EP0712262A1 - Hearing aid - Google Patents

Abstract

The hearing aid (1) has control functions for the amplifier and transmission unit (4) which operate partially or fully according to the principle of neuronal structures (5). An AGC (31) can be associated with the control unit (5'). The AGC is in the signal path between the microphone (2) and the hearing device (3) and is provided for individual matching of the dynamic range of an input signal to the limited dynamic range of the hearing impaired user. The amplifier and transmission unit includes a limiting circuit (Peak Clipping) and/or automatic loudspeaker control. The hearing aid may be a multi-channel hearing aid. A switch or potentiometer may be used to detect the system status of the hearing aid

Description

The invention relates to a hearing aid with an amplifier and transmission part which can be adjusted in terms of its transmission properties between the microphone and the listener to different transmission characteristics.

A programmable hearing aid in a multi-channel design, in which an arrangement of several signal branches is arranged behind the microphone receiving the input sound signals, each of which consists of a frequency-selective filter, a level-dependent gain control and an arrangement for non-linear signal deformation, followed by a summing amplifier that combines the partial signals, which is connected to an output signal converter (receiver) via an output amplifier is known from EP-B-0 071 845. In this known multi-channel hearing aid, an automatic gain control circuit (AGC = automatic gain control) is assigned to each frequency channel, these AGC circuits working independently of one another and their threshold values being adjustable differently. These threshold values can be called up or changed with a programming device. The selected setting values for the channel separation frequencies, the AGC threshold values for each channel and the individual gain setting for each channel are stored in a digital memory of the hearing aid.

From DE-A-27 16 336 a hearing aid is also known in which the analog sound signal coming from the microphone, after passing through a low-pass filter in an A / D converter, is converted into a digital signal and fed to a discrete signal processing circuit, the transfer function of which n -th order from parameters stored in an electrically programmable read-only memory (EPROM) by means of a Microprocessor with arithmetic unit to adapt to hearing damage is controllable. The programming can be changed by deleting the read-only memory and re-programming. The digital signal modified in this way is then converted into a corresponding analog signal in a D / A converter, amplified and fed to the listener.

Furthermore, EP-B-0 064 042 discloses a circuit arrangement for a hearing aid in which, for example, the parameters of a number of different environmental situations are stored in a memory in the hearing aid itself. By actuating a switch, a first group of parameters is called up and controls, via a control unit, a signal processor connected between the microphone and the handset, which then sets a first transmission function intended for an intended environmental situation. The transmission functions of several stored signal transmission programs can be called up in succession via a switch until the transmission function that is just right for the given environmental situation is found.

It is therefore known to adapt hearing aids to the individual hearing loss of the hearing device wearer to be supplied. A setting of the hearing aid is also provided for different listening situations. Programmable hearing aids offer a large number of adjustable parameters which are intended to enable the electro-acoustic behavior of the hearing aid to be optimally adapted to the hearing damage to be compensated for.

It is now desirable to have largely automatic control of signal processing functions in the hearing aid by evaluating the input signal and using a simplified, optimized control system.

The object of the invention is to provide a hearing device which is characterized by a simplified, optimized control system.

According to the invention, this object is achieved in a hearing device of the type mentioned at the outset in that control functions are provided in the amplifier and transmission part, which are implemented in whole or in part according to the principle of neural structures. In addition to other signal processing functions, modern hearing aids also adapt the dynamic range of the input signal to the generally restricted dynamic range of the hearing impaired. This requires specific control functions. These can be implemented using components that work according to the principle of neural structures and allow simple adjustment of the necessary controller characteristics. Among other things, this also enables the targeted introduction of non-linear components into the controller characteristics, as well as, under certain circumstances, the continuous optimization of the control behavior during operation.

In an advantageous embodiment of the invention, at least one automatic gain control - AGC = automatic gain control - for individually adapting the dynamic range of an input signal to a restricted dynamic range of the hearing impaired is provided in a programmable hearing device in at least one signal path between the microphone and the listener, and this gain controller is a controller after Principle associated with neural structures.

Advantageous embodiments of the invention are characterized by the claims.

Further advantages and details of the invention are explained in more detail below with reference to the exemplary embodiments shown in the figures.

• Figur 1 ein Blockschaltbild eines erfindungsgemäßen Hörgerätes,
• Figur 2 ein Blockschaltbild einer neuronalen Struktur mit Signalaufbereitung, zugeordnetem Konfigurationsspeicher sowie Mittel zur Erfassung von Systemzuständen des Hörgerätes,
• Figur 3 ein Modul zur Signalaufbereitung nach Figur 1,
• Figur 4 ein Blockschaltbild eines einzelnen Neurons,
• Figuren 5a, 5b, 5c Beispiele für mögliche Schwellenwertverläufe der Ausgabefunktion W gemäß Figur 4,
• Figur 6 ein einlagiges, rückgekoppeltes Netz mit beispielhafter Verschaltung von drei Neuronen,
• Figur 7 ein mehrlagiges, rückkopplungsfreies Netz mit beispielhafter Verschaltung von elf Neuronen in drei Lagen,
• Figur 8 ein Schaltungsbeispiel für die schaltungstechnische Realisierung eines einlagigen rückgekoppelten Netzes gemäß Figur 6,
• Figur 9 eine mögliche Schaltung zur Realisierung einer Synapse mit programmierbarer Verbindungsstärke,
• Figur 10 eine Ausführung einer Schaltung für eine Synapse mit programmierbarer variabler Verbindungsstärke,
• Figur 11 ein Ausführungsbeispiel eines erfindungsgemäßen Hörgerätes, bei dem die aus dem Signalpfad zwischen dem Mikrofon und dem Hörer abgegriffenen Signale über die Signalaufbereitung und über ein Fuzzy-Logik-System dem Regler nach dem Prinzip der neuronalen Strukturen zugeführt werden.

Show it:

• FIG. 1 shows a block diagram of a hearing device according to the invention,
• FIG. 2 shows a block diagram of a neural structure with signal processing, assigned configuration memory and means for detecting system states of the hearing aid,
• FIG. 3 shows a module for signal processing according to FIG. 1,
• FIG. 4 shows a block diagram of an individual neuron,
• FIGS. 5a, 5b, 5c examples of possible threshold value profiles of the output function W according to FIG. 4,
• FIG. 6 shows a single-layer, feedback network with an exemplary connection of three neurons,
• FIG. 7 shows a multi-layer, feedback-free network with exemplary connection of eleven neurons in three layers,
• 8 shows a circuit example for the implementation of a single-layer feedback network according to FIG. 6,
• FIG. 9 shows a possible circuit for realizing a synapse with programmable connection strength,
• 10 shows an embodiment of a circuit for a synapse with programmable variable connection strength,
• FIG. 11 shows an exemplary embodiment of a hearing device according to the invention, in which the signals tapped from the signal path between the microphone and the listener are processed via the signal and fed to the controller via a fuzzy logic system based on the principle of neural structures.

The hearing aid 1 according to the invention, shown schematically in FIG. 1, records 2 sound signals x via a microphone. This acoustic information (input signal) is converted into electrical signals in the microphone. After signal processing in an amplification and transmission part 4, the electrical signal y is fed to a receiver 3 as an output converter. In the exemplary embodiment, the principle of regulating signal processing functions by means of neural structures 5 is shown using the example of an AGC (gain controller 31 = automatic gain control). Figure 1 shows the basic structure of an AGC control loop. The output variable y to be controlled is tapped and processed (e.g. by rectification and formation of a suitable time average) and fed to a controller 5 '. This controller 5 'controls the amplification of the useful signal by means of an amplifier with variable amplification and determines the behavior of the AGC 31 through its control characteristics (including the so-called settling and decay time).

Signals 8 are tapped from the signal path of the hearing aid 1 between its microphone 2 and its receiver 3 at certain desired tapping points 7. These signals 8 are fed to a controller 5 ′ provided in the hearing aid, which is designed according to the principle of the neural structures 5. The signals 8 first arrive at a module 9 for signal processing and from its outputs conditioned signals 10, 10 ', 10''are fed to the neural structure 5. A data carrier 6 is assigned to the neural structure 5, in which configuration information of the neural structure is stored. Taking into account the configuration information of the data carrier 6, the neural structure 5 generates control signals 11 from the processed signals 10, 10 ′, 10 ″, which are sent to the amplifier and transmission part 4 can be fed to adapt its transmission characteristics. According to the exemplary embodiment, these generated control signals 11 influence the processing of the variable to be controlled (useful signals).

As can be seen from FIG. 2, signals are tapped from the signal path of the hearing aid at all relevant points or tapping points and processed in a suitable manner. These processed signals and any other system information, e.g. whether the microphone or telephone operation is desired is fed into the neural structure. The generated signals 11 thus influence the signal processing of the input signal x to the output signal y. The behavior of the neural structures does not necessarily have to be unchangeable (i.e. completely described by the hardware structure), but can be configurable (e.g. by programming). As already mentioned, configuration information can be stored in the memory 6 in the hearing device 1.

• Die Bildung des zeitlichen Mittelwerts (sowie eventuell der zugehörigen Ableitung) kann mehrfach mit unterschiedlichen Zeitkonstanten geschehen, um auf verschieden schnelle Änderungen des Signalpegels spezifisch reagieren zu können.
• Gleichermaßen kann auch das Signal direkt (also ohne Bildung eines zeitlichen Mittelwertes) dem Neuro-Regler zugeführt werden, um auf Signalspitzen reagieren zu können.
• Weitere Systeminformationen 14 (z.B. über die momentan eingestellte Hörsituation oder Mikrofon-/Telefonposition) können dem Regler zugeführt werden, um diese ebenfalls in das Reglerverhalten mit einbeziehen zu können.
• Sowohl mehrere Eingangsgrößen 8 als auch Ausgangsgrößen 11 sind möglich, so daß der Signalpegel an unterschiedlichen Stellen des gesamten Signalpfads in die Regelung mit einbezogen werden kann bzw. die Regelung an mehreren Stellen im Signalpfad eingreifen kann.

FIG. 3 shows the basic structure of the signal processing and the controller based on the principle of the neural structures for the AGC. In the signal processing block, the required input variables of the neuro controller are obtained from the input signal, for example by rectification, forming a time average and possibly deriving it. A memory with configuration information can also be assigned to the neuro controller itself, so that the control behavior can be adapted to different requirements. The following possible generalizations are indicated in Figures 2, 3:

• The formation of the time average (and possibly the associated derivation) can be done several times with different time constants in order to different be able to react quickly to changes in the signal level.
• In the same way, the signal can also be fed directly to the neuro controller (i.e. without forming a time average) in order to be able to react to signal peaks.
• Further system information 14 (for example about the currently set listening situation or microphone / telephone position) can be fed to the controller in order to be able to include this in the controller behavior as well.
• Both several input variables 8 and output variables 11 are possible, so that the signal level at different points in the entire signal path can be included in the regulation or the regulation can intervene at several points in the signal path.

In a further embodiment of the hearing device according to the invention, means 13 are provided for detecting system states of the hearing device 1, the output signals 14 of which can be fed to the module 9 for signal processing and / or the neural structure 5, these output signals being able to be taken into account when generating the control signals 11.

Control elements that can be actuated by the hearing aid wearer, such as switches, buttons, potentiometers, or the like, can be provided as means 13 for detecting system states of the hearing aid 1. The hearing aid can then be equipped, for example, with a situation switch, which enables the hearing aid wearer - as described at the beginning of EP-B-0 064 042 - to select a stored transmission function which he thinks is suitable for the given environmental situation. On the other hand, the hearing aid can have, for example, a switch for switching from microphone operation to telephone coil operation. Of the hearing aid also has a volume control with which the hearing impaired person influences the volume.

Finally, the hearing device can also be characterized in that a device 15 which monitors the state of charge of the hearing device battery, not shown, is additionally provided as a means for detecting system states of the hearing device 1. Thereafter, it is possible that the respective state of charge of the hearing aid battery is also taken into account when generating the output signals 11 of the neural structure 5.

In the known so-called multi-channel devices, i.e. in hearing aids with several frequency channels, according to the invention the signals 8 are tapped from the signal paths formed by the individual channels. As shown in Figure 3, the signals 8 from the signal paths and the output signals 14 of the means 13, 13 'for detecting system states of the hearing aid, e.g. prepared by rectification, formation of suitable averages over time and possibly from their derivations. In signal processing - module 9 - at least one input variable, e.g. Signals 8, 14, signals 10 processed by a component 16 for rectification and / or a component 17 for averaging (forming a time average) and / or a component 18 for time derivation (derivation block d / dt) from the signals 8, 14, 10 ', 10' 'which are fed to the neural structure 5. Likewise, the signals 14 can also be fed directly to the neural structure (FIG. 2).

Examples for realizing the neural structure are described with reference to FIGS. 4-10.

Neural structures consist of many similar elements or neurons 19. The function of the neural structure as a whole essentially depends on the way in which these neurons are interconnected.

• Propagierungsfunktion ${\text{U:u(t)=Σe}}_{\text{i}}{\text{(t)*w}}_{\text{i}}$
  
  
  Die Ausgangsgröße dieser Funktion ist die Summe aller, jeweils mit dem individuellen Faktor w_i multiplizierten Eingangssignale.
• Aktivierungsfunktion $\text{V:v(t)=f(u(t))}$
  
  
  Im allgemeinen Fall geht in die Ausgangsgröße auch deren eigene Vorgeschichte ein. In vielen Fällen kann hierauf jedoch verzichtet werden. v(t) zum Zeitpunkt t=t₀ ist dann nur noch eine Funktion von u(t) zum Zeitpunkt t=t₀.
• Ausgangsfunktion W:w(t)
  Sie nimmt eine Schwellenwertbildung vor. Dabei sind gemäß Figur 5 zwei grundsätzliche Arten der Schwellenwertbildung möglich.

FIG. 4 shows the block diagram of an individual neuron 19. The neuron generates the output signal a _j (t + ΔT) at time t + ΔT from theoretically any number of input signals e _i (t) at time t. Its function can be broken down into three basic functions:

• Propagation function ${\text{U: u (t) = Σe}}_{\text{i}}{\text{(t) * w}}_{\text{i}}$
  
  
  The output variable of this function is the sum of all input signals multiplied by the individual factor w _i .
• Activation function $\text{V: v (t) = f (u (t))}$
  
  
  In the general case, the output variable also includes its own history. In many cases this can be dispensed with. v (t) at time t = t₀ is then only a function of u (t) at time t = t₀.
• Output function W: w (t)
  It creates a threshold value. According to FIG. 5, two basic types of threshold value formation are possible.

According to FIG. 5a, the course of the output function W represents a step function at the threshold value s.

. Figur 5c zeigt einen linearen Verlauf im Übergangsbereich.According to FIGS. 5b and 5c, the output function W has a continuous course around the threshold value s. FIG. 5b shows a continuous, so-called sigmoid curve of the output variable with limitation to a maximum and a minimum output value. A frequently used characteristic is the sigmoid: $\text{w (t) = 1 / (1 + exp (- (v (t) -s)))}$

. FIG. 5c shows a linear course in the transition area.

The signals which are processed by the neural structure can be designed as voltage signals, current signals or as frequency-variable pulse signals. In the latter In this case, the signal may have to be converted into a continuous current or voltage signal and back again at some points in the neural structure with the aid of suitable circuits.

FIG. 6 shows the exemplary connection of three neurons 19 to the typical structure of a single-layer feedback network with the inputs e _i (t) and the outputs a _j (t + ΔT).

FIG. 7 shows an example of the structure of a multilayer feedback-free network. Depending on the function of the neural structure to be implemented, one or the other network structure must be used. Mixed forms of both structures are also possible.

The function of a neural structure as a whole is essentially determined by the network structure and by the weighting functions of the input signals on each neuron 19. These parameters can be permanently set through the implementation in terms of circuitry if constant behavior is desired. If, on the other hand, a change in behavior should be possible, some or all of these parameters must be programmable. Their respective values must then be stored in a configuration memory or data carrier 6. The individual memory elements can be arranged in a concentrated form or locally assigned to the respective neuron.

The stored parameters can be modified either by external programming of the memory elements and / or by an algorithm implemented in the circuit. Modification is also possible during the ongoing operation of the neural structure.

) geschieht in den Schaltungsknoten am Eingang eines jeden Verstärkers. Die Ausgangssignale der Verstärker und damit der neuronalen Struktur sind die Spannungssignale U_i. Mit e1 bis e4 sind die Eingänge der Schaltung und mit a1 bis a4 sind invertierende und nichtinvertierende Ausgänge der Schaltung bezeichnet.Figure 8 shows an example of the circuitry implementation of a single-layer feedback network. Amplifiers 24 with complementary outputs act as threshold elements. The connections (synapses) between the outputs and inputs of the neurons are weighted using the guide values R _ij . The addition of the input signals for each neuron (currents ${\text{I.}}_{\text{ij}}{\text{= U}}_{\text{i}}{\text{/ R}}_{\text{ij}}$

) happens in the circuit nodes at the input of each amplifier. The output signals of the amplifiers and thus the neural structure are the voltage signals U _i . E1 to e4 denote the inputs of the circuit and a1 to a4 denote inverting and non-inverting outputs of the circuit.

FIG. 9 shows a possible circuit implementation of a synapse (weighted input of a neuron) with programmable connection strength. Only the connection strengths +1, -1 and 0 are possible and the signals to be transmitted from this synapse can only assume the logical values 0 and 1. If both memory cells 25, 26 are programmed so that they block the respective associated switching transistor 27 or 28, output a is independent of input e; the synapse therefore represents an interruption (connection strength 0). If, on the other hand, the memory cell 25 is programmed to close the switch and the memory cell 26 to open the associated switch, then a current (logic 1) flows from the output a when the input is logic 1, and no current (logic 0) if the input is logic 0. So the synapse acts as a connection of strength +1. If both memory cells 25, 26 are programmed inversely for this purpose, the inverse logic behavior results. The synapse then acts as a connection of strength -1. V _dd indicates the circuit connection to the supply voltage in the drawing.

). Werden die Spannungen V_w+ und V_w- auf den Floating Gates von entsprechenden EEPROM-Transistoren gespeichert, so ist auch eine dauerhafte Speicherung der Synapsenstärke möglich.FIG. 10 shows a possible implementation of a programmable synapse with variable connection strength. she works on the principle of the multiplier. The strength of the synaptic connection is stored as the difference between two analog voltage values on two capacitors 29, 30. The output signal (current I _out ) is the product of the input signal (voltage V _in ) multiplied by the voltage difference stored on the capacitors ( ${\text{V}}_{\text{w}}{\text{= V}}_{\text{w +}}{\text{-V}}_{\text{w-}}$

). If the voltages V _{w +} and V _w- are stored on the floating gates of corresponding EEPROM transistors, permanent storage of the synapse strength is also possible.

A further development of the invention is shown schematically on the basis of the block diagram according to FIG. 11, a combination of the fuzzy logic principle and the principle of neural structures being provided. For example, fuzzy logic can be used to prepare the input variables of the neural structure according to certain predefinable rules. Parts of the control behavior that can be specified explicitly can also be implemented as fuzzy logic, while additional parts that cannot be formulated explicitly, e.g. Parts of the control behavior learned during operation can be realized by the neural structure. In the latter case, these two components of the controller would then preferably be connected in parallel. A memory with configuration information, which determines the behavior of the respective component, can in turn be assigned to both components. The principle of operation and a possible circuitry implementation of the functions fuzzy logic, inference formation and defuzzification necessary for the fuzzy logic is described in European patent application 94104619.5.

Significant advantages of the invention result from the improved possibilities when setting the desired control characteristic, inter alia by introducing non-linear components. Furthermore, through continuous optimization of the control characteristics through "learning" in the current Operation and finally by simple and precisely defined inclusion of different input variables in the control characteristic, for example of variables that characterize the state of the overall system.

Claims (16)

Hearing aid (1) with an amplifier and transmission part (4) adjustable in its transmission properties between microphone (2) and receiver (3) to different transmission characteristics, characterized in that control functions are provided in the amplifier and transmission part (4) which are entirely or are partially implemented according to the principle of neural structures (5). Hearing aid according to claim 1, characterized in that at least one automatic gain control (31) - AGC = automatic gain control - for individually adapting the dynamic range of an input signal to a restricted dynamic range of the hearing impaired person in at least one signal path between the microphone (2) and the receiver (3) provided and this gain controller is assigned a controller (5 ') based on the principle of the neural structures. Hearing aid according to claim 1, characterized in that the amplifier and transmission part has a limiter circuit (PC, peak clipping) and / or an automatic volume control, which is assigned a controller based on the principle of neural structures. Hearing aid according to claims 1 to 3, characterized in that in the case of a multi-channel hearing aid, adjustable amplifier and transmission parts are provided in the individual frequency channels and these controllers are assigned according to the principle of neural structures. Hearing aid according to one of claims 1 to 4, characterized in that a data carrier (6) is assigned to the controller (5 ') according to the principle of neural structures, with one or more of the signal path Tapping points (7) signals (8) are tapped and fed to a module (9) for signal processing, and the processed signals (10, 10 ', 10'') can be fed to the neural structure (5) which generates control signals (11), that affect the processing of the variable to be controlled (useful signals). Hearing aid according to one of claims 1 to 5, characterized in that means (13) are provided for detecting system states of the hearing aid (1), the output signals (14) of which are sent to the module (9) for signal processing and / or the neuronal structure (5) can be supplied, these output signals being taken into account when generating the control signals (11). Hearing aid according to claim 6, characterized in that actuating elements, such as switches, buttons, potentiometers or the like, which can be actuated by the hearing aid wearer, are provided as means (13) for detecting system states of the hearing aid (1). Hearing aid according to claim 6, characterized in that a device (15) monitoring the state of charge of the hearing aid battery is provided as means (13, 13 ') for detecting system states of the hearing aid (1). Hearing aid according to one of claims 1 to 8, characterized in that the module (9) for signal conditioning comprises components for rectification (16) and / or for averaging (17) and / or for time derivation (18). Hearing aid according to one of claims 1 to 9, characterized in that in the data carrier (6) which is assigned to the neural structure (5), Configuration information for the neural structure is stored. Hearing aid according to one of claims 1 to 10, characterized in that the neural structure (5) is designed either as a single-layer feedback network (Fig. 6) or as a multi-layer feedback-free network (Fig. 7) or as a mixed form of both network structures. Hearing aid according to one of claims 1 to 11, characterized in that the weighting functions at the input of all neurons are fixed by the circuit structure. Hearing aid according to one of claims 1 to 11, characterized in that the weighting functions at the input of all neurons are designed to be programmable by an external control device, the programming data being stored in a common data carrier (6) or the respective programming data being stored individually in the partial memories assigned to the neurons . Hearing aid according to one of claims 1 to 11, characterized in that the weighting functions at the input of all neurons can be modified at certain times or continuously by an algorithm implemented in the circuit structure. Hearing aid according to one of claims 1 to 14, characterized in that the controller (5 ') according to the principle of neural structures comprises additional functional parts (20) which operate according to the principle of fuzzy logic. Hearing aid according to claim 15, characterized in that between the signal path signals (8) picked up from the microphone (2) and the receiver (3) via the signal conditioning unit (9) and via the fuzzy logic system (20) to the controller (5 ') according to the principle of the neural structures.

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