EP0712261A1 - Prothèse auditive programmable - Google Patents

Prothèse auditive programmable Download PDF

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Publication number
EP0712261A1
EP0712261A1 EP94117795A EP94117795A EP0712261A1 EP 0712261 A1 EP0712261 A1 EP 0712261A1 EP 94117795 A EP94117795 A EP 94117795A EP 94117795 A EP94117795 A EP 94117795A EP 0712261 A1 EP0712261 A1 EP 0712261A1
Authority
EP
European Patent Office
Prior art keywords
hearing aid
aid according
signals
signal
neural structure
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP94117795A
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German (de)
English (en)
Inventor
Oliver Dipl.Ing. Weinfurtner
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sivantos GmbH
Original Assignee
Siemens Audioligische Technik GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Audioligische Technik GmbH filed Critical Siemens Audioligische Technik GmbH
Priority to EP94117795A priority Critical patent/EP0712261A1/fr
Priority to US08/515,907 priority patent/US5754661A/en
Publication of EP0712261A1 publication Critical patent/EP0712261A1/fr
Withdrawn legal-status Critical Current

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/50—Customised settings for obtaining desired overall acoustical characteristics
    • H04R25/505—Customised settings for obtaining desired overall acoustical characteristics using digital signal processing
    • H04R25/507—Customised settings for obtaining desired overall acoustical characteristics using digital signal processing implemented by neural network or fuzzy logic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2225/00—Details of deaf aids covered by H04R25/00, not provided for in any of its subgroups
    • H04R2225/41—Detection or adaptation of hearing aid parameters or programs to listening situation, e.g. pub, forest

Definitions

  • the invention relates to a programmable hearing aid with an amplifier and transmission part which can be adjusted in terms of its transmission properties between at least one microphone and a receiver to different transmission characteristics.
  • EP-B-0 064 042 discloses a circuit arrangement for a hearing device in which, for example, the parameters of a number of different environmental situations are stored in a memory in the hearing device 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.
  • the object of the invention is to provide a programmable hearing aid which is characterized by improved signal processing distinguished, which enables in particular an improved separation of the useful signals from the noise.
  • this object is achieved in a hearing device of the type mentioned in the introduction in that signals of the signal path from the microphone to the listener are routed through a neural structure and processed therein.
  • the use of neural structures enables novel methods and algorithms for signal processing in the hearing aid. Among other things, this improves the separation of different signals, e.g. of useful signals and noise, possible.
  • the behavior of the signal processing can be fixed or programmable or variable in order to continuously adapt to the signal to be processed during operation.
  • the hearing aid 1 shown schematically in FIG. 1, records sound signals via a microphone 2 or further microphones 2 '. This acoustic information is converted into electrical signals in the microphone or microphones. After signal processing in an amplification and transmission part 4, the electrical signal is fed to a receiver 3 as an output converter.
  • the amplifier and transmission part 4 further comprises a neural structure 5 such that, for the purpose of improved signal processing, in particular for improved separation of the useful signals from the noise, signals of the signal path from at least one microphone 2, 2 'to the listener 3 via the neural Structure 5 managed and processed in it.
  • a data carrier 6 is assigned to the neural structure 5, in which configuration information of the neural structure is programmable or permanently stored.
  • a signal processing unit 9 for preprocessing the input signal into a plurality of sub-signals 10, 10 ', 10'' is connected upstream, the sub-signals then being processed further in the neural structure.
  • the neural structure 5 Taking into account the configuration information of the data carrier 6, the neural structure 5 generates an output signal from the processed partial signals 10, 10 ', 10'', in particular a useful signal separated from the noise, which is then further processed, for example, in known components of the amplifier and transmission unit 4 and via the final amplifier 4''' can be fed to the receiver 3.
  • 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.
  • the course of the output function W represents a step function at the threshold value s.
  • the output function W has a continuous course around the threshold value s.
  • FIG. 4b shows a continuous, so-called sigmoid curve of the output variable with limitation to a maximum and a minimum output value.
  • FIG. 4c 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.
  • 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. 5 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 + ⁇ T).
  • Figure 6 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. Your respective values must then be stored in a configuration memory or data medium 6 can be saved. 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.
  • Figure 7 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 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. 8 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 so that it closes the switch and the memory cell 26 so that it opens the associated switch, then a current flows from output a (logic 1) when the Input is logic 1 and no current (logic 0) if the input is logic 0.
  • 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.
  • FIG. 9 shows a possible implementation of a programmable synapse with variable connection strength. It 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.
  • An advantageous application of neural structures in the hearing aid is the separation of independent mixed signals, e.g. the separation of the voice signal of a conversation partner from a noise from another source.
  • the neural structure needs as many independent signal inputs as there are independent signals to be separated from one another. This can be achieved in the hearing aid by using a plurality of microphones, these preferably being arranged in such a way that the signals to be separated arrive at the two microphones with as different a strength as possible.
  • FIG. 11 generally shows how a single-layer feedback network structure can be used to separate the signals.
  • the neural structure receives the signals from the individual microphones and to the Outputs A1, A2, A3 ... are after a certain learning time the separate signals from each other for further processing or output to the listener 3. It makes sense to process or output only one (desired) output signal, while the other output signals are discarded.
  • a suitable size S ij or function independently determines the degree of connection strength for each synapse 7.
  • the size S13, S12, S21, S23, S31, S32 ... or generally S ij represents the learning function of the neural structure.
  • a possible realization of the variable connection strength of the synapse 7 is shown in Figure 10.
  • the input signal E i (t) the returned output signal A j (t) multiplied by a quantity S ij (t) is added.
  • S ij can be stored permanently in order to be able to call them up again and again for the same signal processing function, for example by selecting a listening situation, or the learning process of the neural structure can be restarted by the user in order to process the signal adapt to the new acoustic environment.
  • the learning process of the neural structure can be restarted by the user in order to process the signal adapt to the new acoustic environment.
  • an ongoing automatic adaptation of the neural structure possible in order to continuously adapt to minor changes in the acoustic environment.
  • the neural structure is designed as a single-layer feedback network which has two inputs E1, E2 and comprises two synapses, the limiting amplifiers 31 being provided in the signal paths of the inputs E1, E2 to the two outputs A1, A2 and each Output signal multiplied by a variable S ij and added to the respective other input signal, and furthermore the variable S ij is a function of the two output signals.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Automation & Control Theory (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Neurosurgery (AREA)
  • Otolaryngology (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Amplifiers (AREA)
  • Circuit For Audible Band Transducer (AREA)
EP94117795A 1994-11-10 1994-11-10 Prothèse auditive programmable Withdrawn EP0712261A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP94117795A EP0712261A1 (fr) 1994-11-10 1994-11-10 Prothèse auditive programmable
US08/515,907 US5754661A (en) 1994-11-10 1995-08-16 Programmable hearing aid

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP94117795A EP0712261A1 (fr) 1994-11-10 1994-11-10 Prothèse auditive programmable

Publications (1)

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EP0712261A1 true EP0712261A1 (fr) 1996-05-15

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EP94117795A Withdrawn EP0712261A1 (fr) 1994-11-10 1994-11-10 Prothèse auditive programmable

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US (1) US5754661A (fr)
EP (1) EP0712261A1 (fr)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998054928A2 (fr) * 1997-05-27 1998-12-03 Alexandrescu Eugene Prothese auditive a commutateur actionne par la tete
DE19844748A1 (de) * 1998-09-29 1999-10-07 Siemens Audiologische Technik Verfahren zum Bereitstellen einer Richtmikrofoncharakteristik und Hörgerät
US6044163A (en) * 1996-06-21 2000-03-28 Siemens Audiologische Technik Gmbh Hearing aid having a digitally constructed calculating unit employing a neural structure
EP1023647A1 (fr) * 1997-10-15 2000-08-02 Beltone Electronics Corporation Dispositif "neuroflou" pour prothese auditive programmable
WO2000076268A2 (fr) * 1999-06-02 2000-12-14 Siemens Audiologische Technik Gmbh Prothese auditive a systeme de microphone directionnel et procede permettant de faire fonctionner ladite prothese
DE19948907A1 (de) * 1999-10-11 2001-02-01 Siemens Audiologische Technik Verfahren zur Signalverarbeitung in einer Hörhilfe sowie Hörhilfe
US6674867B2 (en) 1997-10-15 2004-01-06 Belltone Electronics Corporation Neurofuzzy based device for programmable hearing aids
WO2022081260A1 (fr) * 2020-10-16 2022-04-21 Starkey Laboratories, Inc. Dispositif auditif doté de réseaux neuronaux dynamiques pour l'amélioration du son

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US6614914B1 (en) 1995-05-08 2003-09-02 Digimarc Corporation Watermark embedder and reader
US6611607B1 (en) 1993-11-18 2003-08-26 Digimarc Corporation Integrating digital watermarks in multimedia content
US5748763A (en) * 1993-11-18 1998-05-05 Digimarc Corporation Image steganography system featuring perceptually adaptive and globally scalable signal embedding
US6944298B1 (en) 1993-11-18 2005-09-13 Digimare Corporation Steganographic encoding and decoding of auxiliary codes in media signals
US6449377B1 (en) * 1995-05-08 2002-09-10 Digimarc Corporation Methods and systems for watermark processing of line art images
US6560349B1 (en) * 1994-10-21 2003-05-06 Digimarc Corporation Audio monitoring using steganographic information
US6760463B2 (en) * 1995-05-08 2004-07-06 Digimarc Corporation Watermarking methods and media
US6035177A (en) * 1996-02-26 2000-03-07 Donald W. Moses Simultaneous transmission of ancillary and audio signals by means of perceptual coding
EP0964603A1 (fr) * 1998-06-10 1999-12-15 Oticon A/S Procédé de traitement de signaux sonores et dispositif de mise en oeuvre du procédé
EP1133897B1 (fr) * 1998-11-24 2007-09-12 Phonak Ag Prothese auditive
EP1221276B1 (fr) 1999-10-14 2003-07-23 Phonak Ag Procede d'adaptation d'un appareil auditif, et appareil auditif
US6522988B1 (en) * 2000-01-24 2003-02-18 Audia Technology, Inc. Method and system for on-line hearing examination using calibrated local machine
US6633202B2 (en) 2001-04-12 2003-10-14 Gennum Corporation Precision low jitter oscillator circuit
US6937738B2 (en) 2001-04-12 2005-08-30 Gennum Corporation Digital hearing aid system
US7181034B2 (en) 2001-04-18 2007-02-20 Gennum Corporation Inter-channel communication in a multi-channel digital hearing instrument
DE60223869D1 (de) * 2001-04-18 2008-01-17 Gennum Corp Digitaler Quasi-Mittelwertdetektor
US20020191800A1 (en) * 2001-04-19 2002-12-19 Armstrong Stephen W. In-situ transducer modeling in a digital hearing instrument
US7113589B2 (en) * 2001-08-15 2006-09-26 Gennum Corporation Low-power reconfigurable hearing instrument
US7889879B2 (en) * 2002-05-21 2011-02-15 Cochlear Limited Programmable auditory prosthesis with trainable automatic adaptation to acoustic conditions
AUPS247002A0 (en) * 2002-05-21 2002-06-13 Hearworks Pty Ltd Programmable auditory prosthesis with trainable automatic adaptation to acoustic conditions
DE10347211A1 (de) * 2003-10-10 2005-05-25 Siemens Audiologische Technik Gmbh Verfahren zum Nachtrainieren und Betreiben eines Hörgeräts und entsprechendes Hörgerät
DK1691572T3 (da) * 2005-02-09 2019-10-21 Oticon As Fremgangsmåde og system til at træne et høreapparat ved anvendelse af en selvorganiserende kortlægning
EP1946609B1 (fr) * 2005-10-14 2010-05-26 GN ReSound A/S Optimisation de paramètres de prothèse auditive
WO2008154706A1 (fr) * 2007-06-20 2008-12-24 Cochlear Limited Procédé et appareil pour optimiser la commande de fonctionnement d'une prothèse auditive
US10129664B2 (en) * 2015-04-15 2018-11-13 Starkey Laboratories, Inc. User adjustment interface using remote computing resource
US11270198B2 (en) * 2017-07-31 2022-03-08 Syntiant Microcontroller interface for audio signal processing
JP2022514325A (ja) * 2018-12-21 2022-02-10 ジーエヌ ヒアリング エー／エス 聴覚デバイスにおけるソース分離及び関連する方法
DE102019206743A1 (de) * 2019-05-09 2020-11-12 Sonova Ag Hörgeräte-System und Verfahren zur Verarbeitung von Audiosignalen

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WO1993026037A1 (fr) * 1992-06-05 1993-12-23 United States Department Of Energy Procede destine a former des synapses dans des reseaux neuronaux et resistance pour lesdits reseaux
EP0579152A1 (fr) * 1992-07-13 1994-01-19 Minnesota Mining And Manufacturing Company Prothèse auditive, appareil de suppression de bruit et appareil de suppression de la réaction acoustique ayant un filtrage adaptatif focalisé

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Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6044163A (en) * 1996-06-21 2000-03-28 Siemens Audiologische Technik Gmbh Hearing aid having a digitally constructed calculating unit employing a neural structure
WO1998054928A3 (fr) * 1997-05-27 1999-03-04 Eugene Alexandrescu Prothese auditive a commutateur actionne par la tete
WO1998054928A2 (fr) * 1997-05-27 1998-12-03 Alexandrescu Eugene Prothese auditive a commutateur actionne par la tete
US6674867B2 (en) 1997-10-15 2004-01-06 Belltone Electronics Corporation Neurofuzzy based device for programmable hearing aids
EP1023647A1 (fr) * 1997-10-15 2000-08-02 Beltone Electronics Corporation Dispositif "neuroflou" pour prothese auditive programmable
EP1023647A4 (fr) * 1997-10-15 2000-12-06 Beltone Electronics Corp Dispositif "neuroflou" pour prothese auditive programmable
US7187778B2 (en) 1997-10-15 2007-03-06 Beltone Electronics Corporation Neurofuzzy based device for programmable hearing aids
DE19844748A1 (de) * 1998-09-29 1999-10-07 Siemens Audiologische Technik Verfahren zum Bereitstellen einer Richtmikrofoncharakteristik und Hörgerät
WO2000076268A2 (fr) * 1999-06-02 2000-12-14 Siemens Audiologische Technik Gmbh Prothese auditive a systeme de microphone directionnel et procede permettant de faire fonctionner ladite prothese
WO2000076268A3 (fr) * 1999-06-02 2001-05-17 Siemens Audiologische Technik Prothese auditive a systeme de microphone directionnel et procede permettant de faire fonctionner ladite prothese
US7324649B1 (en) 1999-06-02 2008-01-29 Siemens Audiologische Technik Gmbh Hearing aid device, comprising a directional microphone system and a method for operating a hearing aid device
DE19948907A1 (de) * 1999-10-11 2001-02-01 Siemens Audiologische Technik Verfahren zur Signalverarbeitung in einer Hörhilfe sowie Hörhilfe
WO2022081260A1 (fr) * 2020-10-16 2022-04-21 Starkey Laboratories, Inc. Dispositif auditif doté de réseaux neuronaux dynamiques pour l'amélioration du son

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US5754661A (en) 1998-05-19

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