
We can also inspect how the sounds you experienced in New York were located (and also track where you went). Zoom in and see what sound you logged where you went. Note: to reduce the amount of GPS noise each dot represents the mean (lon, lat) coordinate across 1 minute corresponding to 3 GPS samples.
Check the box for which data you would like to see.