FIELD OF THE INVENTION
[0001] The invention relates to a hierarchical control system with a hearing system including
a hearing device. The invention further relates to a method, a computer program and
a computer readable medium for controlling the hearing system.
BACKGROUND OF THE INVENTION
[0002] Hearing devices are generally small and complex devices. Hearing devices can include
a processor, microphone, speaker, memory, housing, and other electronical and mechanical
components. Some example hearing devices are Behind-The-Ear (BTE), Receiver-In-Canal
(RIC), In-The-Ear (ITE), Completely-In-Canal (CIC), and Invisible-In-The-Canal (IIC)
devices. A user can prefer one of these hearing devices compared to another device
based on hearing loss, aesthetic preferences, lifestyle needs, and budget.
[0003] Today's hearing devices mainly work based on the settings that the user receives
from user's audiologist or hearing care professional (HCP). Such first settings have
typically to be optimized at least during an initial period, where the hearing device
is worn.
[0004] There are several ways to improve this configuration such as follow up fittings with
the HCP or by the user who can adjust settings either at the hearing device directly
or e. g. based on apps running on a smartphone.
[0005] Furthermore, some hearing devices are configured for automatic adjustments. In case
of automatic adjustments based on sensors or user feedbacks, the user just gets adjusted
settings for the hearing devices without interactions with the user. Thus, the user
may not be aware of what has caused the change, may not even perceive any change and
cannot control this change. The user thus can also not reject the change when he would
prefer the previous setting.
DESCRIPTION OF THE INVENTION
[0006] It is an objective of the invention to provide a hearing system which provides an
improved user experience. It is a further objective to provide an enhanced safety
for the user.
[0007] These objectives are achieved by the subject-matter of the independent claim. Further
exemplary embodiments are evident from the dependent claims and the following description.
[0008] A first aspect of the invention relates to a hierarchical control system with a hearing
system including a hearing device, the control system implementing at least two control
levels. The control system comprises at least one control unit and assigned to the
control levels. Each control unit may be assigned to one of the control levels. Such
control units may be parts of the hearing device, a user device, such as a smartphones
and/or further computing devices communicatively connected with the hearing system.
There also may be control entities assigned to the control levels, such as the hearing
device, the user, an HCP, etc.
[0009] The hearing system includes a memory storing instructions, and a processor communicatively
coupled to the memory and configured to execute at least parts of the control system.
[0010] The control system and in particular the hearing system is further configured to
execute the following instructions: determining and monitoring a hearing situation
of a user of the hearing system based on a status of the hearing system and user related
data, for example stored in the memory; and determining, based on the hearing situation
of the user, an updated hearing device setting. The updated hearing device setting
also may be associated with one of the at least two control levels.
[0011] The hearing device according to the present invention may be in particular one of
Behind-The-Ear (BTE), Receiver-In-Canal (RIC), In-The-Ear (ITE), Completely-In-Canal
(CIC), and Invisible-In-The-Canal (IIC) devices. Such a hearing device typically comprises
a housing, a microphone or sound detector, and an output device including e.g. a speaker
(also "receiver") for delivering an acoustic signal, i.e. sound into an ear canal
of a user. The output device can also be configured, alternatively or in addition,
to deliver other types of signals to the user which are representative of audio content
and which are suited to evoke a hearing sensation. The output device can in particular
be configured to deliver an electric signal for driving an implanted electrode for
directly stimulating hearing receptors of the user as it is e.g. the case in a cochlea-implant.
Output devices of other types of hearing devices are configured to transmit an acoustic
signal directly via bone conduction as it is e.g. the case with so called BAHA devices
(Bone Anchored Hearing Aid - BAHA) which transmit the acoustic signal via a pin implanted
into the skull of a user. The hearing device may comprise a processor and a memory.
The hearing device may further include other electronical and mechanical components,
like an input unit or a transmitter and/or one or more sensors.
[0012] The hearing system may further include a mobile device being a user device, for example
a smart phone or other connectable device, which can be connected to the hearing device
over a network or by a direct, in particular wireless, connection. In such a case,
sensors included in the mobile device may be used to collect sensor data to be send
to one or more processors of the hearing system.
[0013] The hearing system is configured to determine and monitor a hearing situation of
the user. A hearing situation of the user is to be understood to include factors,
which change the personal hearing experience of the user such as acoustic of the environment,
background and foreground noise and sound as well as medical conditions of the user.
The hearing system may take into account measurements from one or more sensors to
determine the hearing status.
[0014] A processor for determining, based on the hearing situation of the user, an updated
hearing device setting, may be a processor internal to the hearing device or a processor
of a connected device or a connected network e.g. accessible through internet. The
updated hearing device setting may be obtained from a database of available hearing
device settings or can be procedurally generated at runtime based e.g. on the current
hearing situation and user preferences. The control system may comprise such a database.
For example, based on the hearing situation of the user, an updated hearing device
setting may be selected from a database of available hearing device settings, each
available hearing device setting being associated with one of the at least two control
levels. The hearing device settings may include settings for a single parameter as
e.g. volume, or settings for a set of several parameters, like filter settings, loudness,
balances, etc.
[0015] The available hearing device settings stored in the database may include a control
level associated with the respective hearing device setting in which case the step
of associating the updated hearing device setting with a control level simply requires
obtaining and utilizing the corresponding information of the database. In case the
updated hearing device setting is generated at runtime, the step of associating the
updated hearing device setting with a control level may include e.g. associating the
control level procedurally according to a predefined set of rules or may include obtaining
an associated control level e.g. from a lookup table in which control levels are assigned
to certain hearing device settings.
[0016] The control system and/or the hearing system may implement one or more machine learning
algorithms, like a trained neuronal network, which perform the determination and monitoring
of the hearing situation and/or the selection of the updated hearing device setting.
The algorithm may be executed in the hearing device, in a user or mobile device such
as user's smartphone or in the cloud i.e. on one or several remote server or a combination
thereof, i.e. by the control system.
[0017] The database may be provided only for one user or may be provided for several users
with several hearing devices. Such a database may comprise hearing device settings
and their changes for a plurality of users. The device settings may be stored in the
database, together with information, in which hearing situation the settings should
be applied and for which users, in particular depending on user profiles and medical
conditions like the hearing loss type, the amount of hearing loss, i.e. the user related
data.
[0018] The control system is further configured to generate a query message for approval
of the updated hearing device setting and sending the query message to the control
unit assigned to the control level associated with the updated hearing device setting.
In such a way, the control unit and/or the associated control entity assigned to the
control level associated with the updated hearing device setting may be queried for
approval of the updated hearing device setting.
[0019] The control system is further configured to receive a feedback message in response
to the query message from the control unit and, if the feedback messages contains
an approval of the updated hearing device setting, applying the updated hearing device
setting to the hearing device. The control unit may automatically decide, whether
to approve the update or not. It is also possible that information about the update
is presented to a control entity, for example, via a user interface, which then approves
the update via the user interface. In any case, the control unit generates the feedback
messages, which contains information, whether the update is approved or not.
[0020] Upon approval by the control unit and optionally control entity, the hearing system
is allowed to apply the updated hearing device setting.
[0021] The control system is further configured to generate a notification message about
the application of the updated hearing device setting, if the hierarchical control
system comprises a next higher control level. The notification message is sent to
the control unit assigned to the next higher control level. Subsequently at least
the control unit and optionally the control entity assigned to the next higher control
level is notified about the application of the updated hearing device setting, if
the control system comprises a next higher control level. In such a way, the user
can be protected by changes in the hearing device setting, which may be not beneficial,
i.e. may not help the user to compensate his or her hearing loss and/or which may
be dangerous for him. For example, the volume of a hearing device may not be turned
up as high for a user with a mild hearing loss compared to a user with a severe hearing
loss.
[0022] Control entities assigned to a control level can be algorithms, for instance machine
learning algorithms, in particular algorithms implementing an artificial intelligence,
or persons as e.g. a user, a designated caretaker or an HCP. In such a way a control
unit, being a computing device, may be or may comprise a control entity.
[0023] Control entities can also be collective entities as e.g. a manufacturer or a regulating
body. Algorithms particularly may be control entities assigned to the lowest available
control level whereas a regulatory body and/or manufacturer may be the control entity
assigned to the highest available control level.
[0024] There may be several hierarchically ordered control levels with different assigned
control entities. "Hierarchical ordering" herein refers to a well-defined ordering
of the control levels such that each control level - besides a highest control level
- has exactly one next higher control level. The hierarchical ordering can be defined
by an authorization that is required to apply a setting associated with the respective
control level. Typically, higher control levels are authorized to apply settings of
a lower control level whereas lower control levels are not authorized to apply settings
associated with a higher control level. For instance, a user may be authorized to
apply personalized settings of the hearing device whereas the HCP may be authorized
to change personalized settings as well as fitting parameters related to the hearing
loss of the user (which the user is not authorized to change). The regulatory body
or manufacturer may e.g. be authorized to change hearing device related properties
as e.g. a maximum allowable or achievable gain which the HCP is not authorized to
change.
[0025] If a certain control level does not have sufficient authority to apply specific settings,
such settings may be proposed to a control entity assigned to a higher control level
which can approve and apply such settings by way of its higher authority.
[0026] For safety reasons, the control level associated with a particular setting for one
or more parameters may be related to the required deviation from the actual settings
in some embodiments. For example, the volume may be increased solely within a specific
margin by the user, but within a wider margin by the HCP, etc. The same may apply
to other parameters. As such, the control level assigned to a particular setting may
be determined at runtime, based on the required deviation from the actual settings.
The associated control level can be procedurally determined or can be read e.g. from
a lookup table stored in the control system. This enhances the safety of the hearing
device by avoiding to increase a hearing loss of the user by harmful settings or settings
that may be harmful due to too big or sudden a change. Furthermore, when the selection
of the settings is done automatically by a control unit, the control unit and/or control
entity of the next higher control level receives a corresponding notification and
may check, whether the applied selection is beneficial. Alternatively, the selection
of setting can be proposed to the control unit and/or control entity of the next higher
control level and may be approved by this control unit and/or control entity.
[0027] The machine learning algorithm may be trained as to which settings to propose or
to apply in a given hearing situation and/or for a given condition of the user. The
machine learning algorithm may be trained with historical data of the user of the
hearing device and/or with data from a plurality of users obtained via a data sharing
network. For example, the machine learning algorithm may be trained to propose a specific
setting with a higher probability when the respective setting is satisfactory for
a lot of users in the same or a comparable hearing situations.
[0028] New hearing device settings, which may be made by the user or the HCP, etc. can be
included into the database and/or optional additional database and the machine learning
algorithm can evaluate, whether these settings are satisfactory in specific situations
or not. The new settings also can be included into the training process of the machine
learning algorithm.
[0029] The improvements of the hearing device settings can either be audiological improvements
or usability improvements.
[0030] Audiological improvements may comprise preferences of user in specific environments
based on sensor measurements (microphone, accelerometer, GPS location, biometry sensors,
...), for example when working, travelling, listen to music , doing sports.
[0031] Usability improvements may comprise: e.g. adapting /changing timing of user interactions
(responsivity, etc.) based on an user interaction history (e.g., many corrective adjustments)
and/or emotion/health (e.g., shaking/trembling) measured by a biometry sensor.
[0032] According to an embodiment the control system a control unit is associated with a
control entity. Thus, there may be for example a first lower-level control unit associated
with or included in the hearing device and associated with the hearing device. There
may be a second, next higher level control unit, which may be implemented in the user
device and which may be associated with the user as control entity. One or more of
the control units may implement an algorithm, in particular a machine learning algorithm,
which provides the functionality of a control entity, i.e. for example is configured
to approve updates of hearing device settings and to generate feedback messages.
[0033] The user may receive a notification with a suggestion for new possible settings for
the hearing device based on the machine learning algorithm and sensor measurement.
The user feedbacks, whether he applies the new setting(s) and whether also keeps them
on the long run will then be used as well to improve future recommendation(s). This
information may be included into the training of the machine learning algorithm.
[0034] It is possible that information in a feedback message and/or a notification message
is provided to the user by a user interface, either on an app, or directly by the
hearing device (e.g. as a voice message) or by a user device resp. mobile device.
The information may be displayed on the user device.
[0035] According to an embodiment, the control system includes at least three control levels,
such as three control levels or four control levels.
[0036] A control unit assigned to a lowest, first control level may be associated with the
hearing device, and/or a control unit assigned to a next higher, second control level
may be associated with a user of the hearing system, and/or a control unit assigned
to a next higher, third control level may be associated with an HCP or a caretaker,
and/or a control unit assigned to a next higher, fourth control level may be associated
with a regulatory body or a manufacturer.
[0037] The HCP may get notified as well about the recommended and/or accepted changes of
the hearing device settings by the corresponding control unit being a computing device
in his or her office. The notification can be sent to the HCP, in particular to a
device, e.g. computer device, of the HCP as message whenever the user gets this information.
Alternatively, the message is stored and the HCP is notified when the user is the
next time at the HCP office, thus e.g. when the hearing device is connected to a device
of the HCP.
[0038] According to an embodiment, the control system and in particular the control units
include digital interfaces for presenting information to and receiving information
from one or more of the control entities. The control units may also be communicatively
coupled to user interfaces for presenting information to and receiving information
from one or more of the control entities. The query message, the feedback message
and/or the notification message may be data structured exchanged between computing
devices (such as the control units) via their interfaces. These messages also may
contain information to be provided to a person via a user interface as e.g. a text
message or a voice message. The user interface may comprise a display screen or an
electroacoustic transducer in the form of a speaker for communicating visual or acoustic
information, respectively, to the user which is provided or triggered by the message.
The display screen may be a touchscreen for receiving a user input. The user interface
may also comprise other input means for receiving a user input as e.g. a button, a
separate touch sensing area (i.e. a touch pad) or an electroacoustic transducer in
the form of a microphone for acoustic input.
[0039] In particular, the information may be displayed on a screen of the user device or
on a device of the HCP or other control entity.
[0040] According to an embodiment, the status of the hearing system is based on sensor data
acquired by the hearing system. For example, the status of the hearing system includes
a motion status and/or a temperature.
[0041] According to an embodiment, the hearing situation is determined and monitored by
classifying sensor data acquired by the hearing system and optional the user related
data, which is stored in the hearing system, in particular the hearing device. As
an example, the audio data acquired by the hearing device may be classified to determine,
what kind of sounds the user is hearing in the moment. Such hearing situations may
distinguish between speech and music. As a further example, motion data or position
data may be classified, whether the user is walking, riding or going by car.
[0042] According to an embodiment, the sensor data comprises audio data acquired with a
microphone of the hearing system and the audio data is classified with respect to
different sound situations as hearing situations.
[0043] According to an embodiment, the sensor data comprises position data acquired with
a position sensor of the hearing system and the position data is classified with respect
to different locations and/or movement situations of the user as hearing situations.
[0044] According to an embodiment, the sensor data comprises medical data acquired with
a medical sensor of the hearing system and the medical data is classified with respect
to different medical conditions of the user as hearing situation.
[0045] According to an embodiment, the user related data comprises information on a hearing
loss of the user and/or an audiogram of the user. The user related data also may comprise
settings of a sound processing of the hearing system, in particular, the hearing device.
[0046] According to an embodiment, the hearing situation is classified with a first machine
learning algorithm. The first machine learning algorithm may be executed in the hearing
system, in particular in the hearing device.
[0047] According to an embodiment, the updated hearing device setting is determined with
a second machine learning algorithm. The second machine learning algorithm may be
executed in a control unit associated with one control entity. The classification
of the hearing situation may be sent to the control unit, which then selects the updated
hearing device setting from the database.
[0048] A further aspect of the invention relates to a method for controlling a hearing system
and for improving the settings of a hearing device. The method may be performed by
the control system.
[0049] According to an embodiment, the method comprises: determining and monitoring a hearing
situation of a user of the hearing system based on a status of the hearing system
and user related data stored in the hearing system; and determining, based on the
hearing situation of the user, an updated hearing device setting. For example, based
on the hearing situation of the user, an updated hearing device setting may be selected
from a database of available hearing device settings, each available hearing device
setting being associated with one of the at least two control levels.
[0050] According to an embodiment, the method further comprises: associating the updated
hearing device setting with one of the at least two control levels. The may be done
by the hearing device, by the user device or other control units of the control system.
[0051] According to an embodiment, the method further comprises: generating a query message
for approval of the updated hearing device setting and sending the query message to
the control unit assigned to the control level associated with the updated hearing
device setting, receiving a feedback message in response to the query message from
the control unit and, if the feedback messages contains an approval of the updated
hearing device setting, applying the updated hearing device setting to the hearing
device; and, if the control system comprises a next higher control level, generating
a notification message about the application of the updated hearing device setting
and sending the notification message to the control unit assigned to the next higher
control level.
[0052] A further aspect of the invention relates to a computer program for controlling a
hearing system, which, when being executed by at least one processor, is adapted to
carry out the method such as described above and below. A further aspect of the invention
relates to a computer-readable medium, in which such a computer program is stored.
[0053] For example, the computer program may be executed in a processor of the control system,
hearing system and/or a hearing device, which hearing device, for example, may be
carried by the person behind the ear. The computer-readable medium may be a memory
of this control system, hearing system and/or hearing device. The computer program
also may be executed by a processor of a mobile device, which is part of the hearing
system, and the computer-readable medium may be a memory of the mobile device. It
also may be that steps of the method are performed by the hearing device and other
steps of the method are performed by the mobile device.
[0054] In general, a computer-readable medium may be a floppy disk, a hard disk, an USB
(Universal Serial Bus) storage device, a RAM (Random Access Memory), a ROM (Read Only
Memory), an EPROM (Erasable Programmable Read Only Memory) or a FLASH memory. A computer-readable
medium may also be a data communication network, e.g. the Internet, which allows downloading
a program code. The computer-readable medium may be a non-transitory or transitory
medium.
[0055] It has to be understood that features of the method as described in the above and
in the following may be features of the computer program, the computer-readable medium
and the hearing system as described in the above and in the following, and vice versa.
[0056] These and other aspects of the invention will be apparent from and elucidated with
reference to the embodiments described hereinafter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0057] Below, embodiments of the present invention are described in more detail with reference
to the attached drawings.
Fig. 1 schematically shows a hearing system according to an embodiment of the invention.
Fig. 2 shows a block diagram of components of the hearing system according to figure
1.
Fig. 3 schematically shows a basic shared control loop between a user and at least
one hearing device,
Fig. 4 schematically shows a control system according to an embodiment of the invention.
Fig. 5 schematically shows control units associated with the different control entities.
Fig. 6 schematically shows a shared control topology.
Fig. 7 hierarchical shows a shared control system with four layers.
[0058] The reference symbols used in the drawings, and their meanings, are listed in summary
form in the list of reference symbols. In principle, identical parts are provided
with the same reference symbols in the figures.
DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS
[0059] Fig. 1 schematically shows a hearing system 10 according to an embodiment of the
invention. The hearing system 10 includes a hearing device 12 and a user device 14
connected to the hearing device 12. As an example, the hearing device 12 is formed
as a behind-the-ear device carried by a user (not shown) of the hearing device 12.
It has to be noted that the hearing device 12 is a specific embodiment and that the
method described herein also may be performed with other types of hearing devices,
such as e.g. an in-the-ear device or one or two of the hearing devices 12 mentioned
above. The user device 14 may be a smartphone, a tablet computer, and/or smart glasses.
[0060] The hearing device 12 comprises a part 15 behind the ear and a part 16 to be put
in the ear canal of the user. The part 15 and the part 16 are connected by a tube
18. The part 15 comprises at least one sound detector 20, e.g. a microphone or a microphone
array, a sound output device 22, such as a loudspeaker, and an input mean 24, e.g.
a knob, a button, or a touch-sensitive sensor, e.g. capacitive sensor. The sound detector
20 can detect a sound in the environment of the user and generate an audio signal
indicative of the detected sound. The sound detector 20 may be one of the sensors
for determining the hearing situation. The sound output device 22 can output sound
based on the audio signal modified by the hearing device 12 in accordance with the
hearing device settings, wherein the sound from the sound output device 22 is guided
through the tube 18 to the part 16. The input mean 24 enables an input of the user
into the hearing device 12, e.g. in order to power the hearing device 12 on or off,
and/or for choosing a sound program resp. hearing device settings or any other modification
of the audio signal.
[0061] The user device 14, which may be a Smartphone, a tablet computer, or Smart glasses,
comprises a display 30, e.g. a touch-sensitive display, providing a graphical user
interface 32 including control element 32, e.g. a slider, which may be controlled
via a touch on the display 30. The control element 32 may be referred to as input
means of the user device 14. If the user device 14 are smart glasses, the user device
14 may comprise a knob or button instead of a touch-sensitive display.
[0062] Fig. 2 shows a block diagram of components of the hearing system 10 according to
figure 1.
[0063] The hearing device 12 comprises a first processing unit 40. The first processing
unit 40 is configured to receive the audio signal generated by the sound detector
20. The hearing device 12 may include a sound processing module 42. For instance,
the sound processing module 42 may be implemented as a computer program executed by
the first processing unit 40, which may comprise a CPU for processing the computer
program. Alternatively, the sound processing module 42 may comprise a sound processor
implemented in hardware or more specific a DSP (digital signal processor) for modifying
the audio signal. The sound processing module 42 may be configured to modify, in particular
amplify, dampen and/or delay, the audio signal generated by the sound detector 20,
e.g. some frequencies or frequency ranges of the audio signal depending on parameter
values of parameters, which influence the amplification, the damping and/or, respectively,
the delay, e.g. in correspondence with a current sound program. The parameter may
be one or more of the group of frequency dependent gain, time constant for attack
and release times of compressive gain, time constant for noise canceller, time constant
for dereverberation algorithms, reverberation compensation, frequency dependent reverberation
compensation, mixing ratio of channels, gain compression, gain shape/amplification
scheme. A set of one or more of these parameters and parameter values may correspond
to a predetermined sound program included in hearing device settings.
[0064] In general, a sound program resp. hearing device settings may be defined by parameters
and/or parameter values defining the sound processing of the sound processing module
42, such as the parameters described above. Different sound programs resp. hearing
device settings are then characterized by correspondingly different parameters and
parameter values.
[0065] A sound program resp. hearing device settings furthermore may comprise a list of
sound processing features. The sound processing features may for example be a noise
cancelling algorithm or a beamformer, which strengths can be increased to increase
speech intelligibility but with the cost of more and stronger processing artifacts.
[0066] The sound output device 22 generates sound from the modified audio signal and the
sound is guided through the tube 18 and the in-the-ear part 16 into the ear canal
of the user.
[0067] The hearing device 12 may include a control module 44, being a control unit. For
instance, the control module 44 may be implemented as a computer program executed
by the first processing unit 40. Alternatively, the control module 44 may comprise
a control processor implemented in hardware or more specific a DSP (digital signal
processor). The control module 44 may be configured for adjusting the parameters of
the sound processing module 42, e.g. such that an output volume of the sound signal
is adjusted based on an input volume. For example, the user may select a modifier
(such as bass, treble, noise suppression, dynamic volume, etc.) and levels and/or
values of the modifiers with the input mean 24. From this modifier, an adjustment
command may be created and processed as described above and below. In particular,
processing parameters may be determined based on the adjustment command and based
on this, for example, the frequency dependent gain and the dynamic volume of the sound
processing module 42 may be changed.
[0068] All these functions may be implemented as different sound programs stored in a first
memory 50 of the hearing device 12, which sound programs may be executed by the sound
processing module 42. The first memory 50 may be implemented by any suitable type
of storage medium, in particular a non-transitory computer-readable medium, and can
be configured to maintain, e.g. store, data controlled by the first processing unit
40, in particular data generated, accessed, modified and/or otherwise used by the
first processing unit 40. The first memory 50 may also be configured to store instructions
for operating the hearing device 12 and/or the user device 14 that can be executed
by the first processing unit 40, in particular an algorithm and/or a software that
can be accessed and executed by the first processing unit 40.
[0069] The first memory 50 of the hearing device 12 may be a part of the memory 130 storing
instructions according to the present invention and the first processing unit 40 may
be a processor 132 of a control system 100 (see Fig. 4), which comprises the hearing
system 10. In particular the database 140 may be stored in the first memory 50. In
this case, the hearing system 10 determines and monitors the hearing situation of
the user i.a. by the sound detector 20
[0070] The hearing device 12 may further comprise a first transceiver 52. The first transceiver
52 may be configured for a wireless data communication with a remote server 72, which
may be part of a control system 100 (see Fig. 4) for the hearing system 10. It has
to be noted that the control system 100 also may be implemented completely within
the hearing system 10, i.e. without remote server 72,
[0071] Additionally or alternatively, the first transceiver 52 may be adapted for a wireless
data communication with a second transceiver 64 of the user device 14. The first and/or
the second transceiver 52, 64 each may be e.g. a Bluetooth or RFID radio chip.
[0072] A sound source detector 46 may be implemented in a computer program executed by the
first processing unit 40. The sound source detector 46 is configured to determine
at least the one sound source from the audio signal. In particular, the sound source
detector 46 may be configured to determine a spatial relationship between the hearing
device 12 and the corresponding sound source. The spatial relationship may be given
by a direction and/or a distance from the hearing device 12 to the corresponding audio
source, wherein the audio signal may be a stereo-signal and the direction and/or distance
may be determined by different arrival times of the sound waves from one audio source
at two different sound detectors 20 of the hearing device 12 and/or a second hearing
device 12 worn by the same user.
[0073] A first classifier 48 may be implemented in a computer program executed by the first
processing unit 40. The first classifier 48 can be configured to evaluate the audio
signal generated by the sound detector 20. The first classifier 48 may be configured
to classify the audio signal generated by the sound detector 20 by assigning the audio
signal to a class from a plurality of predetermined classes. The first classifier
48 may be configured to determine a characteristic of the audio signal generated by
the sound detector 20, wherein the audio signal is assigned to the class depending
on the determined characteristic. For instance, the first classifier 48 may be configured
to identify one or more predetermined classification values based on the audio signal
from the sound detector 20. The classification may be based on a statistical evaluation
of the audio signal and/or a machine learning algorithm that has been trained to classify
the ambient sound, e.g. by a training set comprising a huge amount of audio signals
and associated classes of the corresponding acoustic environment. So, the machine
learning algorithm may be trained with several audio signals of acoustic environments,
wherein the corresponding classification is known.
[0074] The first classifier 48 may be configured to identify at least one signal feature
in the audio signal generated by the sound detector 20, wherein the characteristic
determined from the audio signal corresponds to a presence and/or absence of the signal
feature. Exemplary characteristics include, but are not limited to, a mean-squared
signal power, a standard deviation of a signal envelope, a mel-frequency cepstrum
(MFC), a mel-frequency cepstrum coefficient (MFCC), a delta mel-frequency cepstrum
coefficient (delta MFCC), a spectral centroid such as a power spectrum centroid, a
standard deviation of the centroid, a spectral entropy such as a power spectrum entropy,
a zero crossing rate (ZCR), a standard deviation of the ZCR, a broadband envelope
correlation lag and/or peak, and a four-band envelope correlation lag and/or peak.
For example, the first classifier 48 may determine the characteristic from the audio
signal using one or more algorithms that identify and/or use zero crossing rates,
amplitude histograms, auto correlation functions, spectral analysis, amplitude modulation
spectrums, spectral centroids, slopes, roll-offs, auto correlation functions, and/or
the like. In some instances, the characteristic determined from the audio signal is
characteristic of an ambient noise in an environment of the user, e.g. a noise level,
and/or a speech, e.g. a speech level. The first classifier 48 may be configured to
divide the audio signal into a number of segments and to determine the characteristic
from a particular segment, e.g. by extracting at least one signal feature from the
segment. The extracted feature may be processed to assign the audio signal to the
corresponding class.
[0075] The first classifier 48 may be further configured to assign, depending on the determined
characteristic, the audio signal generated by the sound detector 20 to a class of
at least two predetermined classes. The classes may represent a specific content in
the audio signal. For instance, the classes may relate to a speaking activity of the
user and/or another person and/or an acoustic environment of the user. Exemplary classes
include, but are not limited to, low ambient noise, high ambient noise, traffic noise,
music, machine noise, babble noise, public area noise, background noise, speech, nonspeech,
speech in quiet, speech in babble, speech in noise, speech in loud noise, speech from
the user, speech from a significant other, background speech, speech from multiple
sources, calm situation and/or the like. The first classifier 48 may be configured
to evaluate the characteristic relative to a threshold. The classes may comprise a
first class assigned to the audio signal when the characteristic is determined to
be above the threshold, and a second class assigned to the audio signal when the characteristic
is determined to be below the threshold. For example, when the characteristic determined
from the audio signal corresponds to ambient noise, a first class representative of
a high ambient noise may be assigned to the audio signal when the characteristic is
above the threshold, and a second class representative of a low ambient noise may
be assigned to the audio signal when the characteristic is below the threshold. As
another example, when the characteristic determined from the audio signal is characteristic
of a speech, a first class representative of a larger speech content may be assigned
to the audio signal when the characteristic is above the threshold, and a second class
representative of a smaller speech content may be assigned to the audio signal when
the characteristic is below the threshold.
[0076] At least two of the classes can be associated with different sound programs i.e.
hearing device settings, in particular with different sound processing parameters,
which may be applied by the sound processing module 42 for modifying the audio signal.
To this end, the class assigned to the audio signal, which may correspond to a classification
value, may be provided to the control module 44 in order to select the associated
audio processing parameters, in particular the associated sound program, which may
be stored in the first memory 50. The class assigned to the audio signal may thus
be used to determine the sound program, which may be proposed as updated hearing device
settings by the control system 100, in particular depending on the audio signal received
from the sound detector 20.
[0077] The hearing device 12 may further comprise a first transceiver 52. The first transceiver
52 may be configured for a wireless data communication with the remote server 72.
Additionally or alternatively, the first transceiver 52 may be adapted for a wireless
data communication with a second transceiver 64 of the user device 14. The first and/or
the second transceiver 52, 64 each may be e.g. a Bluetooth or RFID radio chip.
[0078] Each of the sound processing module 42, the control module 44, the sound source detector
46, and the first classifier 48 may be embodied in hardware or software, or in a combination
of hardware and software. Further, at least two of the modules 42, 44, 46, 48 may
be consolidated in one single module or may be provided as separate modules. The first
processing unit 40 may be implemented with a single processor or with a plurality
of processors. For instance, the first processing unit 40 may comprise a first processor
in which the sound processing module 42 is implemented, and a second processor in
which the control module 44 and/or the sound source detector 46 and/or the first classifier
48 are implemented. The first processing unit 40 may further comprise the processor
132 for executing the control system 100 as a further processor. Alternatively the
one of first or second processor may be used as processor 132.
[0079] The user device 14, which may be connected to the hearing device 12 for data communication,
may comprise a second processing unit 60 with a second memory 62, and a second transceiver
64.
[0080] The second processing unit 60 may comprise one or more processors, such as CPUs.
If the hearing device 12 is controlled via the user device 14, the second processing
unit 60 of the user device 14 may be seen at least in part as a controller of the
hearing device 12. In other words, according to some embodiments, the first processing
unit 40 of the hearing device 12 and the second processing unit 60 of the user device
14 may form the controller of the hearing device 12. A processing unit of the hearing
system 10 may comprise the first processing unit 40 and the second processing unit
60. Thus, first and second processing unit may form the processor 132.
[0081] The second processing unit 60 and the second memory 62 may be alternatively processor
132 and memory 130 according to the present invention. In particular the database
140 may be stored in the second memory 62.
[0082] The hearing device 12 and the user device 14 and in particular the processing units
40, 60 may communicate data via the first and second transceivers 52, 64, which may
be Bluetooth
© transceivers. The hearing device 12 and the user device 14 may be connected for data
communication via a wireless data communication connection.
[0083] With the hearing system 10 it is possible that the above-mentioned modifiers and
their levels and/or values are adjusted with the user device 14 and/or that an adjustment
command is generated with the user device 14 and sent to the hearing device 12. This
may be performed with a computer program run in the second processing unit 60 and
stored in the second memory 62 of the user device 14. This computer program may also
provide the graphical user interface 32 on the display 30 of the user device 14. For
example, for adjusting the modifier, such as volume, the graphical user interface
32 may comprise the control element 34, such as a slider. When the user adjusts the
slider, an adjustment command may be generated, which will change the sound processing
of the hearing device 12. Alternatively or additionally, the user may adjust the modifier
with the hearing device 12 itself, for example via the input mean 24.
[0084] The hearing device 12 and/or the user device 14 may communicate with each other and/or
with the remote server 72 via the Internet 70. The method explained below may be carried
out at least in part by the remote server 72. For example, processing tasks, which
require a huge amount of processing resources, may be outsourced from the hearing
device 12 and/or the user device of 14 to the remote server 72. Further, the processing
units (not shown) of the remote server 72 may be used at least in part as the controller
for controlling the hearing device 12 and/or the use device 14. Thus, the processor
132 for executing the control system 100 of the hearing system 10 as well as the memory
130 may be at least partially located on the remote server 72.
[0085] The user device 14 may comprise a second classifier 66 and/or a further module 68.
[0086] The second classifier 66 may have the same functionality as the first classifier
48 explained above and/or also may be based on a machine learning algorithm. The second
classifier 66 may be arranged alternatively or additionally to the first classifier
48 of the hearing device 12. The second classifier 66 may be configured to classify
the acoustic environment of the user and the user device 14 depending on the received
audio signal, as explained above with respect to the first classifier 48, wherein
the acoustic environment of the user and the user device 14 corresponds to the acoustic
environment of the hearing device 12 and wherein the audio signal may be forwarded
from the hearing device 12 to the user device 14. The system as explained here may
thus comprise a certain number of classifiers, for example classifying movement, time,
noise, environment for describing the possible hearing situations of the user.
[0087] In the following an embodiment of the method of the control system 100 of the hearing
system 10 is described along with Fig. 3.
[0088] The control system 100 is described with respect to Fig. 4. It is shown that the
control system comprises the hearing system 10 and a part 102 external to the hearing
system 10, such as the remote server 72. The remote part 102 is depicted abstractly,
solely showing that it comprises one or more computing devices with at least one processor
130, at least one processor 132 and at least one database 140. Fig. 4 also shows control
units 150, 152, 154, 156, which are in data communication with each other and the
hearing system 10. A control unit 150, 152 also may be part of the hearing device
12 and/or hearing system 10.
[0089] Returning to Fig. 3, when the hearing system 10 is started by the user for example
by switching the hearing device 12 to on, the routine starts in step S2. In step S4,
the hearing system 10 determines the hearing situation of the user in particular with
internal and/or external sensors. Internal sensors are in particular the sound detector
20 and/or sound source detector 42. Furthermore, there may be other sensors like motion
sensors, health sensors, such as blood pressure sensors, heart beat sensors, etc.
or temperature sensors which may be either included in the hearing device 12 or in
the user device 14. If the user device 14 is for example a smart phone, such a smartphone
itself typically includes a microphone and a motion sensor and may have a temperature
sensor.
[0090] The hearing situation may be determined by the hearing device 12 alone, by the user
device 14 or with both the hearing device 12 and the user device 14.
[0091] If the hearing system includes the first and/or second classifiers 48, 66 or even
further classifiers, those may be applied to classify the hearing situation.
[0092] The hearing situation may be classified with a first machine learning algorithm provided
by the first classifier 48 and/or the second classifier 66.
[0093] Based on the hearing situation and user related data, the control system 100 selects
from the database 140, as depicted in Fig. 4, a hearing device setting in step 6.
The database 140 comprises hearing device settings 142, 144. If this hearing device
setting is equal to the used hearing device setting 142, no chance is required, and
the loop returns to step S4. If the hearing device setting is different from the used
one, it is an updated hearing device setting 144, which is selected.
[0094] The database 140 also may be stored in the hearing system 10 or in a control unit
150, 152, 154, 156. For example, the server 72 may be such a control unit.
[0095] The updated hearing device setting 144 may be determined with a second machine learning
algorithm, which is executed is executed in a control unit associated with one control
entity.
[0096] The classification of the hearing situation, which has been generated by the first
machine learning algorithm may be sent to the control unit and may be used there as
input to the second machine learning algorithm.
[0097] In step S8, the control system 100 determines, which control level the updated hearing
device setting is assigned to. Each of the available hearing settings is assigned
to one control level.
[0098] The control system 100 is a hierarchical control system. Typically, in such a hierarchical
control framework, inner layers/loops run at higher frequency than outer layers/loops.
Notifications or feedback can happen instantaneously or may be batched (e.g., as summary
report). The notification and feedback can be applied on the hearing device 12 directly
or alternatively on third devices, such as smartphones that provide a display to highlight
and type, or computer terminals that close the control loop via connection to the
cloud. Thus, in particular by a message send to the user or HCP. Feedbacks allow to
acknowledge, rate, override, oversteer, revert single changes or roll back multiple
changes in history at several layers in hierarchy. They can be triggered by the user
right on the device or by an actor at higher layer indirectly via remote connection
(via proxies like cloud, smartphones, fitting stations at HCPs). They can be actively
submitted by the user on the devices as explicit feedbacks but may also happen implicitly
as the hearing devices observe the user, its behavior and interactions with the hearing
devices. The feedback to the hearing devices can also be given by speech: either actively
by the user via voice control or passively by having the hearing devices monitor the
user's speech in daily conversations and detect keywords that indicate some reinforcement,
rejection or hint regarding an applied functional change or future change still to
be applied. These feedbacks shall help to personalize the steering of the hearing
device, enable learning but also forgetting (which is important for lifelong learning
systems), safeguard regulatory aspects with respect to machine learning algorithm
(as user has the final say through shared control and override mechanism) and make
the hearing device a self-aware system that applies changes where it can do or initiates
queries to higher control levels.
[0099] In step S10, the control system 100 initiates a query to the control units 150, 152,
154, 156 and optionally control entities 120, 122, 124, 126 (see Fig. 5) assigned
to the respective hearing setting. The query is sent as a query message, which is
a data structure exchanged between control units 150, 152, 154, 156.
[0100] As depicted in Fig. 5, the control entity 120 may be associated with the control
unit 150, which may be the control module 44 of the hearing device 12. The control
entity 122 is associated with a control unit 152 or 152', wherein the control unit
152 is for example implemented into a smartphone of the user or the control unit 152'
is for example implemented in a computer of the user. The control entity 154, may
be the HCP, can be associated with the control unit 154, which is implanted in a computing
device of the HCP and the control entity 156 may be associated with a control unit
156, wherein the control entity 156 may be a regulatory body or manufacturer. Thus
a query message may be either send by a direct (wireless connection) as depicted between
the user device 14 and the hearing device 12 or via a network connection, e.g. internet
70, as depicted for the control units 152', 154 and 156.
[0101] Upon approval, the hearing system 10 is allowed to apply the updated hearing device
setting. If the update is not allowed, the hearing system returns to step S4. The
approval is also sent as a message, in this case a feedback message, from the respective
control unit 150, 152, 154, 156 to the hearing system 10.
[0102] If the updated hearing device setting is applied, the control system 100 subsequently
notifies at least the control unit 150, 152, 154, 156 and optionally the control entity
120, 122, 124, 126 assigned to the next higher control level about the application
of the updated hearing device setting in step S12, if the control system comprises
a next higher control level. This notification, also in the form of a notification
message, can be either send directly or may be batched.
[0103] Thus, the new settings are applied. Now either the routine ends with step S14, for
example by switching the hearing system off, or returns to step S4, if a continuous
monitoring is exhibited.
[0104] The notifications to the next higher control unit and/or entity cover functional
changes (e.g., new functions, modes, configuration settings) that have already been
applied and are perceivable for the user, that are suggested by the hearing devices
(aka recommender systems) based on user history (e.g., user interaction history) or
context (e.g., sensed acoustic environments a user stays in during the day). There
may be further notifications to a control unit and/or entity that are enforced by
a control unit and/or control entity of a higher control level in future. A notification
may also comprise several options for the user to choose from (e.g., to apply and
test out, eventually rate and single out the preferred one). These notifications shall
improve the transparency of the system towards the user.
[0105] The basic shared control loop as shown in Fig. 3 is a loop between user and at least
one hearing device 12. The hearing device 12 may comprise at least one processing
unit dedicated to Al, like a deep neural network processor, and one or several sensors
and user interactions. Machine learning may happen during operation on the hearing
devices or a third connected device, based on data sensed by the hearing device sensors
or data obtained by the user interacting with the hearing device. Further data may
be prescribed, defining preconditions (e.g., severity or type of hearing loss, user
type) for learning from the sensed or user/usage data, or itself being the output
from learning algorithms applied to other data sources offline (e.g., deep neural
network models trained on other user data from manufacture's database). The user and
the hearing devices are both involved in steering the system behavior: the user receives
notifications with information about system functions applied or recommended to be
applied from the hearing device resp. hearing system, the hearing system receives
feedback from the user (acknowledge, revert and roll back, override), from which it
can learn further.
[0106] The control system 100 shows that the processor 132 is communicatively coupled with
the memory 130, not depending on whether processor 132 and memory 130 are assigned
directly to the hearing device or to another device as discussed above. The processor
communicates with the different control entities 120, 122, 124, 126, which may be
for example assigned as control entity 120 being the control module 44, control entity
122 being the user, control entity 124 being the HCP and control entity 126 being
the manufacturer or a regulatory body.
[0107] Figure 6 shows a hierarchical (respectively layered) shared control topology with
an inner control loop, comprising the shared control among the user and the hearing
devices according to Figure 3. The hearing device constitutes the lowest control level
110 with control entity 120. The user constitutes the next higher control level 112
with control entity 122. The shared control topology further comprises an outer control
loop, comprising the shared control among the hearing care professional (HCP) and
the system of the user and the hearing devices, wherein the HCP constitutes a third
level 114, the HCP being the third control entity 124. The HCP may receive notifications
from the system about changes applied or suggested, and can act upon them by triggering
recommendations for the user, enabling new functions or features, adjusting configuration
settings or enforcing hard bounds on the configuration space for the user as well
as the steering units of the hearing devices. The optional fourth level 116 is constituted
by the control entity 116, which may be for example the manufacturer, e.g. limiting
the learning and changing of device settings.
[0108] Figure 7 shows another embodiment of the hierarchical shared control system with
three layers and several actors on each layer. In addition to Figure 5, there are
additional actors on the outmost layer, such as a regulatory body (e.g., a public
health authority or the US food and drug administration) or a manufacturer (e.g.,
a hearing device manufacturer like Sonova), which may receive notifications from the
underlying system of applied configuration settings, exercised working modes, provided
quality guarantees or compliance with regulations, specifications or best practice
guidelines. In turn being able to influence and partially control the underlying system
by providing approval or additional support (e.g., provision of an additional deep
neural network model for a desired concrete use case by the manufacturer), or simply
enforcing the abidance of their requirements. On the inner layers, also one or more
additional actors may be present compared to Figure 5. Besides the HCP, significant
others or family members may be informed or provide control inputs to the underlying
system. Besides the main user of the hearing devices, other hearing device users or
the community of hearing device wearers or hearing impaired may be involved in the
shared control of the hearing devices or other accessories that connect to the hearing
devices (e.g., remote microphones, smart chargers or mobile apps on a smartphone).
For example, hearing devices of different users may connect to each other to exchange
control inputs or notifications for the user. Alternatively, or additionally feedback
from other users or the hearing device wearer community may find its way via the manufacturer's
ICT infrastructure to the user's hearing devices. Feedback and notifications may be
exchanged between user and accessory, resulting in shared control among user and accessory
itself or indirectly among user and hearing devices again, using the accessory as
a proxy.
[0109] The hearing system as described above provides in the different embodiments one or
more of the following benefits:
The machine learning algorithm is improved by collecting feedback (e.g., ratings,
acknowledgments) from users for applied configurations and configuration changes,
which can be used as labels for learning (knowledge about true improvements); a bad
rating or a user's veto could also indicate uncertainty of the steering unit and a
need for gathering more representative data for the given situation.
The machine learning algorithm learns users' preferences. It can use them for abstraction
of user groups/profiles, provide recommendations/predictions to users based on their
own and/or other users' feedback, as well as environmental clues as part of the hearing
situation of the user from sensor measurements, which helps to increase users' convenience
and hearing devices' performance (i.e., continuous adjustments in the field to make
up for potentially limited product requirements/verification of the Al system) The
users interacts with the system and thus set their requirements which leads to a user-centered/driven
customized settings and takes care of personalized requirements quasi a posteriori).
[0110] The inclusion of a machine learning algorithm in the system is in particular beneficial,
if the Al can learn from the preferences and data of a multitude of users providing
heterogeneous data.
[0111] The safety of the system in enhanced by having human control entities at several
levels (user himself, experts like HCP, manufacturer, regulatory body) to acknowledge
decisions by machine learning algorithm to ensure compliance with medical regulations
(medical safety, application/network security) and/or performance as intended, i.e.,
according to requirements/specification (machine learning algorithm safety as well
as machine learning algorithm security: increase users' safety/security and hearing
devices' quality, eventual verification - according to users' requirements - to make
up for limited product verification of machine learning algorithm systems and anticipate
unexpected situations as quasi verification of the "black box" in the field through
experts instances).It also remedies inherent limitations of the machine learning algorithm
of missing determinism and transparency (e.g. what has been learnt exactly) and its
predictions implying uncertainty.
[0112] While the invention has been illustrated and described in detail in the drawings
and foregoing description, such illustration and description are to be considered
illustrative or exemplary and not restrictive; the invention is not limited to the
disclosed embodiments. Other variations to the disclosed embodiments can be understood
and effected by those skilled in the art and practicing the claimed invention, from
a study of the drawings, the disclosure, and the appended claims. In the claims, the
word "comprising" does not exclude other elements or steps, and the indefinite article
"a" or "an" does not exclude a plurality. A single processor or controller or other
unit may fulfill the functions of several items recited in the claims. The mere fact
that certain measures are recited in mutually different dependent claims does not
indicate that a combination of these measures cannot be used to advantage. Any reference
signs in the claims should not be construed as limiting the scope.
LIST OF REFERENCE SYMBOLS
[0113]
- 10
- hearing system
- 12
- Hearing device
- 14
- User device
- 15
- part behind the ear
- 16
- part to be put in the ear
- 18
- tube
- 20
- sound detector
- 22
- device
- 24
- input mean
- 30
- display
- 32
- control element
- 34
- control element
- 40
- first processing unit
- 42
- sound module
- 44
- control module
- 46
- sound source detector
- 48
- first classifier
- 50
- first memory
- 52
- first transceiver
- 60
- second processing unit
- 62
- second memory
- 64
- second transceiver
- 66
- second classifier
- 70
- Internet
- 72
- remote server
- 100
- control system
- 102
- external part
- 110, 112, 114, 116
- control level
- 120, 122, 124, 126
- control entity
- 130
- memory
- 132
- processor
- 140
- database
- 142
- hearing device settings
- 144
- updated hearing device settings
- 150, 152, 154, 156
- control unit
1. A hierarchical control system (100) with a hearing system (10) including a hearing
device (12), the control system (10) implementing at least two hierarchical ordered
control levels (110, 112, 114, 116),
wherein the control system comprises one or more control units (150, 152, 154, 156)
assigned to the control levels (110, 112, 114, 116),
wherein the control system (10) is configured to execute the following instructions:
determining and monitoring a hearing situation of a user of the hearing system (10)
based on a status of the hearing system (10) and user related data stored in the hearing
system (10),
determining, based on the hearing situation of the user, an updated hearing device
setting (144),
associating the updated hearing device setting (144) with one of the at least two
control levels,
generating a query message for approval of the updated hearing device setting (144)
and sending the query message to the control unit (150, 152, 154, 156) assigned to
the control level (110, 112, 114, 116) associated with the updated hearing device
setting (144),
receiving a feedback message in response to the query message from the control unit
(150, 152, 154, 156) and, if the feedback messages contains an approval of the updated
hearing device setting (144), applying the updated hearing device setting (144) to
the hearing device (12); and,
if the control system (100) comprises a next higher control level, generating a notification
message about the application of the updated hearing device setting (144) and sending
the notification message to the control unit (150, 152, 154, 156) assigned to the
next higher control level (110, 112, 114, 116).
2. The control system (100) according to claim 1,
wherein at least one control entity (120, 122, 124, 126) is assigned to each of the
control levels (110, 112, 114, 116), and
wherein at least one control entity (120, 122, 124, 126) is a user or a HCP or a regulatory
body or a manufacturer, and/or
wherein at least one control entity (120, 122, 124, 126) is associated with one or
more control units (150, 152, 154, 156).
3. The control system (100) according to claim 1 or 2,
wherein the control system (100) includes at least three control levels, and a control
unit (150) assigned to a lowest, first control level (110) is associated with the
hearing device (12), and/or
a control unit (152) assigned to a next higher, second control level (112) is associated
with a user of the hearing system (10), and/or
a control unit (154) assigned to a next higher, third control level (114) is associated
with an HCP or a care taker, and/or
a control unit (156) assigned to a next higher, fourth control level is associated
with a regulatory body or a manufacturer.
4. The control system (100) according to one of the preceding claims,
wherein the control system (10) and/or the control units (150, 152, 154, 156) include
interfaces or are communicatively coupled to interfaces for presenting information
to and receiving information from one or more control entities (110, 112, 114, 116).
5. The control system (100) according to one of the preceding claims,
wherein the status of the hearing system (10) is based on sensor data acquired by
the hearing system (10); and/or
wherein the hearing situation is determined and monitored by classifying sensor data
acquired by the hearing system (10) and the user related data.
6. The control system (100) according to claim 5,
wherein the sensor data comprises audio data acquired with a microphone (20) of the
hearing system (10) and the audio data is classified with respect to different sound
situations as hearing situations; and/or
wherein the sensor data comprises position data acquired with a position sensor of
the hearing system (10) and the position data is classified with respect to different
locations and/or movement situations of the user as hearing situations; and/or
wherein the sensor data comprises medical data acquired with a medical sensor of the
hearing system (10) and the medical data is classified with respect to different medical
conditions of the user as hearing situation.
7. The control system (100) according one of the previous claims,
wherein the user related data comprises information on a hearing loss of the user
and/or an audiogram of the user; and/or
wherein the user related data comprises settings of a sound processing of the hearing
system (10).
8. The control system (100) according to one of the preceding claims,
wherein the hearing situation is classified with a first machine learning algorithm
(48, 66);
wherein the first machine learning algorithm (48, 66) is executed in the hearing system
(10).
9. The control system (100) according to one of the preceding claims,
wherein the updated hearing device setting (144) is determined with a second machine
learning algorithm;
wherein the second machine learning algorithm is executed in a control unit (150,
152, 154, 156) associated with one control entity (120, 122, 124, 126) and wherein
the classification of the hearing situation is sent to the control unit (150, 152,
154, 156).
10. A method for controlling a hearing system (10) by means of a hierarchical control
system (100) implementing at least two hierarchically ordered control levels (110,
112, 114, 116) and comprising one or more control units (150, 152, 165, 156) assigned
to the control levels, the method comprising:
determining and monitoring a hearing situation of a user of the hearing system (10)
based on a status of the hearing system (10) and user related data stored in the hearing
system (10); and
determining, based on the hearing situation of the user, an updated hearing device
setting (144),
associating the updated hearing device setting (144) with one of the at least two
control levels (110, 112, 114, 116),
generating a query message for approval of the updated hearing device setting (144)
and sending the query message to the control unit (150, 152, 154, 156) assigned to
the control levels (110, 112, 114, 116) associated with the updated hearing device
setting (144),
receiving a feedback message in response to the query message from the control unit
(150, 152, 154, 156) and, if the feedback messages contains an approval of the updated
hearing device setting (144), applying the updated hearing device setting (144) to
the hearing device (12); and,
if the control system (100) comprises a next higher control level, generating a notification
message about the application of the updated hearing device setting (144) and sending
the notification message to the control unit (150, 152, 154, 156) assigned to the
next higher control level (110, 112, 114, 116).
11. A computer program for controlling a hearing system (10), which, when being executed
by at least one processor, is adapted to carry out the steps of the method of claim
10.
12. A computer-readable medium, in which a computer program according to claim 11 is stored.