Method for creating weakness indicator value of person by means of hearing device

Abstract

The invention relates to a method for creating a weakness indicator value (I0) of a person by means of a hearing device (1), in which first movement data (20) relating to a pass and / or fall is collected by means of at least one acceleration sensor (8a-c) of the hearing device (1), second data (22) relating to moisture, in particular data of electrical skin activity, is collected over the following time of a fall or fall by means of a skin sensor (14) of the hearing device (1) and / or by means of a skin sensor (14) of a first auxiliary device (36) that can be connected to the hearing device (1) in a data-based manner, the data makes it possible to specify information about physiological and / or psychological conditions over a temporal range of the fall or fall, and wherein a weakness indicator value (I0) is generated as a function of the first motion data (20) and as a function of second data (22) about moisture.

Description

Technical Field

[0001] The invention relates to a method for creating a weakness index value for a person by means of a hearing device. Background Art

[0002] It is very important for people with degenerative diseases or other muscle or nerve diseases, as well as elderly people with limited movement safety, to have an accurate report on their movement safety in daily life in order to be able to limit the health risks that may result from potential stumbles and falls.

[0003] Although the fall itself can be recorded with the aid of an acceleration sensor, data on the more detailed physiological conditions of the fall, that is to say in particular on the physical preconditions before the fall and on other reactions of the body to the fall, are often missing. Therefore, in many of the above-mentioned cases, measurements using only the data of an acceleration sensor (or an inertial measurement unit) are generally not suitable for reproducing the complete picture of the person's physical weakness. Summary of the invention

[0004] The object of the present invention is therefore to specify a measure for the frailty of a person which is particularly informative for elderly people or persons suffering from degenerative diseases or other muscle or nerve diseases.

[0005] According to the invention, the above technical problem is solved by a method for creating a weakness index value for a person by means of a hearing device, wherein first movement data about stumbling and / or falling are collected by at least one acceleration sensor of the hearing device, wherein second data about moisture, in particular data about the electrical skin activity of the person, are collected by a skin sensor of the hearing device (in particular a skin conductivity sensor) and / or by a skin sensor of a first auxiliary device that can be connected to the hearing device in a data-technical manner in the immediate time range of the stumbling or falling, the second data about moisture providing inferences about skin moisture, thereby enabling information about the physiological and / or psychological condition in the immediate time range of the stumbling or falling, and wherein the weakness index value is generated based on the first movement data and based on the second data about moisture. Advantageous embodiments that are considered in part to be inventive in themselves are the subject of the following description.

[0006] In this case, a hearing device generally includes a device that is configured to generate sound signals from electrical signals (which may also be generated from internal signals of the device) and to feed the hearing organ of the wearer of the device, i.e., in particular earphones (e.g., as "earbuds"), headphones, data glasses with loudspeakers, etc. However, hearing devices also include hearing aids in the narrow sense, i.e., devices for taking care of the hearing loss of the wearer, in which an input signal generated from an ambient signal by means of a microphone is processed into an output signal and amplified in particular in this case in a frequency band-dependent manner, and the output sound signal generated from the output signal by means of a loudspeaker, etc., is suitable for at least partially compensating the hearing loss of the wearer, in particular in a user-specific manner. In this case, the wearer is also the person for whom the weakness indicator value is created.

[0007] The first auxiliary device including the skin sensor can be designed in particular as a smart watch or data bracelet (in particular with a user interface), and can also be configured in particular to control functions of the hearing device via the user interface. Preferably, the first auxiliary device is arranged and configured to be worn by the wearer on both arms (in particular wrists) during normal use.

[0008] In this context, a frailty index value is to be understood in particular as a quantitative variable which provides information about the development of cognitive and / or cognitive motor impairment, the degree of dementia, a high risk of falling and / or a high probability of a decline in cognitive motor abilities over time. (Weakness) or Gebrechlichkeit (fragility) is to be understood in particular as a condition which is characterized by reduced physiological reserves and decreased resistance to stress due to a reduction in the function of several physiological systems, which is in particular accompanied by an increased risk of disability, hospitalization or even death.

[0009] A frailty index value is therefore also to be understood as a quantitative variable which indicates the probability and / or risk of a future fall.

[0010] In this case, the weakness index value can in particular be used to set emphasis on the assessment of stress before a fall or on the other hand on the assessment of stress after a fall. The weakness index value can in particular also be additionally related to the classification of a fall event by means of the first movement data, the classification of physiological preconditions and / or reactions according to the second data about moisture, and / or the time ratio of the relevant emphasis in the two mentioned data types.

[0011] In this case, the acceleration sensor generates in particular a signal with data about acceleration in at least one spatial direction and / or rotation about at least one axis. In particular, the data and therefore also first movement data about stumbling and / or falling are collected with the aid of an inertial measurement unit (IMU) of the hearing instrument, which is configured to interpret accelerations in all three spatial directions and rotations about any rotation axis in space. In particular, first movement data are to be understood as data of the acceleration sensor or IMU in which a specific event of stumbling or falling becomes apparent.

[0012] In this case, a fall may also be caused in particular by a stumble, i.e. a serious disturbance of normal walking, wherein the person may still resume the normal walking movement process when stumbling, without falling (i.e. completely reaching the ground). In this case, the time range immediately following a stumble and / or a fall may be given in particular by a time period that begins up to 1 minute, preferably up to 10 seconds, before the first detection of the first stumble or fall, and ends up to 5 minutes, preferably up to 1 minute after the stumble or fall has ended (given by the resumption of the normal walking movement or by reaching the ground).

[0013] The moisture of the skin is a reliable measure of physiological and psychological stress. It can be detected, for example, by means of skin conductivity measurement via electrodermal activity (EDA) using two measuring electrodes on the skin surface, which are arranged at a spacing of a few millimeters relative to each other. In the hearing device, the two measuring electrodes are preferably arranged on the surface of the hearing device in such a way that, when worn normally, the measuring electrodes are in contact with the skin surface in the ear or on the ear (for example behind the auricle) in the manner described. Now, second data about moisture (for example data about EDA) in the time range immediately following the stumble and / or fall can provide information about the detailed physiological and / or psychological condition in this time period, which can be used to generate a weakness indicator value. Another possibility is an optical measurement of the moisture of the skin, in particular by means of the intensity of scattered and reflected light, for example by means of an electro-optical microstructure sensor.

[0014] For example, when stumbling, the Achilles tendon reflex or the posterior tibial reflex initially starts without direct involvement of the brain, so that in the case of stumbling due to muscle disease or muscle weakness, the change, in particular the reduction, of EDA as a reaction to stumbling starts relatively late. In contrast, in the case of neurodegenerative diseases or systemic vertigo, the person usually already feels unsafe when walking, so that the EDA may have already decreased before stumbling or falling can be identified in the first movement data (sometimes a few seconds before).

[0015] In particular, a first time point is determined here at which the person's stumbling and / or falling begins based on first movement data from at least one acceleration sensor, wherein a second time point is determined based on second data about moisture at which the person is aware of the stumbling and / or falling, and wherein the time interval between the first time point and the second time point is taken into account for the weakness indicator value. If, for example, there is absolutely no measurable reaction of skin moisture or EDA, this may also be caused by a physiological abnormality, which can advantageously be reflected in the weakness indicator value.

[0016] Since, for example, EDA decreases due to pressure sensations, it is particularly advantageous to determine the weakness indicator value in such a way that the value increases the more severe and / or longer the decrease in the person's EDA after a stumble or a fall occurs.

[0017] Here, the skin sensor is preferably activated based on a stumble or fall detected in the first movement data, or based on other relevant movement situations, in particular climbing stairs, which are detected with the help of data collected by at least one acceleration sensor. This means that based on the data of the acceleration sensor (or IMU) with the help of a corresponding evaluation it is detected that a person is, for example, climbing stairs, which results in an increased risk of stumbling or falling, and the skin sensor is activated accordingly, or, for example, based on the first movement data of the acceleration sensor (or IMU), an already existing stumble or fall is detected and the skin sensor is immediately activated.

[0018] However, the skin sensor can also continuously collect data that provide inferences about the moisture of the skin, wherein only those of the data that were collected in the immediate time range of a stumble and / or a fall are then stored as second data about moisture for further use in the weakness indicator value and / or for further processing. That is, (in particular ex post) data associated with a stumble or a fall are selected from the continuously collected skin sensor data, which were identified by means of an evaluation of the first movement data.

[0019] Advantageously, the immediate temporal range of the stumble is divided into three phases, wherein, in particular, for a first phase immediately before the stumble or fall, and / or for a second phase during the stumble or fall, and / or for a third phase immediately after the stumble or fall, second data about the moisture content are respectively collected, these second data about the moisture content are respectively compared with reference values ​​for the relevant phase, for example by quotients or (if necessary standardized) differences, and wherein the comparison is used for the weakness indicator value. This means in particular that for each phase (according to the first phase of the detection), the EDA is respectively separately compared with the correspondingly stored reference value, and one or more values ​​are determined based on the comparison (for example by mathematical functions, if necessary also from a combination of multiple variables of the individual phases), and these one or more values ​​are used for the weakness indicator value.

[0020] Here, it is preferred that the first stage has a duration between 1 second and 1 minute immediately before the first sign of stumbling or falling, and / or the second stage has a duration from the end of the first stage until orderly walking movements are resumed or until the ground is reached (i.e., the fall ends), and / or the third stage has a duration from 1 second to 5 minutes immediately after the end of the second stage. In particular, for the first stage, the second data on moisture is detected by continuously collecting EDA, and the relevant data of the first stage is selected according to the stumbling or falling identified from the first motion data.

[0021] The false positive classification of a stumble or a fall as an event relevant to the weakness index value is advantageously detected based on the second data on moisture. This can be done, for example, by specifying a maximum value of the EDA, etc., which must be reached within the time range immediately following the stumble / fall and / or a minimum value of the change in the EDA. If this is not the case, the event is identified as a "false positive" and therefore as irrelevant, and the relevant first movement data and the second data on moisture are not used for the weakness index value.

[0022] Advantageously, a measure of the concentration of the person before stumbling or falling is determined based on the second data about moisture, and the measure for concentration is used for the weakness index value. For example, if the EDA has decreased before stumbling or falling, it can be inferred from this that the person is mentally stressed. Then, preferably, it is additionally assumed that stress is accompanied by an increase in concentration. Then, in particular, falls that occur despite increased concentration can be specifically weighted for the weakness index value.

[0023] It has proven to be further advantageous that the first movement data contain at least one information item of the following type about stumbling or falling: intensity, duration, height difference, position change, severity, and / or the second data item about moisture contain at least one data item of the following type about skin electrical activity within a given time period: maximum value, minimum value, average value, time integral. Such data types are easy to collect and require few resources for further processing and storage. In this case, the intensity of the fall is characterized in particular by the height difference and pulse change and / or duration and possible subsequent falls (e.g. on stairs), wherein the severity of the fall may depend in particular on the intensity and additional acoustic properties, such as the sound of falling or the sound of crying out in pain, which acoustic properties are preferably detected by an acoustic input transducer (e.g. microphone) of the hearing device and are evaluated and recognized accordingly.

[0024] In another advantageous embodiment, a weakness indicator value is determined in the immediate time range of a stumble or a fall from the first movement data and from the second data about moisture, and then output and / or stored, or the first movement data and the second data about moisture are stored together with a time index, and a weakness indicator value at a later time point is generated based on the stored first movement data and the second data about moisture. That is, in the first case mentioned, the first movement data and the second data about moisture collected in the immediate time range of a stumble or a fall are also processed immediately (i.e. in particular after the end of the data collection without a further delay) as a weakness indicator value, which is then transmitted to the person via a second auxiliary device (e.g. a smartphone) connected to the hearing device and / or can be stored in the hearing device itself and / or in the second auxiliary device for long-term monitoring. In the second case mentioned, it is directly the data itself (first movement data and the second data about moisture) collected about the stumble or the fall, which are stored together with the corresponding time stamp for further processing into a weakness indicator value later.

[0025] That is, in the second case, the event of stumbling or falling is clearly separated in time from the process of generating the weakness index value. Nevertheless, in another possible design for better control (e.g. by medical experts), in the first case mentioned, the raw data about stumbling or falling (i.e. the first movement data and the second data about moisture) can also be stored together even if they have been directly further processed into a weakness index value.

[0026] Here, it is preferred to consider using multiple events of stumbling and / or falling for the weakness index value, wherein in particular, the time accumulation of events and / or the change of the time distribution of events and / or the higher weight of recent events are used. By using multiple events of stumbling or falling for the weakness index value, the weakness index value is more statistically convincing. The time accumulation of events, that is, in particular the increase, can then indicate a possible, generally negative development at the personnel, and therefore it may be necessary to consult a doctor or the like about this. In the case of suitable function construction, this accumulation of events or generally the change of the time distribution of events can be reflected in the weakness index value. In particular, this can be achieved by a higher weighting of recent events, because relatively more frequent and / or more severe events in the recent period (i.e., for example, more severe falls) thus drive the weakness index value to rise continuously through a stronger weighting.

[0027] Preferably, the weakness indicator value is determined in the hearing device based on the first movement data and on the second data about moisture, or the first movement data and at least part of the second data about moisture from the hearing device (and, if necessary, the second movement data from the first auxiliary device) are transmitted to the second auxiliary device that can be connected to the hearing device in a data-technical manner, wherein the weakness indicator value is calculated at least partially on the second auxiliary device. That is, in the first case mentioned, the calculation is performed only in the hearing device based on the mentioned data. This is particularly advantageous in the case of the above-mentioned immediate calculation of the weakness indicator value in time (i.e. without further delay). In the second case, for example, the data can be preprocessed in the hearing device (e.g. sorting according to relevance, data types in the first movement data and the second data about moisture as described above, false alarm detection as described, the above-mentioned temporal division into stages, etc.), and the data preprocessed in this way are transmitted to the auxiliary device for final processing as a weakness indicator value.

[0028] The invention further relates to a hearing system comprising a hearing device and being configured to carry out the method described above. The hearing system can comprise a first auxiliary device, such as a smart watch or a data bracelet, which can be connected to the hearing device in a data-technical manner and comprises the skin sensor. Preferably, the hearing system also comprises a second auxiliary device, such as a smart phone, which can be connected to the hearing device in a data-technical manner, wherein the second auxiliary device is configured to carry out a part of the method, in particular to transmit second data about moisture, such as about the EDA of the person, from the hearing device to the auxiliary device.

[0029] The hearing system according to the invention shares the advantages of the method according to the invention. The advantages given for the method and for its developments can also be transferred to the hearing system.

[0030] Furthermore, the invention relates to a use of a hearing device for creating a weakness indicator value for a person, wherein first movement data about stumbling and / or falling are collected by at least one acceleration sensor of the hearing device, wherein second data about moisture are collected in the time range immediately following the stumbling or falling by a skin sensor of the hearing device and / or by a skin sensor of a first auxiliary device that can be connected to the hearing device in a data-technical manner, the second data about moisture providing inferences about skin moisture, thereby enabling information about the physiological and / or psychological condition in the time range of the stumbling or falling to be provided, and wherein the weakness indicator value is generated based on the first movement data and based on the second data about moisture. In the case where the skin sensor is arranged in the first auxiliary device, the invention particularly relates to the use of a hearing device and an auxiliary device that can be connected to the hearing device in a data-technical manner for creating a weakness indicator value for a person.

[0031] The aforementioned use of the hearing system according to the invention shares the advantages of the method according to the invention. The advantages given for the method and for its developments can also be transferred to the use of the hearing system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. Here, they are schematically shown respectively:

[0033] Figure 1 A hearing aid with an IMU and EDA sensor for creating a weakness index value is shown in a block circuit diagram,

[0034] Figure 2 The block diagram shows the timeline by following Figure 1 a method for creating a weakness index value for a hearing aid, and

[0035] Figure 3 shows the method for executing Figure 2 A hearing system with a hearing aid, a data bracelet and a smartphone according to an alternative embodiment of the method.

[0036] Parts and variables which correspond to one another are provided with the same reference symbols in all the figures. DETAILED DESCRIPTION

[0037] exist Figure 1 Schematically in a block circuit diagram, a hearing device 1 is shown, which is designed here as a hearing aid 2 for taking care of the hearing loss of a wearer (not shown). However, the hearing device 1 can also be a conventional earphone, for example a so-called "earphone".

[0038] The hearing aid 2 has a microphone M1, which generates an input signal E1 from ambient sounds, not shown in detail. In addition, the hearing aid 2 has a control unit 4, which has a signal processor 6, and the control unit 4 is particularly configured to process the input signal E1 in a user-specific manner according to the hearing requirements of the wearer, in particular amplifying and / or compressing it according to frequency bands. Here, the processing of the input signal E1 generates an output signal A1, which is converted into an output sound signal, not shown in detail, by the loudspeaker L1 of the hearing aid 2. As an alternative or in addition, the hearing aid can also have a bone conduction earpiece (not shown). Here, the hearing aid can also have other microphones (not shown), which generate additional input signals from ambient sounds, and the aforementioned signal processing is performed on these additional input signals, wherein directional processing can also be performed with the help of directional microphones.

[0039] The hearing aid 2, which is designed as a BTE device (“Behind The Ear”) here, has an IMU, which includes three acceleration sensors 8a-c and three rotation speed sensors 10a-c. The IMU is configured to be able to characterize the wearer's movements as comprehensively and completely as possible, wherein the IMU outputs a motion signal 12 to the control unit 4. In the IMU, the raw data of the three acceleration sensors 8a-c and the three rotation speed sensors 10a-c can already be preprocessed, so that the motion signal 12 already gives the specific direction of movement (and / or the rotation axis and rotation direction in space) and the intensity (speed) of the movement. However, the motion signal 12 can also include the raw data of the mentioned acceleration sensors 8a-c and rotation speed sensors 10a-c, so that the direction of movement and / or the direction of rotation and the associated speed are determined in the control unit 4.

[0040] Furthermore, the hearing aid 2 has a skin sensor, which is designed here as a skin conductivity sensor 14 and comprises a first measuring electrode 16a and a second measuring electrode 16b and is configured to measure the EDA of the wearer when the hearing aid 2 is normally worn and the skin conductivity sensor 14 is activated. In particular, for this purpose, the two measuring electrodes 16a / b are embedded in the side wall of the housing of the hearing aid to be worn behind the ear, which side wall faces the scalp or at least partially contacts the scalp when worn. The skin conductivity sensor 14 is particularly configured to output a very weak voltage to the contacting skin via one of the two measuring electrodes 16a / b, which are preferably only a few milliseconds apart from each other, and to measure the voltage drop occurring over a few millimeters on the skin surface via the remaining measuring electrodes 16a / b. Furthermore, the skin conductivity sensor 14 is configured to output an EDA signal 18 to the control unit 14. As an alternative to the skin conductivity sensor 14 (not shown), in particular optical sensors such as electro-optical microstructure sensors can also be used, which allow the moisture of the skin to be determined via the intensity of reflected and scattered light.

[0041] The control unit 4 is configured to detect whether the wearer has stumbled or even fallen based on the motion signal 12 (pre-processed or based on raw data). The data of the motion signal 12 detected in the immediate time range of the stumble or fall are further used as first motion data (not shown in detail) in a manner to be described in detail to provide quantitative variables that enable information to be provided about the detailed conditions of the stumble or fall and the possible risk of recurrence. For these detailed conditions, the EDA signal 18 is also used.

[0042] exist Figure 2 The flow of the following method is schematically shown in a block diagram relative to a time line T, wherein the method is based on Figure 1 The motion signal 12 and the EDA signal 18 generate the weakness index value I0. The processing depicted below the dashed line is no longer shown according to the time sequence given by the time line.

[0043] At a first point in time T1, the user of the hearing aid 2 stumbles. This results in correspondingly detectable data or data changes in the motion signal 12 of the IMU, which are referred to as first motion data 20. These first motion data 20 are therefore given by the data in the motion signal 12, or by the orientation data preprocessed in the IMU as described, or by corresponding representative and therefore analyzable emphasis in the raw data of the IMU.

[0044] The analysis of the movement signal 12, and thus of the first movement data 20, which is preferably carried out in the control unit 4, now indicates a stagger that started at the time T1. Therefore, when a stagger is detected, the skin conductivity sensor 14 is immediately activated so that a more accurate physiological and psychological condition, in particular the stress level of the user (i.e. the wearer) of the hearing aid 2 can be detected via the EDA. In order to activate the skin conductivity sensor 14 as early as possible, a very high sensitivity can be selected so that signal components in the movement signal 12 that could potentially represent the initial branch of a stagger already lead to activation, so that early signal components with valuable information about the EDA are not missed due to excessively high confidence requirements.

[0045] Here, the skin conductivity sensor 14 detects second data 22 about moisture in the EDA signal 18 , which can provide information about the physiological and psychological conditions during staggering and can be used together with the first movement data 20 to generate the weakness index value I0 .

[0046] In the present exemplary embodiment, at time T2, the initial stumble turns into a fall, i.e., the user of the hearing aid 2 is no longer able to correctly resume a normal walking movement, and a fall occurs. At time T3, relatively shortly after time T2, the fall ends, since the user of the hearing aid 2 has now reached the ground. The fall and the end of the fall can also be detected in the first movement data 20 based on a representative data pattern (e.g., by an increasing acceleration in the negative z-direction, which then ends abruptly), and are therefore correspondingly identified in the analysis of the first movement data 20.

[0047] In the present case, the second data 22 about moisture are analyzed separately in three different time phases with respect to the fall: Here, the first phase P1 starts immediately (i.e. only immediately after the time point T1) with the activation of the skin conductivity sensor 14 and thus with the detection of the EDA signal 18, and lasts until the actual fall at the time point T2. The second phase P2 is given by the time from the actual fall to the ground at the time point T3, and the third phase P3 is immediately after the fall at the time point T3 and ends at the time point T4 after a predetermined time interval, which can in particular be between 1 second and 5 minutes. For the three individual phases P1, P2, P3, the second data 22-1, 22-2 and 22-3 about moisture detected during them are analyzed separately.

[0048] This can be done, for example, in the following way, that is, from the second data 22-1, 22-2 and 22-3 of the EDA about moisture detected after the phases P1-P3 (which actually reproduce the conductivity, i.e. the reverse resistance), one or more specific standardized data types 22sd (e.g. maximum value, minimum value, average value or integral) are formed. In this case, minimum values ​​22-1m, 22-2m and 22-3m and average values ​​22-1av, 22-2av and 22-3av are formed. Now, for the relevant phases P1, P2, P3 and data types, these standardized data types 22sd are compared with the corresponding reference values ​​R-1m, R-2m, R-3m or R-1av, R-2av, R-3av.

[0049] Now, for the weakness index value I0, the comparison can be used, for example, in the form of a quotient or a difference. Here, the mathematical expression of the weakness index value I0 can take into account, for example, the decrease in EDA caused by pressure. If this decrease is particularly severe (see minimum value) or particularly long (average value, second and third stages P2, P3), the stress level is particularly high. Now, based on the severity of the fall, it can be inferred that the user of the hearing aid 2, for example, did not expect this fall or did not fully expect this fall, and his body's reaction to the fall (such as the reflex of the Achilles tendon reflex) also surprised himself. For this, in particular, information 24 about the fall, such as intensity, duration, height difference reached and / or changes in body position, can be determined based on the first movement data 20, so that, for example, a significantly severe reaction in the case of a relatively mild fall can be detected. Here, the information 24 can also be used for the weakness index value I0.

[0050] Furthermore, when constructing the frailty index value I0, it may be considered that the stronger and / or longer the EDA determined in the second data on moisture is, the larger the frailty index value I0 is.

[0051] Furthermore, a measure 26 of the attentiveness of the user of the hearing aid 2 can be determined from the second data 22 about moisture. If, for example, the attentiveness in the phase immediately before a fall (identifiable by the corresponding second data 22-1 about moisture) is significantly too low, this can indicate, for example, an increased risk of falling, which can also be used in the calculation of the weakness index value I0 (i.e., in particular in the mathematical construction of the weakness index value I0).

[0052] In addition, it is possible to determine when the user is aware of the fall, i.e., notice the fall, based on the second data 22 about moisture, and for the calculation of the weakness index value I0, the time interval between this time point (not shown) and the time point T2 when the fall begins can also be considered (i.e., in particular, the weakness index value I0 is constructed accordingly).

[0053] Here, in the present embodiment, the first motion data 20 and the second data 22 about moisture are used for the weakness index value I0 immediately after the collection is completed (i.e., in particular, immediately after the collection of the second data 22-3 about moisture in the third stage P3), i.e., for example, at a time point TI0 shortly after the time point T4. Here, the weakness index value I0 can be directly formed as a mathematical function from the data about falling at the time point T2 (solid line).

[0054] However, the weakness index value I0 can also take into account earlier events such as stumbling and / or falling (not shown). Here, the weakness index value I0 can be formed, for example, as a continuous average, a weighted average or a recursive average of temporary characteristic parameters. The temporary characteristic parameter K0 of the current event (stumbling / falling) is formed by the first motion data 20 and the second data 22 about moisture in the manner described above (dashed line). Subsequently, similar characteristic parameters Kj of earlier events are used to average to form the weakness index value I0, or the last existing weakness index value I0 is used for recursive averaging and corresponding updates. Here, in particular, the temporal cumulative components of the relevant events can be included in the weighting together, so that, for example, when falling occurs with increased frequency and / or severity, a larger value is assigned to the weakness index value I0.

[0055] according to Figure 2 A particularly preferred alternative design possibility for the method shown for creating a weakness index value is in particular provided by continuous detection of EDA by means of a skin conductivity sensor 14, wherein, when a stumble and / or a fall is detected by the movement signal 12 or the first movement data 20, the relevant data of the EDA signal 18 are used as second data 22 about moisture (or second data 22-1, 22-2, 22-3 about moisture for the individual stages P1-P3).

[0056] Here, the first movement data 20 and the second data 22 about moisture (or the second data about moisture in the phases P1-P3), and / or the associated standardized data types 22sd, such as maximum values, minimum values, average values ​​or integrals, and / or their comparison with associated reference values, and / or information 24 about falls, such as intensity, duration, height difference reached or changes in body position, can be stored for later final further processing into a weakness indicator value I0. Preferably, at least part of this later further processing is carried out in an auxiliary device, such as a smartphone, which can be connected to the hearing aid 2. Particularly preferably, the preprocessed variables, such as the standardized data 22sd and, if necessary, their associated reference values, can also be transmitted to the auxiliary device and stored there (preferably together with a time index).

[0057] exist Figure 3, a corresponding hearing system 30 for preferably implementing, in particular, these alternative designs is shown in a schematic block diagram. In this case, the hearing system 30 comprises a hearing aid 2 and a first auxiliary device 36, which is designed as a data bracelet 38, by means of which the “real” hearing aid 2 can be controlled and, in the present case, comprises an IMU. The hearing system 30 also comprises a second auxiliary device 32, which is designed as a smartphone 34. In this case, the preprocessing of the movement signal 12, for example for detecting a stumble or a fall, can be performed directly in the data bracelet 38, and the corresponding first movement data 20 and / or the information 24 about stumbling / falling can be transmitted to the smartphone 34. Therefore, the following signal can also be transmitted to the hearing aid 2, which is used to activate the skin conductivity sensor 14, or (in the case of continuous activation) to transmit the data detected from the first stage P1 before the stumble / fall to the third stage P3 after the stumble / fall in the EDA signal 18 as second data 22 about moisture (if necessary after preprocessing to a standardized data type 22sd) to the smartphone 34. The weakness index value I0 can then be determined there from the first movement data 20 or information 24 and from the second data about moisture or the standardized data type 22sd. In particular, the data can be stored on the smartphone for this purpose and processed into the weakness index value I0 in time separately from the stumble / fall (for example by means of temporary characteristic variables K0, Kj). However, in Figure 3 In the embodiment shown in FIG. 1 , the frailty index value I0 can also be directly and immediately calculated.

[0058] Although the present invention has been further shown and described in detail through preferred embodiments, the present invention is not limited to the disclosed examples, and other variations may be derived by those skilled in the art without departing from the scope of protection of the present invention.

[0059] Reference numerals list

[0060] 1 Hearing equipment

[0061] 2 Hearing aids

[0062] 4 Control unit

[0063] 6 Signal Processor

[0064] 8a-c Acceleration sensor

[0065] 10a-c Speed ​​sensor

[0066] 12 Motion Signal

[0067] 14 Skin sensor, skin conductivity sensor

[0068] 16a / b First / second measuring electrode

[0069] 18 EDA signals

[0070] 20 First Sports Data

[0071] 22 Second data about water content

[0072] 22-1 / 2 / 3 Second data on moisture in the first / second / third phase

[0073] 22-1 / 2 / 3m Minimum value of the second data on moisture

[0074] 22-1 / 2 / 3av Average value of the second data on moisture

[0075] 22sd Standardized data types

[0076] 24 Information (about falls)

[0077] 26 Measuring User Attention

[0078] 30 Hearing System

[0079] 32 Second auxiliary equipment

[0080] 34 Smartphone

[0081] 36 First Auxiliary Equipment

[0082] 38 Data bracelet

[0083] A1 Output Signal

[0084] E1 Input Signal

[0085] I0 Weakness index value

[0086] IMU Inertial Measurement Unit

[0087] K0,Kj temporary characteristic parameters

[0088] L1 Speaker

[0089] M1 Microphone

[0090] P1 / 2 / 3 First / Second / Third Stage

[0091] R-1 / 2 / 3av reference value (for average value)

[0092] R-1 / 2 / 3m Reference value (for minimum value)

[0093] T Timeline

[0094] T1-4 time point

Claims

1. A method for creating a weakness index value (I0) of a person by means of a hearing device (1), in, collecting first movement data (20) about stumbling and / or falling by means of at least one acceleration sensor (8a-c) of the hearing device (1), wherein second moisture data (22) are collected in the immediate time frame of a stumble or a fall by means of a skin sensor (14) of the hearing device (1) and / or by means of a skin sensor (14) of a first auxiliary device (36) which can be connected to the hearing device (1) in a data-intensive manner, the second moisture data providing conclusions about skin moisture, thereby enabling information about a physiological and / or psychological condition to be provided in the immediate time frame of the stumble or the fall, and The weakness index value (I0) is generated according to the first exercise data (20) and according to the second data (22) on water content.

2. The method according to claim 1, in, collecting the first movement data (20) by means of an inertial measurement unit (IMU) of the hearing device (1), and / or wherein the second data (22) about moisture is collected as data of skin electrical activity by means of a skin conductivity sensor as a skin sensor (14), and / or The second data (22) about moisture are collected as skin reflectivity data by means of an optical sensor as a skin sensor (14).

3. The method according to claim 1 or claim 2, in, The skin sensor (14) is activated based on a stumble or a fall detected in the first movement data (20) or based on other relevant movement situations that are detected with the aid of data collected by at least one acceleration sensor (8a-c).

4. The method according to any one of the preceding claims, in, The skin sensor (14) continuously collects data giving an inference about the moisture of the skin, and In this case, only those of the data which were collected in the immediate time range of the stumble and / or the fall are stored as second data (22) about moisture and / or are further processed.

5. The method according to any one of the preceding claims, in, for a first stage (P1) immediately before stumbling or falling, and / or for a second stage (P2) during stumbling or falling, and / or for a third stage (P3) immediately after stumbling or falling, respectively collecting second data (22-1, 22-2, 22-3) on moisture, comparing the second data on moisture with reference values ​​(R-1m, R-2m, R-3m, R-1av, R-2av, R-3av) for the relevant stages (P1, P2, P3), respectively, and Therein, the comparison is applied to the frailty index value (I0).

6. The method according to claim 5, in, The first phase (P1) has a duration between immediately following the first sign of staggering and up to 1 second and 1 minute before staggering, and / or wherein the second phase (P2) has a duration from the end of the first phase (P1) until orderly walking movements are resumed or until the ground is reached, and / or Therein, the third phase (P3) has a duration of 1 second to 5 minutes immediately after the end of the second phase (P2).

7. The method according to any one of claims 2 to 6, in, The weakness index value (I0) is determined in such a way that the more severe and / or longer the decrease in the electrical skin activity of a person after stumbling or falling, the greater the value.

8. The method according to any one of the preceding claims, in, False positive classification of stumbling or falling as an event associated with the weakness index value (I0) is detected based on the second data (22) regarding moisture.

9. The method according to any one of the preceding claims, in, A measure (26) for the concentration of the person before stumbling or falling is determined based on the second data (22) about moisture, and the measure (26) for concentration is used for the weakness index value (I0).

10. The method according to any one of the preceding claims, in, determining a first point in time (T1) at which a person stumbles and / or falls based on first movement data (20) from at least one acceleration sensor (8a-c), wherein a second time point is determined based on second data (22) about moisture, at which second time point the person is aware of stumbling and / or falling, and Therein, the time interval between the first time point and the second time point is considered for the frailty index value (I0).

11. The method according to any one of the preceding claims, in, The probability and / or risk of future falls is generated as a frailty index value (I0).

12. The method according to any one of claims 2 to 11, in, The first movement data (20) includes at least one of the following types of information (24) about stumbling or falling: intensity, duration, height difference, position change, severity, and / or The second data (22) on moisture contains at least one data type (22sd) on skin electrical activity of the following types within a given time period: maximum value, minimum value (22-1m, 22-2m, 22-3m), average value (22-1av, 22-2av, 22-3av), and time integral.

13. The method according to any one of the preceding claims, in, Determining the weakness index value (I0) based on the first movement data (20) and based on the second data (22) about water content within a time range immediately following a stumble or a fall, and then outputting and / or storing it, or The first motion data (20) and the second data on moisture (22) are stored together with a time index, and a weakness index value (I0) at a later time point is generated based on the stored first motion data (20) and the second data on moisture (22).

14. The method according to claim 13, in, Consider multiple events of stumbling and / or falling for use in the frailty index value (I0), and Therein, the temporal accumulation of events and / or the change in the temporal distribution of events and / or a higher weighting of recent events are used.

15. The method according to any one of the preceding claims, in, determining a weakness index value (I0) in the hearing device (1) based on the first movement data (20) and based on second data (22) about moisture, or Therein, at least a portion of the first movement data (20) and / or the second data (22) on moisture are transmitted from the hearing device (1) to a second auxiliary device (32), and the weakness index value (I0) is calculated at least partially on the second auxiliary device (32).

16. The method according to any one of the preceding claims, in, The weakness index value (I0) is calculated at least partially with the aid of an artificial neural network, which uses the first movement data (20) and / or second data (22) on moisture and / or pre-processed data derived therefrom as input variables.

17. A method according to any one of the preceding claims, in, Second data (22) about moisture are collected by a skin sensor (14) of a first auxiliary device (36) which can be connected to the hearing device (1) in a data-technical manner and which is worn on the arm of a person in normal use.

18. A hearing system (30) comprising a hearing device (1) and configured for performing the method according to any one of the preceding claims.

19. The hearing system (30) according to claim 18, further comprising: a first auxiliary device (36) which can be connected to the hearing device (1) in a data-based manner, the first auxiliary device comprising a skin sensor (14), and / or A second auxiliary device (36) which can be connected to the hearing device (1) in a data-technology manner, wherein the second auxiliary device (32) is configured to carry out a part of the method according to any one of claims 1 to 16.

20. The hearing system (30) according to claim 18 or 19, in, A first auxiliary device (36) including a skin sensor (14) is configured to be worn on the arm of a person in normal use.

21. Use of a hearing device (1) for creating a weakness index value (I0) of a person, in, collecting first movement data (20) about stumbling and / or falling by means of at least one acceleration sensor (8a-c) of the hearing device (1), wherein second moisture data (22) are collected in the immediate time frame of a stumble or a fall by means of a skin sensor (14) of the hearing device (1) and / or by means of a skin sensor (14) of a first auxiliary device (36) which can be connected to the hearing device (1) in a data-intensive manner, the second moisture data providing conclusions about skin moisture, thereby enabling information about a physiological and / or psychological condition to be provided in the immediate time frame of the stumble or the fall, and The weakness index value (I0) is generated according to the first exercise data (20) and according to the second data (22) on water content.

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