Method for creating a frailty indicator score for a person using an auditory instrument

Abstract

The invention describes a method for generating a frailty indicator value (I0) of a person using a hearing instrument (1), wherein at least one accelerometer (8a-c) of the hearing instrument (1) collects first motion data (20) relating to a stumble and / or fall, wherein a skin sensor (14), in particular a skin conductance sensor, collects second moisture-related data (22), in particular data relating to electrodermal activity, in the immediate temporal environment of the stumble or fall, which provide information about physiological and / or psychological circumstances in the temporal environment of the stumble or fall, and wherein the frailty indicator value (I0) is generated on the basis of the first motion data (20) and on the basis of the second moisture-related data (22).

Description

[0001] The invention relates to a method for establishing a frailty indicator value of a person using a hearing instrument.

[0002] For people with degenerative or other muscle or nerve diseases, but also for elderly people with limited mobility, it is important to have precise information about the safety of their movements in everyday life in order to be able to limit the health risk that could result from potential tripping and falling.

[0003] While accelerometers can be used to document a fall itself, data on the specific physiological circumstances of the fall are often missing, particularly on physical preconditions prior to the fall, but also on other body reactions to the fall. A measure that uses only data from accelerometers (or an inertial measurement unit) is therefore usually unsuitable in many of the aforementioned cases to provide a complete picture of the person's situation with regard to their vulnerability.

[0004] The invention is therefore based on the object of specifying a measure of a person's weakness, which is particularly meaningful for people of advanced age or people with degenerative or other muscle or nerve diseases.

[0005] The stated object is achieved according to the invention by a method for creating a frailty indicator value for a person using a hearing instrument, wherein first movement data relating to a stumbling and / or falling are collected by at least one acceleration sensor of the hearing instrument, wherein second moisture-related data, in particular data relating to an electrodermal activity of the person, are collected by a skin sensor, in particular a skin conductivity sensor, in the immediate temporal environment of the stumbling or falling, which provide an indication of skin moisture and thereby enable information to be obtained about physiological and / or psychological circumstances in the temporal environment of the stumbling or falling, and wherein the frailty indicator value is generated based on the first movement data and the second moisture-related data.Advantageous and partly inventive embodiments are the subject of the dependent claims and the following description.

[0006] A hearing instrument generally includes any device that is designed to generate a sound signal from an electrical signal - which can also be provided by an internal signal of the device - and to supply it to the ear of a wearer of this device, i.e. in particular a pair of headphones (e.g. as an "earbud"), a headset, data glasses with a loudspeaker, etc. A hearing instrument also includes a hearing aid in the narrower sense, i.e. a device for treating a wearer with a hearing impairment, in which an input signal generated from an ambient signal by means of a microphone is processed into an output signal and is amplified in particular in a frequency band-dependent manner, and an output sound signal generated from the output signal by means of a loudspeaker or similar is suitable, in particular in a user-specific manner, to at least partially compensate for the wearer's hearing impairment.

[0007] The hearing instrument can also have an additional “external unit” such as a smartwatch or a data bracelet (in particular with a user interface), in which at least one acceleration sensor is possibly arranged.

[0008] A frailty indicator value is defined as any quantitative value that provides information about the degree of cognitive and / or cognitive-motor impairment, dementia, a high risk of falls, and / or a high probability of a decline in cognitive-motor skills over time. The technical term "frailty" (probably best translated as "weakness" or "frailty") is understood in particular as a syndrome characterized by reduced physiological reserve and reduced resilience to stressors due to a functional decline of multiple physiological systems, which is associated with an increased risk of disability, hospitalization, and even death. A frailty indicator value is therefore also understood to be a quantitative value that indicates a probability and / or a risk of a future fall.

[0009] The frailty indicator value can, in particular, focus on assessing stress before a fall, on the one hand, or on assessing stress after a fall, on the other. The frailty indicator value can, in particular, also depend on a classification of the fall event based on the first movement data, a classification of the physiological precondition and / or reaction based on the second humidity-related data, and / or the temporal relationship between relevant fluctuations in the two aforementioned data types.

[0010] The acceleration sensor generates, in particular, a signal with data about an acceleration in at least one spatial direction and / or a rotation about at least one axis. In particular, said data, and thus also the first movement data regarding stumbling and / or falling, are collected using an inertial measurement unit (IMU) of the hearing instrument, which is configured to resolve accelerations in all three spatial directions and rotations about any rotational axis in space. In particular, the first movement data are to be understood as data from the acceleration sensor or IMU in which a specific event of stumbling or falling is evident.

[0011] A fall can be triggered in particular by a stumble, i.e., a significant disruption of normal walking, whereby the person still has the opportunity to restore normal walking motion while stumbling instead of falling (i.e., striking the ground completely). The immediate temporal context of the stumble and / or fall can be defined in particular by a period that begins up to one minute, preferably up to ten seconds, before the first stumble or the first recognition of the fall, and ends up to five minutes, preferably up to one minute, after the end of the stumble or fall (given by the resumption of normal walking motion or by striking the ground).

[0012] Skin moisture is a reliable measure of physiological and psychological stress. It can be measured via electrodermal activity (EDA) using skin conductance measurements, for example, with two measuring electrodes placed on the skin surface a few millimeters apart. In a hearing instrument, these two measuring electrodes are preferably arranged on the surface of the hearing instrument in such a way that, when worn as intended, the measuring electrodes in or on the ear (e.g., behind the auricle) are in contact with the skin surface as described. The second moisture-related data (e.g., EDA data) in the immediate temporal context of the trip and / or fall can provide information about the specific psychological and / or physiological circumstances during this period, which can be used to generate the frailty indicator value.Another possibility is an optical measurement of skin moisture, in particular via the intensity of scattered and reflected light, e.g. via an electro-optical microstructure sensor.

[0013] For example, when someone stumbles, the Achilles tendon reflex or the posterior tibial reflex initially engages without direct involvement of the brain, so that in the case of a stumble in myopathy or myasthenia, a change, particularly a reduction in EDA in response to the stumble, occurs comparatively late. In a neurodegenerative disease or general dizziness, however, a person usually already feels unsteady while walking, so EDA may already be reduced before a stumble or fall is detectable in the initial movement data (sometimes by several seconds).

[0014] In particular, a first point in time at which the person begins to stumble and / or fall is determined based on the first movement data of the at least one acceleration sensor. A second point in time at which the person becomes aware of stumbling and / or falling is determined based on the second moisture-related data. A time interval between the first and second points in time is taken into account for the frailty indicator value. If, for example, there is absolutely no measurable reaction of the skin moisture or the EDA, this may also be caused by a physiological abnormality, which can advantageously be reflected in the frailty indicator value.

[0015] Since, for example, EDA is reduced by the perception of stress, it is particularly advantageous if the frailty indicator value is determined in such a way that the value increases the more and / or the longer the person's EDA is reduced after the trip or fall.

[0016] Preferably, the skin sensor is activated based on a tripping or falling detected in the first movement data, or based on another relevant movement situation, in particular climbing stairs, which is detected using the data collected by at least one acceleration sensor. This means that, based on a corresponding evaluation, it is detected from the data of the acceleration sensor (or the IMU) that the person is currently climbing stairs, for example, and thus there is an increased risk of tripping or falling, which is why the skin sensor is activated, or that, for example, an already occurring tripping or falling is detected from the first movement data of the acceleration sensor (or the IMU), and the skin sensor is immediately activated.

[0017] However, the skin sensor can also continuously collect data that provides information about skin moisture levels. Of these data, only those collected in the immediate temporal vicinity of a trip and / or fall are stored and / or further processed as second moisture-related data for further use in the frailty indicator value. From the continuously collected data of the skin sensor, those data related to a trip or fall are selected (particularly retrospectively), which is identified based on an evaluation of the first movement data.

[0018] Advantageously, the immediate temporal environment of the tripping is divided into three phases, with second moisture-related data being recorded for a first phase immediately before the tripping or falling and / or for a second phase during the tripping or falling and / or for a third phase immediately after the tripping or falling, which are then compared with a reference value for the corresponding phase, e.g. using a quotient or a (possibly standardised) difference, and with the said comparison being used for the frailty indicator value. This means in particular that for individual phases (the first phase depending on the recording), the EDA is compared separately with correspondingly stored reference values, and from the comparison (e.g. using a mathematical function, if necessaryalso from several variables for the combination of the individual phases) one or more numerical values ​​are formed, which are used for the frailty indicator value.

[0019] Preferably, the first phase lasts between one second and one minute immediately before the first sign of a trip or fall, and / or the second phase lasts from the end of the first phase until the patient regains orderly walking movement or reaches the ground (i.e., the fall has ended), and / or the third phase lasts from one second to five minutes immediately after the end of the second phase. In particular, the second moisture-related data for the first phase are acquired by continuously collecting the EDA, and the relevant data of the first phase are selected based on a trip or fall detected from the first movement data.

[0020] Ideally, a false positive classification of a trip or fall as an event relevant for the frailty indicator value is detected based on the second humidity-related data. This can be achieved, for example, by specifying a maximum value or similar for an EDA and / or a minimum value for a change in the EDA, which must be reached in the immediate temporal vicinity of the trip / fall. If this is not the case, the event is identified as a "false positive" and thus irrelevant, and the associated first movement data and second humidity-related data are not used for the frailty indicator value.

[0021] Advantageously, the second humidity-related data is used to determine a measure of the person's alertness prior to the trip or fall, and the alertness measure is used for the frailty indicator value. For example, if the EDA is already reduced before the trip or fall, this can be inferred from the person's mental tension. Preferably, it is then additionally assumed that the tension is accompanied by increased alertness. Falls despite increased alertness can then be given special weighting, especially for the frailty indicator value.

[0022] It is also advantageous if the first movement data contain at least one piece of information of the following type about a stumble or fall: an intensity, a duration, a difference in altitude, a change in position, a degree of severity, and / or if the second moisture-related data contain at least one piece of data of the following type with regard to electrodermal activity over a given period of time: a maximum, a minimum, an average value, a time integral. Such data types are easy to collect and require few resources for further processing and storage. The intensity of the fall is particularly determined by a difference in altitude and a change in momentum and / or duration as well as possible subsequent falls (e.g.B: on a staircase), whereby the severity of a fall can depend in particular on the strength as well as on additional acoustic features such as falling or pain noises, which are preferably recorded via an acoustic input transducer (e.g. a microphone) of the hearing instrument and are evaluated and recognized accordingly.

[0023] In a further advantageous embodiment, the frailty indicator value is determined in the immediate temporal environment of the tripping or falling based on the first movement data and the second humidity-related data, and is then output and / or stored, or the first movement data and the second humidity-related data are stored together with a time index, and the frailty indicator value is generated at a later point in time based on the stored first movement data and the second humidity-related data. In the former case, the first movement data and second humidity-related data, which were recorded in the immediate temporal environment of the tripping or falling, are output and / or stored.In the latter case, the data collected regarding the tripping or falling event are also processed immediately (i.e., in particular, without any further delay after the completion of the data collection) into a frailty indicator value, which can then be output to the person via an auxiliary device connected to the hearing instrument (such as a smartphone) and / or stored in the hearing instrument itself and / or said auxiliary device for longer-term monitoring. In the latter case, the data collected regarding the tripping or falling event itself (first movement data and second moisture-related data) are stored together with a corresponding time stamp for later processing into the frailty indicator value.

[0024] In the second case, the event of the trip or fall is clearly separated in time from the process of generating the frailty indicator value. Nevertheless, in another possible configuration, for better monitoring (e.g., by medical specialists), the raw data on the trip or fall (i.e., first movement data and second moisture-related data) can also be stored in the first case, even if further processing to generate the frailty indicator value has already taken place immediately.

[0025] Preferably, a plurality of stumbling and / or falling events are taken into account for the frailty indicator value, whereby in particular a temporal accumulation of the events and / or a change in the temporal distribution of the events and / or a higher weighting of more recent events is used. A plurality of stumbling or falling events makes the frailty indicator value more statistically meaningful. A temporal accumulation, in particular an increase in events, can then indicate a possible, generally negative development in the person, so that they should consult a doctor or similar. This accumulation or general change in the temporal distribution of events can be reflected in the frailty indicator value with a suitable functional construction. In particular, this can be achieved by giving more recent events a higher weighting, as this would then reflect relatively more frequent and / or more serious events (e.g.more severe falls) have recently been able to increase the frailty indicator value due to the greater weighting.

[0026] Preferably, the frailty indicator value is determined in the hearing instrument based on the first movement data and the second humidity-related data, or at least parts of the first movement data and the second humidity-related data are transmitted from the hearing instrument to said auxiliary device that can be connected to the hearing instrument via data technology, wherein the calculation of the frailty indicator value is carried out at least partially on the auxiliary device. In the first case, the calculation is carried out based on the said data exclusively in the hearing instrument. This is particularly advantageous for the aforementioned immediate calculation of the frailty indicator value (i.e., without further delay). In the second case, the data can be preprocessed in the hearing instrument (e.g., sorting according to relevance, a data type as described above from the first movement data or the second humidity-related data, false positive detection as described above).temporal division into phases, etc.), and the pre-processed data are transferred to the auxiliary device for final processing into the frailty indicator value.

[0027] The invention further mentions a hearing system which comprises a hearing instrument and which is designed to carry out the method described above.

[0028] The hearing instrument can comprise an external unit, such as a smartwatch or a data bracelet, in which, in particular, the at least one acceleration sensor can be arranged. Preferably, the hearing system further comprises an auxiliary device, such as a smartphone, that can be connected to the hearing instrument for data purposes. The auxiliary device is configured to carry out parts of the method, for which purpose, in particular, the second humidity-related data, for example, relating to the person's EDA, is transmitted from the hearing instrument to the auxiliary device.

[0029] The hearing system according to the invention shares the advantages of the method according to the invention. The advantages stated for the method and its further developments can be applied analogously to the hearing system.

[0030] An embodiment of the invention is explained in more detail below with reference to the accompanying drawings, each of which shows schematically: Fig. 1 in a block diagram a hearing aid with an IMU and an EDA sensor for creating a frailty indicator value, Fig. 2 in a block diagram against a timeline a method of a frailty indicator value using the hearing aid according to Fig. 1, and Fig. 3 a hearing system with a hearing aid, a data bracelet and a smartphone for carrying out an alternative embodiment of the method according to Fig. 2

[0031] Corresponding parts and sizes are provided with the same reference numerals in all figures.

[0032] In Fig. Figure 1 schematically shows a block diagram of a hearing instrument 1, which in this case is designed as a hearing aid 2 for treating a hearing impairment of a wearer (not shown). However, the hearing instrument 1 could also be a normal pair of headphones, such as a so-called "earbud."

[0033] The hearing aid 2 has a microphone M1, which generates an input signal E1 from ambient sound (not shown in detail). The hearing aid 2 also has a control unit 4 with a signal processor 6, which is configured, among other things, to process the input signal E1 in a user-specific manner according to the wearer's audiological requirements, and in particular to amplify and / or compress it frequency band by frequency band. By said processing of the input signal E1, an output signal A1 is generated, which is converted by a loudspeaker L1 of the hearing aid 2 into an output sound signal (not shown in detail). Alternatively or additionally, the hearing aid can also have a bone conduction receiver (not shown).The hearing aid can also have additional microphones (not shown) which generate additional input signals from the ambient sound which are included in the aforementioned signal processing, whereby directional processing can also be carried out using directional microphones.

[0034] The hearing aid 2, which in this case is designed as a BTE ("Behind The Ear") device, has an IMU comprising three acceleration sensors 8a-c and three yaw rate sensors 10a-c. The IMU is configured to characterize the wearer's movements as comprehensively and completely as possible, with the IMU outputting a movement signal 12 to the control unit 4. In the IMU, the raw data from the three acceleration sensors 8a-c and the three yaw rate sensors 10a-c can be preprocessed such that the movement signal 12 already indicates a specific direction of movement (and / or axis and direction of rotation in space) as well as the strength (speed) of the movement. However, the movement signal 12 can also comprise said raw data from the aforementioned acceleration and yaw rate sensors 8a-c, 10a-c, so that the movement and / or rotation direction and associated speed are only determined in the control unit 4.

[0035] The hearing aid 2 further comprises a skin sensor, which in this case is configured as a skin conductivity sensor 14, and which comprises a first measuring electrode 16a and a second measuring electrode 16b, and is configured to measure an EDA of the wearer when the hearing aid 2 is worn as intended and the skin conductivity sensor 14 is activated. In particular, for this purpose, the two measuring electrodes 16a / b are embedded in a side wall of a housing of the hearing aid, which is to be worn behind the ear, such that when worn, the side wall faces the scalp or at least partially touches it. The skin conductivity sensor 14 is configured, in particular, 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 mm apart, and to measure the voltage drop that occurs across the few mm of skin surface via the remaining measuring electrode 16a / b.The skin conductivity sensor 14 is further configured to output an EDA signal 18 to the control unit 4. As an alternative (not shown) to the skin conductivity sensor 14, an optical sensor, e.g., an electro-optical microstructure sensor, could also be used, which allows the determination of skin moisture via the intensity of reflected and scattered light.

[0036] The control unit 4 is configured to detect, based on the movement signal 12 (either preprocessed or from the raw data), whether the wearer has tripped or even fallen. The data from the movement signal 12, which was recorded in the immediate temporal vicinity of the trip or fall, is further used as initial movement data (not shown in detail) in a manner to be described below to provide a quantitative value that provides information about the specific circumstances of the trip or fall and, if applicable, the risk of recurrence. The EDA signal 18 is also used for these specific circumstances.

[0037] In Fig. 2 is a schematic block diagram showing the sequence of a method based on the motion signal 12 and the EDA signal 18 according to Fig. 1 generates a frailty indicator value I0. Processes drawn below the dashed line are no longer represented according to the timeline.

[0038] At a first time T1, a user of the hearing aid 2 stumbles. This leads to correspondingly detectable data or data changes in the motion signal 12 of the IMU, which shall be referred to as first motion data 20. This first motion data 20 is thus determined by the data in the motion signal 12, either by the directional data preprocessed in the IMU as described, or by corresponding characteristic and thus analyzable deflections in the raw data of the IMU.

[0039] An analysis of the movement signal 12 and thus of the first movement data 20, preferably carried out in the control unit 4, now reveals a stumble beginning at time T1. Consequently, the skin conductivity sensor 14 is activated immediately upon detection of the stumble in order to be able to record the more precise physiological and psychological conditions, in particular their stress level, via the EDA of the user (i.e., the wearer) of the hearing aid 2. For the earliest possible activation of the skin conductivity sensor 14, a very high sensitivity can be selected so that any signal component in the movement signal 12 that could potentially represent an initial offshoot of a stumble already leads to activation, so as not to miss early signal components containing valuable information for the EDA due to excessively high confidence requirements.

[0040] The skin conductivity sensor 14 records second moisture-related data 22 in the EDA signal 18, which can provide information about the said physiological and psychological circumstances during stumbling and which, together with the first movement data 20, can be used to generate the frailty indicator value I0.

[0041] In the present exemplary embodiment, the initial stumble becomes a fall at a time T2, i.e., the user of the hearing aid 2 can no longer properly regain normal walking motion and falls. At time T3, which is comparatively shortly after time T2, the fall ends, as the user of the hearing aid 2 has now reached the ground. The fall and the aforementioned end of the fall can also be detected in the first movement data 20 based on characteristic data patterns (e.g., through increased acceleration in the negative z-direction, which then ends abruptly), and are consequently recognized accordingly in the analysis of the first movement data 20.

[0042] In the present case, the second humidity-related data 22 relating to the fall are analyzed separately in three different temporal phases: A first phase P1 begins immediately with the activation of the skin conductivity sensor 14 and thus the recording of the EDA signal 18 (i.e., only slightly after time T1) and lasts until the start of the actual fall at time T2. A second phase P2 is defined by the time during the actual fall until impact with the ground at time T3, and a third phase P3 immediately follows the fall at time T3 and ends after a predetermined period of time, which can in particular be between one second and five minutes, at time T4. For each of the three phases P1, P2, P3, the second humidity-related data 22-1, 22-2, and 22-3 recorded during each phase are analyzed separately.

[0043] This can be achieved, for example, by forming one or more specific standardized data types 22sd, such as a maximum, a minimum, a mean, or an integral, from the second humidity-related data 22-1, 22-2, and 22-3 of the EDA (which represent an electrical conductivity, i.e., an inverse resistance) recorded after phases P1-P3. In this case, minima 22-1m, 22-2m, and 22-3m, as well as mean values ​​22-1av, 22-2av, and 22-3av, are formed. These standardized data types 22sd are then compared with the respective reference values ​​R-1m, R-2m, R-3m or R-1av, R-2av, R-3av for the respective phases P1, P2, P3, and data types.

[0044] The aforementioned comparisons, for example in the form of quotients or differences, can now be used for the frailty indicator value I0. A mathematical formulation of the frailty indicator value I0 can, for example, take into account that stress causes a decrease in EDA. If this decrease is particularly severe (see minimum) or particularly long (mean, second and third phases P2, P3), the stress level is particularly high. Depending on the severity of the fall, it can now be concluded that the user of the hearing aid 2 did not anticipate this fall or did not sufficiently anticipate it, and that his physical reaction to it (reflexes such as the Achilles tendon reflex) surprised him. For this purpose, information 24 about the fall can be determined, such as the strength, duration, an achieved difference in altitude and / or a change in body position, for exampleto specifically detect particularly violent reactions in comparatively moderate falls. Information 24 can also be used for the frailty indicator value I0.

[0045] Furthermore, when constructing the frailty indicator value I0, it can be taken into account that this value increases the stronger and / or the longer the EDA determined in the second moisture-related data is.

[0046] Furthermore, a measure 26 for the attentiveness of the user of the hearing aid 2 can be determined based on the second humidity-related data 22. If, for example, the attentiveness (detectable via the corresponding second humidity-related data 22-1 of the phase immediately before the fall) is significantly too low, this may indicate a fundamentally increased risk of falling, which can also be used in the calculation of the frailty indicator value I0 (i.e., in particular, in its mathematical construction).

[0047] Furthermore, the second humidity-related data 22 can be used to determine when the user becomes aware of falling, i.e. notices the fall, and the time interval between this point in time (not shown) and the point in time T2 at which the falling begins can also be taken into account for the calculation of the frailty indicator value I0 (i.e., in particular, the frailty indicator value I0 can be constructed accordingly).

[0048] In the present exemplary embodiment, the first movement data 20 and second humidity-related data 22 are used for the frailty indicator value I0 immediately after the complete collection (i.e., in particular, immediately after the collection of the second humidity-related data 22-3 of the third phase P3), i.e., approximately at a time TI0 shortly after the time T4. The frailty indicator value I0 can be directly calculated as a mathematical function from the aforementioned data on the fall at the time T2 (solid lines).

[0049] However, the frailty indicator value I0 can also take into account previous events (not shown) such as tripping and / or falling. In this case, the frailty indicator value I0 can be calculated, for example, as a running, weighted or recursive average of a preliminary parameter. The preliminary parameter K0 of a current event (trip / fall) is calculated in the manner described above from the first movement data 20 and the second humidity-related data 22 (dashed lines). This is followed by averaging using comparable parameters Kj of previous events to calculate the frailty indicator value I0, or a recursive averaging with the most recently available frailty indicator value I0, and a corresponding update. In particular, a component of the temporal accumulation of relevant events can be included in the weighting, so that, for example,the frailty indicator value I0 is assigned a higher numerical value if the falls occur with increasing frequency and / or severity.

[0050] Particularly preferred alternative design options to the Fig. 2 are provided in particular by a continuous detection of the EDA by the skin conductivity sensor 14, wherein when a stumbling and / or falling is detected from the movement signal 12 or the first movement data 20, the associated data of the EDA signal 18 are used as second moisture-related data 22 (or 22-1, 22-2, 22-3 for the individual phases P1-P3).

[0051] In this case, the said first movement data 20 and second humidity-related data 22 (or in phases P1-P3), and / or the associated standardized data types 22sd such as maximum, minimum, mean, or integral and / or their comparison with the associated reference values, and / or information 24 on the fall, such as severity, duration, achieved height difference, or change in body position, can be stored for later, final processing to obtain the frailty indicator value I0. Preferably, at least part of such subsequent processing takes place in an auxiliary device connectable to the hearing aid 2, such as a smartphone. Particularly preferably, preprocessed variables such as the said standardized data 22sd and, if applicable, their associated reference values ​​can also be transmitted to the auxiliary device and stored there (preferably together with a time index).

[0052] A corresponding hearing system 30 for the preferred implementation of these alternative embodiments in particular is described in Fig. 3 in a schematic block diagram. The hearing system 30 comprises the hearing aid 2 and an auxiliary device 32, which is designed as a smartphone 34. The hearing aid 2, in turn, comprises an external unit 36, which is designed as a data bracelet 38, through which the "actual" hearing aid 2 can be controlled, and which in the present case comprises the IMU. The preprocessing of the movement signal 12, based on which, for example, the tripping or falling is detected, can take place directly in the data bracelet 38, and corresponding first movement data 20 and / or the information 24 regarding the tripping / fall can be transmitted to the smartphone 34.As a result, a signal can also be transmitted to the “actual” hearing aid 2 to activate the skin conductivity sensor 14 or (in the case of permanent activation) to transmit the data recorded from the first phase P1 before the trip / fall to the third phase P3 after the trip / fall in the EDA signal 18 as second humidity-related data 22, if necessary after pre-processing to the standardized data types 22sd, to the smartphone 34. There, the frailty indicator value I0 can then be determined from the first movement data 20 or the information 24 as well as from the second humidity-related data or the standardized data types 22sd. In particular, the said data can be stored on the smartphone for this purpose and processed at a time separate from the trip / fall to form the frailty indicator value I0, e.g. using the preliminary parameters K0, Kj. Also in the . Fig.However, in the embodiment shown in Figure 3, an immediate calculation of the frailty indicator value I0 is possible.

[0053] Although the invention has been illustrated and described in detail by the preferred embodiment, the invention is not limited to the disclosed examples and other variations may be derived therefrom by those skilled in the art without departing from the scope of the invention. List of reference symbols 1 hearing instrument 2 hearing aids 4 Control unit 6 Signal processor 8a-c acceleration sensors 10a-c Angular rate sensors 12 motion signal 14 skin sensor, skin conductivity sensor 16a / b first / second measuring electrode 18 EDA signal 20 first movement data 22 second moisture-related data 22-1 / 2 / 3 second humidity-related data of the first / second / third phase 22-1 / 2 / 3m minima of the second moisture-related data 22-1 / 2 / 3av Mean values ​​of the second moisture-related data 22sd standardized data types 24 Information (about falling) 26 Measure of user attention 30 hearing system 32 Auxiliary device 34 smartphones 36 outdoor unit 38 data bracelet A1 output signal E1 input signal I0 Frailty indicator value IMU Inertial Measurement Unit K0, Kj preliminary characteristic L1 speaker M1 microphone P1 / 2 / 3 first / second / third phase R-1 / 2 / 3av reference values ​​(for the mean values) R-1 / 2 / 3m reference values ​​(for the minima) T Timeline T1-4 time points

Claims

[1] Method for establishing a frailty indicator value (I0) of a person using a hearing instrument (1), wherein first movement data (20) relating to a stumbling and / or falling are collected by at least one acceleration sensor (8a-c) of the hearing instrument (1), wherein second moisture-related data (22) are collected by a skin sensor (14) in the immediate temporal environment of the stumbling or falling, which provide an indication of skin moisture and thereby provide information about physiological and / or psychological circumstances in the temporal environment of the stumbling or falling, and wherein the frailty indicator value (I0) is generated based on the first movement data (20) and the second humidity-related data (22). [2] Method according to claim 1, wherein the first movement data (20) are collected by means of an inertial measuring unit (IMU) of the hearing instrument (1), and / or wherein the second moisture-related data (22) are collected as data of an electrodermal activity by means of a skin conductivity sensor as a skin sensor (14), and / or the second moisture-related data (22) are collected as skin reflectivity data by means of an optical sensor as a skin sensor (14). [3] Method according to claim 1 or claim 2, wherein the skin sensor (14) is activated based on a stumbling or falling detected in the first movement data (20), or is activated based on another relevant movement situation which is detected by means of the data collected by the at least one acceleration sensor (8a-c). [4] Method according to one of the preceding claims, wherein the skin sensor (14) continuously collects data which provides an indication of the moisture content of the skin, and wherein of said data only those which are collected in the immediate temporal environment of a stumbling and / or falling are stored and / or further processed as second moisture-related data (22). [5] Method according to one of the preceding claims, wherein for a first phase (P1) immediately before the tripping or falling and / or for a second phase (P2) during the tripping or falling and / or for a third phase (P3) immediately after the tripping or falling, second moisture-related data (22-1, 22-2, 22-3) are collected, which are each compared with a reference value (R-1m, R-2m, R-3m, R-1av, R-2av, R-3av) for the associated phase (P1, P2, P3), and where said comparison is used for the frailty indicator value (I0). [6] Method according to claim 5, wherein the first phase (P1) has a duration between one second and one minute immediately before the first sign of a stumble until the same, and / or wherein the second phase (P2) has a duration from the end of the first phase (P1) until regaining an orderly walking movement or until reaching the ground, and / or wherein the third phase (P3) has a duration of one second to five minutes immediately after the end of the second phase (P2). [7] Method according to one of claims 2 to 6, wherein the frailty indicator value (I0) is determined such that the value increases, the more and / or the longer the electrodermal activity of the person is reduced after the stumble or fall. [8] Method according to one of the preceding claims, wherein the second moisture-related data (22) are used to detect a false positive classification of a stumbling or falling as an event relevant to the frailty indicator value (I0). [9] Method according to one of the preceding claims, wherein a measure (26) for the person's attention before stumbling or falling is determined on the basis of the second moisture-related data (22), and the measure (26) for the attention is used for the frailty indicator value (I0). [10] Method according to one of the preceding claims, wherein, based on the first movement data (20) of the at least one acceleration sensor (8a-c), a first time (T1) is determined at which the person starts to stumble and / or fall, wherein a second point in time at which the person becomes aware of tripping and / or falling is determined based on the second moisture-related data (22), and where a time interval between the first and second time points is taken into account for the frailty indicator value (I0). [11] Method according to one of the preceding claims, wherein a probability and / or a risk of a future fall is generated as the frailty indicator value (I0). [12] Method according to one of claims 2 to 11, wherein the first movement data (20) contain at least one piece of information (24) of the following type about a stumbling or falling: a strength, a duration, a height difference, a change in position, a degree of severity and / or wherein the second humidity-related data (22) includes at least one data type (22sd) of the following type regarding the electrodermal activity over a given period of time: a maximum, a minimum (22-1 m, 22-2 m, 22-3 m), an average value (22-1 av, 22-2 av, 22-3 av), a time integral. [13] Method according to one of the preceding claims, wherein the frailty indicator value (I0) is determined in the immediate temporal environment of the stumbling or falling based on the first movement data (20) and on the second moisture-related data (22), and is then output and / or stored, or wherein the first movement data (20) and the second humidity-related data (22) are stored together with a time index, and the frailty indicator value (I0) is generated at a later time based on the stored first movement data (20) and the second humidity-related data (22). [14] Method according to claim 13, wherein a plurality of events of stumbling and / or falling are taken into account for the frailty indicator value (I0), and whereby a temporal accumulation of events and / or a change in a temporal distribution of events and / or a higher weighting of more recent events is taken into account. [15] Method according to one of the preceding claims, wherein the frailty indicator value (I0) is determined based on the first movement data (20) and the second moisture-related data (22) in the hearing instrument (1), or wherein at least parts of the first movement data (20) and / or the second moisture-related data (22) are transmitted from the hearing instrument (1) to an auxiliary device (32), and the calculation of the frailty indicator value (I0) is carried out at least partially on the auxiliary device (32). [16] Method according to one of the preceding claims, wherein the calculation of the frailty indicator value (I0) is carried out at least partially by means of an artificial neural network which uses the first movement data (20) and / or the second humidity-related data (22) and / or preprocessed data derived therefrom as input variables. [17] Hearing system (30) comprising a hearing instrument (1) and adapted to carry out the method according to one of the preceding claims. [18] Hearing system (30) according to claim 16, which further comprises an auxiliary device (32) which can be connected to the hearing instrument (1) by data technology, wherein the auxiliary device (32) is configured to carry out parts of the method according to one of claims 1 to 15.

Images