Method for operating a hearing device and hearing device

Abstract

A hearing device has an acceleration sensor that is positioned on the head of a hearing device wearer in the intended worn state, is configured for measurement in two mutually orthogonal measurement axes and is operated by virtue of at least one main feature related to an acceleration directed tangentially in relation to the head being derived from an acceleration signal of the acceleration sensor. The at least one main feature is used to ascertain a presence of a yaw movement of the head by taking into consideration at least one prescribed criterion, derivable from the acceleration signal itself, beyond the presence of an acceleration value of the tangentially directed acceleration that is indicative of a movement.

Claims

1. A method for operating a hearing device, the method comprising the following steps: providing a hearing device having an acceleration sensor to be positioned on the head of a hearing device wearer in an intended worn state and being configured for measurement in two mutually orthogonal measurement axes; deriving at least one main feature related to an acceleration directed tangentially in relation to the head from an acceleration signal of the acceleration sensor; and using the at least one main feature to ascertain a presence of a yaw movement of the head by taking into consideration at least one prescribed criterion, beyond a presence of an acceleration value of the tangentially directed acceleration, being indicative of a movement derivable from the acceleration signal itself; the at least one main feature is at least one of: a time characteristic of the tangentially directed acceleration, or a correlation coefficient between a time derivative of the tangentially directed acceleration and a radially directed acceleration, or a curve of a graph in which the tangential acceleration is plotted against a radial acceleration; and the prescribed criterion being used is at least one of: whether the time characteristic of the tangentially directed acceleration has two oppositely directed local extremes in succession within a prescribed movement time window, or a level of the correlation coefficient, or a geometric shape of the curve.

2. The method according to claim 1, wherein: one supplementary feature derived from the acceleration signal is a time characteristic of an acceleration directed radially in relation to the head; and the prescribed criterion being used is whether the time characteristic of the radially directed acceleration assumes a local extreme within the prescribed movement time window.

3. The method according to claim 1, wherein: the at least one main feature ascertained by using the time characteristic of the tangentially and optionally a radially directed acceleration is a movement intensity; and the prescribed criterion being used is a level of the movement intensity.

4. The method according to claim 3, wherein the movement intensity being ascertained is at least one of a movement duration or a total energy or a mean energy contained in the tangentially and radially directed acceleration.

5. The method according to claim 1, which further comprises using the correlation coefficient or an arithmetic sign of the correlation coefficient to ascertain a yaw direction.

6. The method according to claim 1, which further comprises checking the prescribed criterion as to whether the curve of the graph approximates an ellipsoidal shape.

7. The method according to claim 1, which further comprises using a direction of rotation of the curve to ascertain a yaw direction.

8. The method according to claim 1, which further comprises ascertaining the at least one main feature and optionally a supplementary feature in a moving manner over a time window overlapping a subsequent time window.

9. The method according to claim 1, which further comprises ascertaining a value of a yaw angle from the acceleration signal only if the presence of the yaw movement is detected.

10. The method according to claim 1, which further comprises filtering at least one of constant or linear measured value components out of the acceleration signal.

11. The method according to claim 1, which further comprises applying a classification algorithm to the at least one main feature and optionally to a supplementary feature to determine the presence or at least a probability of the presence of the yaw movement.

12. The method according to claim 1, which further comprises ascertaining a spatial area of interest of the hearing device wearer over a prescribed period based on the yaw movement.

13. The method according to claim 1, which further comprises using information about the yaw movement of the head of the hearing device wearer for customizing a signal processing algorithm for a group conversation situation.

14. The method according to claim 1, which further comprises referencing a zero degree line of vision of the hearing device wearer based on at least one of a nodding movement of the head, a vertical movement of the hearing device wearer or a forward movement of the hearing device wearer.

15. The method according to claim 1, which further comprises using an output of a movement classifier as an additional criterion for ascertaining the yaw movement.

16. The method according to claim 1, which further comprises placing the acceleration sensor in or on the hearing device in such a way that one of the measurement axes of the acceleration sensor is at least approximately oriented tangentially relative to the head.

17. A hearing device, comprising: an acceleration sensor to be positioned on the head of a hearing device wearer in an intended worn state, said acceleration sensor being configured for measurement in two mutually orthogonal measurement axes and for supplying an acceleration signal; and a processor connected to said acceleration sensor and configured to perform the following method steps: deriving at least one main feature related to an acceleration directed tangentially in relation to the head from the acceleration signal of said acceleration sensor; and using the at least one main feature to ascertain a presence of a yaw movement of the head by taking into consideration at least one prescribed criterion, beyond a presence of an acceleration value of the tangentially directed acceleration, being indicative of a movement derivable from the acceleration signal itself; the at least one main feature is at least one of: a time characteristic of the tangentially directed acceleration, or a correlation coefficient between a time derivative of the tangentially directed acceleration and a radially directed acceleration, or a curve of a graph in which the tangential acceleration is plotted against a radial acceleration; and the prescribed criterion being used is at least one of: whether the time characteristic of the tangentially directed acceleration has two oppositely directed local extremes in succession within a prescribed movement time window, or a level of the correlation coefficient, or a geometric shape of the curve.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

(1) FIG. 1 is a diagrammatic, longitudinal-sectional view of a hearing device with a schematic circuit diagram;

(2) FIG. 2 is a top-plan view of a head of a hearing device wearer with the hearing device worn on the ear as intended;

(3) FIG. 3 is a flow chart for a method for operating the hearing device that is performed by a processor of the hearing device;

(4) FIGS. 4 and 5 each show a graph for features derived from an acceleration signal plotted against time;

(5) FIGS. 6 and 7 each show a graph in which a radial acceleration is plotted against a tangential acceleration, for a characteristic of the acceleration;

(6) FIG. 8 is a graph for the time characteristic of a yaw angle of the head of the hearing device wearer; and

(7) FIG. 9 is a polar diagram for a histogram of the yaw angle.

DETAILED DESCRIPTION OF THE INVENTION

(8) Referring now in detail to the figures of the drawings, in which mutually corresponding parts and variables are always provided with the same reference signs, and first, particularly, to FIG. 1 thereof, there is seen a hearing device 1, specifically a so-called behind-the-ear hearing device. The hearing device 1 includes a (hearing device) housing 2 in which multiple electronic components are disposed. The hearing device 1 includes two microphones 3 as electronic components configured for detecting sounds from the surroundings of the hearing device 1. In addition, the hearing device 1 includes a signal processor 4 as an electronic component. The signal processor is configured to process the sounds captured through the use of the microphones 3 and to output them to a loudspeaker 5 for output to the ear of a hearing device wearer. In order to detect the physical position of the hearing device 1, the latter additionally includes an acceleration sensor 6 interconnected with the signal processor 4. There is additionally a battery 7 disposed in the housing 2 for the purpose of supplying power to these electronic components. The battery is specifically formed by a storage battery in the present exemplary embodiment. In order to conduct the sound produced by the loudspeaker 5 to the ear of the hearing device wearer, the housing 2 has a sound tube 8 connected to it that, in the intended worn state on the head 9, specifically on the ear of the hearing device wearer (see FIG. 2), is inserted into the auditory canal of the hearing device wearer with an ear mold 10.

(9) The acceleration sensor 6 is configured for three-dimensional measurement and, to this end, has three mutually orthogonal measurement axes x, y and z (see FIG. 2). In this case, the acceleration sensor 6 is disposed in the housing 2 of the hearing device 1 in such a way that the measurement axis z coincides with the vertical direction in the intended worn state on the head 9 and when the body posture of the hearing device wearer is upright. The measurement axis x is oriented tangentially in relation to the head 9 and forwardi.e. along a zero degree line of vision 12in this case. The measurement axis y is directed radially away from the head 9. The two measurement axes x and y are also in a horizontal plane when the body posture of the hearing device wearer is upright. On the basis of this configuration, the measured values associated with the measurement axis x reproduce an acceleration directed tangentially in relation to the head 9 (subsequently referred to as tangential acceleration at). The measured values associated with the measurement axis y accordingly reproduce an acceleration directed radially in relation to the head 9 (subsequently referred to as radial acceleration ar).

(10) The signal processor 4 is configured to use an acoustic classifier, implemented in the signal processor 4 as an algorithm, to infer a conversation situation (i.e. a conversation by at least two people) from the sounds captured through the use of the microphones 3 and then to customize the signal processing accordingly. By way of example, this involves an apex angle of a directional microphone formed through the use of the two microphones 3 being set in such a way that all voice components arriving at the microphones 3 from the surroundings, specifically the source locations of these voice components, lie within the apex area of the directional microphone. In order to be able to customize the signal processing even more precisely in such a conversation situation, specifically in order to be able to adjust the apex angle in such a way that only the people actually involved in the conversation (who each are a source location of a voice component) are within the apex area of the directional microphone, the signal processor 4 performs a method that is explained in more detail below.

(11) In a first method step 20, the measured values ascertained by the acceleration sensor 6which are output in groups of in each case three measurement values, each of which is in turn associated with one of the measurement axes x, y and zare stored in a buffer store (which is integrated in the signal processor 4). The buffer store is in this case configured for moving buffer-storage of eight such measured value groups. In a subsequent method step 30, multiple features are derived (also: extracted) from the measured values associated with the respective measurement axes x, y and z. These features are supplied, in a further method step 40, to a classifier in which a classification algorithmin the form of a Gaussian mixture mode model in the present exemplary embodimentis implemented. This classifier uses the features derived in method step 30 to ascertain whether the hearing device wearer turns his or her head 9, i.e. rotates it at least approximately about the measurement axis z. Such sideways rotation of the head 9 is referred to hereinbelow as a yaw movement.

(12) In the configuration and orientation depicted for the acceleration sensor 6 in the present exemplary embodiment, the measurement axis z is thus a so-called yaw axis. Accordingly, the measurement axis x is a roll axis about which the hearing device wearer inclines his or her head 9 to the side, and the measurement axis y is a nod axis about which the hearing device wearer inclines his or her head 9 downward or upward (nodding; analogous to the terms yaw, roll and pitch).

(13) In parallel with method steps 30 and 40 described above, a method step 50 involves the measured values of the acceleration sensor 6 that are stored in the buffer store being purged of steady-state and, in comparison with the duration of a head movement, only slowly changing influences. The influence of the gravitational pull, which can be assumed to be in a steady-state, is removed through the use of a high pass filter in this case. Further influences leading to an offset in the measured values, for example an anatomically dependent deviation in the actual yaw axis from the vertical and/or the actual orientation of the measurement axis z, are removed, in one exemplary embodiment, by subtracting the temporal average of the buffer measured values from the respective single measured value. Influences with a linear effect (i.e. linear trends) are removed by so-called detrending.

(14) If a method step 55 involves the classifier outputting the result that there is a yaw movement of the head 9, a further method step 60 involves a value of a yaw angle W being determined from the ascertained measured values, specifically from the tangential acceleration at. That is to say that the amount by which the hearing device wearer has turned his or her head 9 is ascertained (see FIG. 8).

(15) The information regarding whether there is a yaw movement and through what yaw angle W the head 9 is turned is used in a method step 70 to perform a statistical analysis. This involves ascertaining how often the hearing device wearer turns his or her head 9 within a prescribed time window. Additionally, the values of the yaw angle W that are associated with the individual yaw movements are used to create a histogram, from which it is possible to read the directionsreferenced to the zero degree line of vision 12in which the hearing device wearer has turned his or her head 9 in the prescribed time window (see FIG. 9). The frequency distribution of the individual directions can also be used to read a spatial distribution of the area of interest of the hearing device wearer from this histogram.

(16) In a further method step 80, the information generated in method steps 60 and 70 is used by the signal processor 4 to additionally customize the signal processing. Specifically, this method step 80 involves the information of the acoustic classifier described above and of the movement analysis described above being fused through the use of the acceleration sensor 6 so as to allow more precise customization of the signal processing to a conversation situation. In one exemplary embodiment, specifically the apex angle of the directional microphone, the orientation of the directional cone of the directional microphone and the position of a so-called notch are customized further, if need be delimited further in comparison with a setting proposed solely by the acoustic classifier, on the basis of the informationnamely of the yaw angle W and of the histogramascertained through the use of the acceleration sensor 6.

(17) In a first exemplary embodiment, method step 30 involves one main feature ascertained being a time characteristic at(t) of the tangential acceleration at. The supplementary feature ascertained is a time characteristic ar(t) of the radial acceleration ar. In method step 40, one criterion considered for the presence of the yaw movement is whether the time characteristic at(t) of the tangential acceleration at assumes two local extremes Mt having opposite arithmetic signs, which indicate two opposite accelerations, namely an actual acceleration and a slowing-down, within a prescribed time period, subsequently referred to as movement time window Zb, having a duration of one second. In addition, the criterion also involves consideration of whether the time characteristic ar(t) of the radial acceleration ar assumes a local extreme Mr, indicating a head movement with an acceleration component directed radially in relation to the head 9, within the movement time window Zb. FIG. 4 depicts, in exemplary fashion, the time characteristics at(t) and ar(t) for a yaw movement of the head 9 to the right (see seconds 0.5-1.5) and to the left (see seconds 2-3), in each case. For the yaw movement to the right, the time characteristic at(t) thereforedue to the orientation of the measurement axis x forwardinitially passes through the positive extreme Mt, which indicates the beginning of the yaw movement, and subsequently passes through the negative extreme Mt, which indicates the slowing-down of the head 9 at the end of the yaw movement. In parallel, the time characteristic ar(t)due to the orientation of the measurement axis y to the outsidelikewise shows a positive extreme Mr within the movement time window Zb due to the centrifugal force. The response is accordingly converse for the yaw movement to the left, as can be taken from the right-hand half of FIG. 4. If such a manifestation of the main feature and of the supplementary featurei.e. as depicted between seconds 0.5 and 1.5 or 2 and 3is detected in method step 40, the classifier outputs, in method step 55, that there is a yaw movement. Without the extreme Mr in the time characteristic ar(t), that is to say without an actually present radial acceleration ar, there is, for example, only a movement of the head 9 or of the hearing device wearer directed straightforward.

(18) In a further exemplary embodiment, method step 30 involves the main feature determined being a correlation coefficient K between a time derivative of the tangential acceleration at, specifically the time characteristic at(t) thereof, and the radial acceleration ar, specifically the time characteristic ar(t) thereof. This is depicted in more detail in FIG. 5. The timing of the change in the tangential acceleration at, specifically a temporal extreme Md in this change, which can be seen from the time derivative of the tangential acceleration at, coincidesas can be seen from FIG. 5for a yaw movement of the head 9 at least approximately with that of the extreme Mr in the radial acceleration ar. Therefore, the value of the correlation coefficient Kspecifically the level of the absolute value thereofreveals whether there is a yaw movement at all. It is additionally possible to read the direction of the yaw movement from the arithmetic sign of the correlation coefficient K. For the yaw movement to the right depicted between seconds 0.5-1.5 in FIG. 5, the value of the correlation coefficient K is approximately 0.75. For the yaw movement to the left depicted between seconds 2-3, the correlation coefficient K is approximately 0.8.

(19) In a further exemplary embodiment, explained on the basis of FIGS. 6 and 7, method step 30 involves the main feature produced being a curve D of a graph in which the radial acceleration ar is plotted against the tangential acceleration at. In the subsequent method step 40, the criterion used is the shape of this curve D. Specifically, consideration is given to whether the curve D can be approximated to the shape of an ellipse. In this case, the measured values for the yaw movement to the right are plotted in FIG. 6 and to the left are plotted in FIG. 7, with the measured values also forming the basis for the preceding FIGS. 4 and 5. The depicted offset between the respective start and end (the latter marked by an upside-down triangle) is caused by a crooked head posture in this case. As a result, the shape of the curve D also differs from the ideal circular shape and instead corresponds to an oval or an ellipse. If the curve D has such a shape, the classifier infers the presence of the yaw movement in method step 40 and outputs a corresponding result in method step 55.

(20) In yet a further exemplary embodiment (not depicted in more detail), method step 30 involves the main feature ascertained being a movement intensity I. This is portrayed in this case by the energy contained in the tangential and the radial acceleration. The movement intensity I in this case is estimated on the basis of the averaged vector normals of the respective vector of the tangential and radial acceleration at and ar. By way of example, the energy is estimated in this case through the use of a temporally discrete sum of the vector length of the resulting vector of the tangential and radial acceleration at and ar.

(21) FIG. 8 depicts the time characteristic of the values of the yaw angle W ascertained in method step 60 in exemplary fashion.

(22) FIG. 9 depicts the histogram ascertained in method step 70 in the form of a polar diagram in exemplary fashion. From the polar diagram, it is specifically possible to use the radial length of the shaded areas to read how often or for how long the hearing device wearer has turned his or her head 9 in a specific angle range. From this, it is in turn possible to derive a spatial area of interest, which is used in method step 80 to set the apex angle of the directional microphone accordingly. In this specific example, there is a conversation between the hearing device wearer and two people, one directly opposite and one offset to the left by approximately 20-25 degrees.

(23) In an optional exemplary embodiment, a method step 90 (see dashed depiction in FIG. 3) involves a so-called movement classifier being used to infer a movement situation of the hearing device wearer, i.e. a movement state of the entire body or an activity including the movement state, from the features ascertained in method step 30. By way of example, method step 90 involves ascertaining whether the hearing device wearer is at rest or for example is riding a bicycle. If the hearing device wearer is at rest, the probability of the hearing device wearer taking part in a conversation with multiple third persons is also higher. If he or she is riding a bicycle, the probability of him or her taking part in such a conversation is comparatively low. In that case, the ascertainment of the yaw movement in method step 40 and the subsequent method steps 60-80 optionally do not take place.

(24) In a further optional exemplary embodiment, method step 55 involves the classifier also outputting the (temporal) duration of the yaw movement and optionally also the level of the yaw movement, specifically the movement intensity I.

(25) In a further exemplary embodiment, not depicted in more detail, a further method step involves a reset being performed, i.e. referencing of the zero degree line of vision 12, whenever an almost pure nodding movement takes place, which is indicative of drinking, for example. As a result, the histogram can be produced particularly precisely and robustly, sinceeven in the case of undetected yaw movementsthe zero degree line of vision 12 can be repeatedly found and this prevents the individual values of the yaw angle W from adding up and thus the incorrect assumption that the zero degree line of vision 12 is changing.

(26) The subject matter of the invention is not restricted to the exemplary embodiments described above. Rather, further embodiments of the invention can be derived from the description above by a person skilled in the art. In particular, the individual features of the invention described on the basis of the different exemplary embodiments, and the refinement variants of those individual features, can also be combined with one another in another way. By way of example, in a further exemplary embodiment, method step 40 involves all of the features described above, specifically the main features and the supplementary feature, being checked for whether they satisfy the respective criterion.

(27) The following is a summary list of reference numerals and the corresponding structure used in the above description of the invention.

LIST OF REFERENCE SIGNS

(28) 1 Hearing device 2 Housing 3 Microphone 4 Signal processor 5 Loudspeaker 6 Acceleration sensor 7 Battery 8 Sound tube 9 Head 10 Ear mold 12 Zero degree line of vision 20 Method step 30 Method step 40 Method step 50 Method step 55 Method step 60 Method step 70 Method step 80 Method step at Tangential acceleration ar Radial acceleration at(t) Time characteristic ar(t) Time characteristic K Correlation coefficient D Curve I Movement intensity Mt, Mr, Md Extreme W Yaw angle Zb Movement time window x, y, z Measurement axis