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Associations between hearing performance
and physiological measures - an overview
and outlook
Lukas H. B. TIETZa,
1
, Panagiotis KATRAKAZASb,
Ariane LAPLANTE-LÉVESQUEa, Niels Henrik PONTOPPIDANa,
Nina KOLOUTSOUc, George SPANOUDAKISd
and Dimitrios KOUTSOURISb
a Eriksholm Research Centre, Oticon, Snekkersten, Denmark
b Biomedical Engineering Laboratory, National Technical University of Athens, Greece
c Guys and St. Thomas’ NHS Foundation Trust, London, United Kingdom
d The City University, London, United Kingdom
Abstract. The current paper summarises the research investigating associations
between physiological data and hearing performance. An overview of state-of-the-
art research and literature is given as well as promising directions for associations
between physiological data and data regarding hearing loss and hearing
performance. The physiological parameters included in this paper are: electrodermal
activity, heart rate variability, blood pressure, blood oxygenation and respiratory
rate. Furthermore, the environmental and behavioural measurements of physical
activity and body mass index, alcohol consumption and smoking have been
included. So far, only electrodermal activity and heart rate variability are
physiological signals simultaneously associated with hearing loss or hearing
performance. Initial findings suggest blood pressure and respiratory rate to be the
most promising physiological measures that relate to hearing loss and hearing
performance.
Keywords. hearing loss, hearing performance, sensors, wearables, physiological
measures
Introduction
One of the fastest growing markets of this decade is that of the wearable healthcare
devices (i.e. smartwatches and wristbands) [1]. Given the amount of data that such
devices record, they make possible the collection of large heterogeneous datasets that
combine data from wearables with observations and monitoring of people with a known
health-related condition, e.g. hearing loss (HL). These data can help shape evidence-
informed public health policies, which require data provided by and for technological,
clinical, legislative and political actors.
The EVOTION project (http://h2020evotion.eu) funded under the Horizon 2020
programme of the European Union uses data collected from hearing aids (HA) and
sensors included in a wearable (smartwatch) to assist in the formulation of evidence-
1
Lukas H. B. Tielz, Eriksholm Research Centre, Oticon, Snekkersten, Denmark, e -mail:
luti@eriksholm.com
informed public health decision models in HL related policy making.
To do so, it is crucial to establish a basis for associations between existing sensor
technology, as they are included in wearables, and HL and hearing performance (HP).
Therefore, for the first part we considered sensors measuring physiological data, namely
skin conductance -also known as electrodermal activity (EA)-, heart rate variability
(HRV), respiratory rate (RR), oxygen saturation levels (SpO2) and blood pressure (BP).
The hearing measures part includes the severity of HL and HP, such as speech
understanding or listening effort.
1. State-of-the-Art Analysis
Published research has so far focused on relating HL and two physiological parameters:
EA and HRV. Summarising the literature published over the last 5 years (2012-2017),
we have grouped the reviewed publications that measure associations with the
physiological parameter they have researched, as shown in Table 1.
Table 1. Published research and the physiological parameter correlating with either HL or HP.
Physiological Measurement
Related Studies
Electrodermal Activity
[2], [3]
Heart Rate Variability
[3], [4]
Blood pressure
[4], [5]
Blood Oxygenation
None
Respiratory Rate
[3]
Environmental/Behavioural Relations
Related Studies
Smoking
[6],[7],[8],[9]
Physical Activity
[9],[10],[11],[12]
Body Mass Index (BMI)
[8],[9],[11],[12]
Alcohol consumption
[7],[13]
Below we present the results outlined by reviewing the aforementioned studies:
1.1. Electrodermal Activity
EA can be used as a measure of the stress that a person experiences. A change in the
impedance of the skin, due to altering transpiration, is measured and used to determine
the electrodermal activity. Speech recognition tests have been conducted: listeners were
asked to rate the difficulty of understanding speech samples masked in noise in varying
signal-to-noise ratios. During these subjective listening effort tests, skin conductance was
measured. EA was then associated with increased listening effort (HP). [2,3] The results
showed an increased EA for higher effort, displaying a higher stress level in harder
listening situations.
1.2. Heart Rate Variability
Like EA, HRV is a measure of the stress that a person experiences. [3 and 7] found HRV
to be associated with HP. In subjective listening effort tests (described in 1.1.), this stress
parameter has been measured simultaneously. With increasing difficulty, the HRV was
decreasing, signalling higher stress levels. [3] Furthermore, people who experienced a
sudden HL showed a lower HRV during night time measurements. [4]
1.3. Blood Pressure
BP is associated with HL. However, the conducted studies [4,5] were carried out through
a longitudinal design. They found that higher BP is associated with a higher risk of
experiencing a HL later in life [4]. Furthermore, people exposed to noise in the workplace
have reportedly higher BP. [5]
1.4. Respiratory Rate and Blood Oxygenation
The literature currently published does not show any associations between other
biosignals (RR and SpO2) and HL nor HP. No studies investigate the relationship
between SpO2 and HL nor HP. In [3] RR was not associated with HL nor HP.
1.5. Environmental and Behavioural Associations
Environmental parameters, such as BP, have been investigated longitudinally for their
association with HL and HP.
The amount of smoking was in [6-8] associated with severity of HL. Physical
activity seems to prevent or delay HL. [10,11] Findings also suggest that a higher BMI
increase the chance of HL for women [11], whereas men seem less affected. [9]
Conversely, [10,12] found that HL can lead to decreased physical activity and less
healthy lifestyle in older citizens. In [13] the type of consumed alcoholic beverages was
associated with a risk of HL. Women, who reportedly consumed beer had a statistically
higher chance of suffering a HL. Whereas, those drinking a moderate amount of wine,
had a significantly lower chance.
2. Discussion
The link between HL/HP and environmental and behavioural factors have been studied
far more than with physiological measures. The development of wearable technology
supports the research conducted in the HL/HP field, as more parameters can be measured
with every new smart device. The selected parameters reflect the parasympathetic and
sympathetic nervous system and can therefore be directly correlated to HL; as shown in
the reviewed studies, the human body reacts to the increased difficulty of understanding
things due to HL. Existing, commercially available devices form a solid base on which
researchers can build on, along with an increase in the variety of physiological
parameters that can be measured over the past years. Research-focused wearables are
also being introduced to the market at a steady rate, making data collections from these
wearables and their related software more accessible to researchers.
So far, only two parameters have been correlated with HL/HR: HRV and EA. Both
have been linked to stress and listening effort. Research has yet to discover the
correlations and physiological responses and HP. The first five listed parameters (EA,
HRV, RR, SpO2 and BP) can be measured with a good time resolution and associated
with HP, as measurements can be carried out simultaneously to listening tests.
The increased stress levels can be transferred into the real world, in stating that
people experiencing hearing difficulties as a result of a HL suffer more stress symptoms.
Environmental relations are important to see trends, but they require longitudinal
studies to uncover associations with HL.
3. Conclusion
As our results indicate, the field of research investigating associations between hearing
and physiological parameters is currently immature. Based on the state-of-the-art
research, mainly stress indicators, like RR, EA and BP, should be favoured as parameters
to be tested and correlated with hearing measures, e.g. listening effort. A special interest
should be given to BP, as this parameter has already been proven to be correlated with
HL in longitudinal studies.
A better understanding of associations between hearing and physiological
parameters will help policy-makers find right solutions that protect and support those in
need. Enabling better continuous access to heterogeneous data sets, thus allowing better
and more information bestowed upon researchers, policymakers, and other actors
involved in policymaking, is paramount.
Acknowledgement
This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 727521.
References
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