Hearing system with hearing device-based health characterization and / or monitoring and related methods

Abstract

The invention discloses a hearing system. The hearing system includes an electronic device including a memory, an interface, and a processor. The hearing system comprises a hearing device comprising a memory, an interface, a processor, and one or more sensors. The system is configured to obtain sensor data, such as external sensor data, from one or more sensors. The system is configured to determine a health parameter indicative of a cognitive state of a hearing device user based on sensor data, such as external sensor data. The system is configured to determine whether the health parameter satisfies a first criterion indicative of cognitive decline. The system is configured to output a health representation related to the cognitive state in accordance with the health parameter satisfying the first criterion.

Description

Technical Field

[0001] The present disclosure relates to the field of hearing systems, and in particular to hearing systems and related methods for health characterization and / or monitoring based on hearing devices. Background Art

[0002] Hearing loss is associated with cognitive impairment and dementia, and is the largest modifiable risk factor for dementia if addressed in early middle age (e.g. in the 45-65 age group). Furthermore, according to the Lancet Commission, the risk of dementia increases for every 10 decibels of hearing loss.

[0003] Additionally, for people diagnosed with mild cognitive impairment, using hearing aids was associated with a significantly lower risk of dementia compared to people with hearing loss who did not use hearing aids. The scientific hypothesis is that hearing loss leads to an increased cognitive load, which in turn leads to the involvement of other parts of the brain, impairing other functions and, over time, causing a reduction in cognitive reserve until the onset of dementia. The World Health Organization estimates that 55 million people worldwide suffer from dementia, most of whom live in low- and middle-income countries. The World Health Organization projects that the number of people suffering from dementia worldwide will rise to 139 million by 2050. Alzheimer's disease and related dementias are the seventh leading cause of death and one of the main issues affecting the quality of life of older people. Summary of the invention

[0004] Currently, there is a lack of technology for long-term, accurate, and convenient characterization and / or monitoring of a user's health status, such as characterization and / or monitoring of a user's cognitive state and its development.

[0005] Therefore, there is a need for health characterization and / or monitoring systems and health characterization and / or monitoring methods that can mitigate, alleviate or address existing shortcomings and can provide improved health characterization and / or monitoring, improve cognitive status characterization and / or monitoring, and enhance understanding of cognitive health.

[0006] A hearing device is disclosed. The hearing device may be considered as a hearing device with health representation and / or monitoring. The hearing device comprises a memory, an interface, a processor and one or more sensors, wherein the processor is configured to acquire (e.g., receive and / or retrieve) sensor data from the one or more sensors; determine a health parameter based on the sensor data, e.g., indicating a cognitive state of a user of the hearing device; and optionally determine whether the health parameter satisfies a first criterion, e.g., indicating cognitive decline. Optionally, the processor is configured to output a health representation associated with the cognitive state, e.g., through the interface, e.g., based on the health parameter satisfying the first criterion.

[0007] A method of operating a hearing device is disclosed. The method includes acquiring sensor data from one or more sensors of the hearing device; determining a health parameter based on the sensor data, such as indicating a cognitive state of a user of the hearing device; and determining whether the health parameter satisfies a first criterion, such as indicating cognitive decline. Optionally, the method includes outputting a health representation associated with the cognitive state, such as based on the health parameter satisfying the first criterion.

[0008] In addition, an electronic device is disclosed. The electronic device includes a memory, an interface, and a processor. The processor is configured to obtain external sensor data from a hearing device through the interface; determine a health parameter based on the external sensor data, such as indicating a cognitive state of a user of the hearing device. The processor can be configured to determine whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the processor is configured to output a health representation related to the cognitive state, such as through the interface, for example, based on the health parameter meeting the first criterion.

[0009] In addition, a method of operating an electronic device is disclosed. The method includes acquiring sensor data, such as external sensor data from a hearing device; determining a health parameter based on the sensor data, such as the external sensor data, such as indicating a cognitive state of a user of the hearing device; and determining whether the health parameter meets a first criterion, such as indicating cognitive decline. Optionally, the method includes outputting a health representation associated with the cognitive state, such as based on the health parameter meeting the first criterion.

[0010] In addition, a hearing system is disclosed. The hearing system includes an electronic device, the electronic device including a memory, an interface and a processor. The hearing system includes a hearing device, the hearing device including a memory, an interface, a processor and one or more sensors. The system is configured to obtain sensor data from the one or more sensors, such as external sensor data. The system is configured to determine a health parameter indicating a cognitive state of a user of the hearing device based on the sensor data, such as the external sensor data. The system is configured to determine whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the system is configured to output a health representation associated with the cognitive state based on the health parameter meeting the first criterion.

[0011] A method of operating a hearing system is disclosed. The method includes acquiring sensor data, such as external sensor data, from a hearing device. The method includes determining a health parameter indicative of a cognitive state of a user of the hearing device based on the sensor data, such as the external sensor data. The method includes determining whether the health parameter satisfies a first criterion indicative of cognitive decline. Optionally, the method includes, in dependence on the health parameter satisfying the first criterion, outputting a health representation associated with the cognitive state.

[0012] The disclosed hearing systems, hearing devices, electronic devices, and related methods provide improved health characterization and / or monitoring. In other words, the present disclosure can provide improved sensor-based (e.g., audio-based) health characterization and / or monitoring of hearing device users, with improved accuracy and precision. For example, the distance between the hearing device and the user's mouth can be constant and close, which can provide sensor data with improved accuracy. In addition, by using the hearing device to provide sensor data, the sensor can be placed closer to the artery, which can provide better measurements and, in turn, more accurate sensor data. It can be appreciated that by using the hearing device to provide sensor data, fewer motion artifacts can occur, for example compared to sensors located at the user's limbs.

[0013] The present disclosure allows improving cognitive decline detection by determining health parameters based on sensor data, for example based on sensor data indicative of biomarkers of a hearing device user, such as voice biomarkers, physiological biomarkers and / or biodynamic biomarkers.

[0014] It will be appreciated that the present disclosure may provide improved feedback about a user's cognitive state that is easier for the user to understand. The present disclosure provides improved awareness about user health, and in particular about cognitive health of hearing device users. In other words, the present disclosure may provide enhanced awareness about the importance of cognitive health and diseases associated with cognitive decline. For example, by providing a health representation, the present disclosure may improve visualization and / or comprehensibility for hearing device users. Thus, the health representation may provide information about cognitive state, for example based on health parameters. It is well known that hearing devices are worn for long periods of time throughout the day, so hearing devices with health characterization and / or monitoring capabilities may increase the probability of, for example, detecting cognitive decline.

[0015] Accordingly, the present disclosure may provide a customized health representation to a user of a hearing device, for example based on long-term sensor data. Furthermore, the present disclosure may encourage increased use of hearing devices, for example to reduce the risk of cognitive decline.

[0016] It will be appreciated that the present disclosure provides for health characterization and / or monitoring of hearing device users, for example, to perform early detection and / or identification of cognitive decline in hearing device users. For example, hearing device users may be continuously screened for cognitive decline, such as cognitive impairment. This in turn may reduce long-term healthcare costs and reduce the burden on caregivers and healthcare systems. The present disclosure provides a flexible and non-invasive way to characterize and / or monitor the health status of hearing device users, for example, by using sensor data from the hearing device. In other words, the present disclosure may provide a low-cost technique to perform health characterization and / or monitoring of hearing device users, which may also be performed remotely for the user at home.

[0017] One advantage of the present disclosure is that the health status of a hearing device user may be characterized and / or monitored based on sensor data obtained over a long period of time, for example, a hearing device user typically wears the hearing device for most of the waking hours. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features and advantages of the present disclosure will become apparent to those skilled in the art through the following detailed description of examples of the present disclosure in conjunction with the accompanying drawings, in which:

[0019] Figure 1 schematically illustrates an example hearing system according to the present disclosure,

[0020] Figure 2 is a flowchart of an example method according to the present disclosure,

[0021] Figure 3 is a flowchart of an example method according to the present disclosure, and

[0022] Figure 4A and Figure 4B is a flow chart of an example method according to the present disclosure. DETAILED DESCRIPTION

[0023] Various examples and details will be described below with reference to the relevant drawings. It should be noted that the drawings may be drawn to scale or not to scale, and that elements of similar structure or function are represented by the same reference numerals throughout the drawings. It should also be noted that the drawings are only used to facilitate the description of the examples. They are not intended to be an exhaustive description of the present disclosure or a limitation on the scope of the present disclosure. In addition, the examples shown do not necessarily have all the aspects or advantages shown. The aspects or advantages described in conjunction with a particular example are not necessarily limited to that example and may be practiced in any other example, even if not shown or not so explicitly described.

[0024] The accompanying drawings are schematic and simplified for clarity, and they only show details that are helpful for understanding the present disclosure, while other details have been omitted. Throughout the accompanying drawings, the same reference numerals are used for the same or corresponding parts.

[0025] A hearing system is disclosed. The hearing system may be viewed as a system for performing health characterization and / or monitoring. In other words, the hearing system may be viewed as a system for performing health characterization and / or monitoring of a hearing device user (eg, a user wearing the hearing device).

[0026] The hearing system comprises an electronic device, which comprises a memory, an interface and a processor. The electronic device of the hearing system may be an electronic device disclosed herein. The hearing system comprises a hearing device, which comprises a memory, an interface, a processor and one or more sensors. The hearing device of the hearing system may be a hearing device disclosed herein.

[0027] The hearing device disclosed herein may include one or more processors, a memory, an interface and one or more transducers, such as a microphone (eg a first microphone) and / or a receiver (eg a hearing device speaker).

[0028] The hearing device may be configured to be worn on an ear of a user. The hearing device may be a hearable device. The hearing device may be a hearing aid, wherein the processor is configured to compensate for a hearing loss of the user.

[0029] A hearing device may be an earplug, a hearing aid, a headset, a personal sound amplification product (PSAP), an over-the-counter (OTC) hearing device, a hearing protection device, a custom hearing device, or other ear-worn hearing device. Hearing devices may include both prescription devices and over-the-counter devices.

[0030] Hearing devices may be embodied in a variety of housing styles / form factors. Some of these form factors are behind-the-ear (BTE) hearing devices, receiver-in-the-canal (RIC) hearing devices, receiver-in-the-ear (RIE) hearing devices, or microphone-in-the-ear (MaRIE) hearing devices. What these devices have in common is that they may include a BTE component configured to be worn behind a user's ear and an in-the-ear (ITE) component configured to be partially or fully inserted into a user's ear canal. Typically, a BTE component may include at least one input transducer, a power supply, and a processing unit. The term BTE hearing device may refer to a hearing device in which a receiver (i.e., an output transducer) is contained in the BTE component and sound is directed to the ITE component via an acoustic tube connecting the BTE and ITE components, while the terms RIE, RIC, and MaRIE devices refer to hearing devices in which a receiver is contained in an ITE component, which is coupled to the BTE component via a connector cable or wire that is configured to transmit electrical signals between the BTE and ITE components.

[0031] The hearing device may be of the behind-the-ear (BTE) type, in-the-ear (ITE) type, in-the-canal (ITC) type, receiver-in-the-canal (RIC) type or receiver-in-the-ear (RITE) type. The hearing aid may be a binaural hearing aid.

[0032] In one or more example hearing systems, hearing devices, and / or electronic devices, the hearing device may be considered a user hearing device, such as a headset, earplugs, hearing aids, over-the-counter (OTC) hearing devices, and / or hearing protection devices. In one or more example hearing systems and / or hearing devices, the hearing device may include one or more transceivers for wireless communication. In one or more example hearing systems and / or hearing devices, the hearing device may facilitate wired communication, such as by using a cable, such as a cable.

[0033] The hearing device may be configured to communicate wirelessly, e.g., via an interface, with one or more devices, e.g., with another hearing device, e.g., as part of a binaural hearing system, and / or with one or more accessory devices / electronic devices, such as a smartphone and / or a smartwatch. The hearing device may optionally include an antenna for converting one or more wireless input signals. The wireless input signal may come from an external source, such as a spouse microphone device, a wireless television audio transmitter, and / or a distributed microphone array associated with a wireless transmitter. The wireless input signal may come from another hearing device, e.g., as part of a binaural hearing system, and / or from one or more accessory devices. The sensor data disclosed herein may be based on one or more wireless input signals, e.g., from an external source. This may, for example, provide information about the user's environment, which may be used to determine the health parameters disclosed herein.

[0034] The hearing device optionally comprises a radio transceiver coupled to the antenna for converting the antenna output signal into a transceiver input signal. Wireless signals from different external sources may be multiplexed in the radio transceiver as transceiver input signals or provided as separate transceiver input signals at separate transceiver output terminals of the radio transceiver. The hearing device may comprise multiple antennas and / or the antenna may be configured to operate in one or more antenna modes.

[0035] In one or more hearing systems, hearing devices and / or electronic devices, one or more sensors include a microphone for providing microphone input data. In other words, one or more sensors may include a group of microphones. In one or more hearing systems and / or electronic devices, external sensor data includes microphone input data. The microphone may include one or more microphones. The microphone may include a first microphone for providing a first microphone input signal and / or a second microphone for providing a second microphone input signal. The microphone may include N microphones for providing N microphone signals, where N is an integer in the range of 1 to 10. In one or more example hearing devices, the number of microphones N is 2, 3, 4, 5 or more. The microphone may include a third microphone for providing a third microphone input signal. In one or more example hearing devices, the microphone input data may come from a single microphone signal (e.g., a first microphone signal) or a combination of microphone input signals from multiple microphones. For example, the microphone data may be based on a first microphone input signal from a first microphone and / or a second microphone input signal from a second microphone. The microphone may include an ear canal microphone and / or an environmental microphone for picking up self-speech (e.g., a user's own speech). This may allow filtering out external speech and / or sounds of the user's environment, for example, essentially picking up only the user's speech. In one or more hearing systems, hearing devices and / or electronic devices, the health parameters are based on microphone input data.

[0036] In one or more hearing systems, hearing devices and / or electronic devices, one or more sensors include one or more of the following: a microphone, an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor. An example of an optical sensor is a photoplethysmogram (PPG) sensor. An example of a current sensor is an electrocardiogram (ECG) sensor and / or an electroencephalogram (EEG) sensor. A motion sensor may be considered an inertial measurement unit (IMU). An example of a motion sensor may include an accelerometer and / or a gyroscope. The motion sensor may, for example, include a magnetic sensor, such as a magnetometer. An example of a capacitive sensor may include a capacitive microphone and / or a temperature sensor.

[0037] In one or more hearing systems, hearing devices and / or electronic devices, the one or more sensors include one or more body sensors, such as a heart rate sensor, a blood pressure sensor, a pulse sensor, a photoplethysmogram (PPG) sensor, an electrocardiogram (ECG) sensor, an electroencephalogram (EEG) sensor, an electrical bioimpedance sensor and / or a temperature sensor. The one or more sensors of the hearing device may include a body sensor, which is a capacitive and / or conductive sensor, for example for measuring and / or determining stress levels.

[0038] The sensor data disclosed herein may be obtained from one or more sensors described above. In other words, the sensor data may be generated and / or provided by one or more sensors described above.

[0039] The hearing device comprises one or more processors for processing input signals (e.g., transceiver input signals and / or microphone input signals). The processor is optionally configured to compensate for hearing loss of a user of the hearing device. The processor provides an electrical output signal to the processor based on the input signal. The input of the processor is optionally connected to a corresponding microphone and / or output of the pre-processing unit. One or more microphone inputs of the processor may be connected to corresponding one or more microphone outputs of the pre-processing unit.

[0040] The hearing system, hearing device and / or electronic device may be configured to communicate wirelessly via a wireless communication system, such as a short-range wireless communication system, such as Wi-Fi, Bluetooth, Zigbee, IEEE 802.11, IEEE 802.15, infrared and / or the like.

[0041] The hearing system, hearing device and / or electronic device (e.g., accessory device) can be configured to communicate wirelessly via a wireless communication system, such as a 3GPP system, such as a 3GPP system supporting one or more of: New Radio, NR, Narrowband Internet of Things, NB-IoT and Long Term Evolution - Enhanced Machine Type Communications, LTE-M, millimeter wave communications, such as millimeter wave communications in licensed bands, such as device-to-device millimeter wave communications in licensed bands.

[0042] In one or more hearing systems, hearing devices and / or electronic devices, the interface of the electronic device and / or the interface of the hearing device comprises one or more of the following: a Bluetooth interface, a low-power Bluetooth interface and a magnetic induction interface. For example, the interface of the electronic device and / or the interface of the hearing device may include a Bluetooth antenna and / or a magnetic interference antenna.

[0043] The system is configured to acquire external sensor data from one or more sensors. In other words, the system is configured to obtain the external sensor data at the hearing device and / or the electronic device. In other words, the electronic device may obtain, receive and / or retrieve the external sensor data from the hearing device. The hearing device may transmit and / or send the external sensor data to the electronic device. The system is configured to determine a health parameter indicating a cognitive state of a user of the hearing device based on the external sensor data, for example using a processor of the hearing device and / or a processor of the electronic device. In other words, the system is configured to determine a health parameter indicating a cognitive state of a user of the hearing device based on the external sensor data, for example at a processor of the hearing device and / or a processor of the electronic device. The system is configured to determine a first criterion indicating cognitive decline, for example using a processor of the hearing device and / or a processor of the electronic device. In other words, the system is configured to determine whether a health parameter satisfies a first criterion indicating cognitive decline, for example at a processor of the hearing device and / or a processor of the electronic device. Optionally, the system is configured to output a health representation related to the cognitive state through an interface of the hearing device and / or an interface of the electronic device, for example using a processor of the hearing device and / or a processor of the electronic device, based on the health parameter satisfying the first criterion.

[0044] A hearing device is disclosed. The hearing device can be regarded as a hearing device with health representation and / or monitoring. The hearing device includes a memory, an interface, a processor and one or more sensors. The processor is configured to obtain sensor data from the one or more sensors. The processor is configured to determine a health parameter indicating a cognitive state of a user of the hearing device based on the sensor data. The processor is configured to determine whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the processor is configured to output a health representation related to the cognitive state through the interface based on the health parameter meeting the first criterion.

[0045] An electronic device is disclosed. The electronic device includes a memory, an interface, and a processor. The processor is configured to obtain external sensor data from a hearing device through the interface. The processor is configured to determine a health parameter indicating a cognitive state of a user of the hearing device based on the external sensor data. The processor is configured to determine whether the health parameter satisfies a first criterion indicating cognitive decline. Optionally, the processor is configured to output a health representation associated with the cognitive state through the interface based on the health parameter satisfying the first criterion.

[0046] External sensor data and sensor data disclosed herein may be used interchangeably. External sensor data may be considered as sensor data obtained from a hearing device. In other words, external sensor data may be considered as sensor data generated by one or more sensors of a hearing device.

[0047] In one or more hearing systems, hearing devices and / or electronic devices, the electronic device includes one or more sensors, such as one or more internal sensors. In one or more hearing systems, hearing devices and / or electronic devices, the system is configured to obtain internal sensor data from one or more sensors of the electronic device. In one or more hearing systems, hearing devices and / or electronic devices, the health parameters are based on the internal sensor data. The internal sensor data can be regarded as sensor data obtained from the electronic device. In other words, the internal sensor data can be regarded as sensor data generated by one or more sensors of the electronic device. It will be understood that the health parameters are determined based on sensor data (e.g., external sensor data) and / or internal sensor data.

[0048] One or more sensors of an electronic device (e.g., an accessory device) may include one or more of the following: an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor. An example of an optical sensor is a photoplethysmogram (PPG) sensor. An example of a current sensor is an electrocardiogram (ECG) sensor and / or an electroencephalogram (EEG) sensor. A motion sensor may be considered an inertial measurement unit (IMU). An example of a motion sensor may include an accelerometer and / or a gyroscope. A motion sensor may include, for example, a magnetic sensor, such as a magnetometer. An example of a capacitive sensor may include a capacitive microphone and / or a temperature sensor.

[0049] In one or more hearing systems, hearing devices and / or electronic devices, one or more sensors of the electronic device (e.g., an accessory device) include one or more body sensors, such as a heart rate sensor, a blood pressure sensor, a pulse oximeter sensor, a photoplethysmogram (PPG) sensor, an electrocardiogram (ECG) sensor, an electroencephalogram (EEG) sensor, an electrical bioimpedance sensor, and a temperature sensor. The one or more sensors of the hearing device may include a body sensor that is a capacitive and / or conductive sensor, for example, for measuring and / or determining stress levels.

[0050] The internal sensor data disclosed herein can be obtained from one or more of the above-mentioned sensors. In other words, the internal sensor data can be generated and / or provided by any one or more of the above-mentioned sensors.

[0051] In one or more example hearing systems, hearing devices and / or electronic devices, the one or more sensors include one or more motion sensors, such as accelerometers, inertial motion sensors, gyroscopes, altimeters and / or position sensors (e.g., GPS sensors).

[0052] In one or more example hearing systems, hearing devices and / or electronic devices, the body sensor is configured to determine body data indicating body information of the user to provide a health parameter. In one or more example hearing systems, hearing devices and / or electronic devices, the motion sensor is configured to determine motion data indicating motion information of the user to provide a health parameter.

[0053] In one or more example hearing systems, hearing devices and / or electronic devices, a user may be considered a user of a hearing device and / or a user of an electronic device (eg, a user of an accessory device).

[0054] In one or more example hearing systems and / or electronic devices, the electronic device is a server device.

[0055] In one or more example hearing systems and / or electronic devices, the electronic device is an accessory device.

[0056] An electronic device may include an accessory device and / or a server device. The electronic device may be configured to run on an accessory device and / or a server device. In other words, the electronic device may be configured to function as a server device and / or an accessory device. The accessory device may, for example, be or include a mobile phone, such as a smartphone, a smart watch, a smart speaker, a tablet computer, a computer, such as a laptop or PC, or a tablet computer. In other words, the electronic device may, for example, be a user device, such as a mobile phone or a computer, configured to perform health characterization and / or monitoring. In one or more example hearing systems and / or electronic devices, the accessory device may be considered a user accessory device, such as a mobile phone, a smart watch, a tablet computer, and / or a wearable device. In one or more example hearing systems, the accessory device may include one or more transceivers for wireless communication. In one or more example hearing systems, the accessory device may facilitate wired communication, such as by using a cable, such as a cable.

[0057] The server device may be configured on a cloud, such as a cloud network. Different operations configured to be performed by the electronic device and / or system disclosed herein may be performed on different devices, such as an electronic device and / or a server device.

[0058] The health parameters disclosed herein indicate the cognitive state of the user of the hearing device. The health parameters may also be considered and / or represented as cognitive parameters. In other words, the health parameters may indicate information related to the cognitive state of the user of the hearing device. The cognitive state of the user may indicate the user's ability to hear, speak, see and / or move. In other words, the health parameters may indicate the user's ability to hear, speak, see and / or move. For example, the cognitive parameters may be considered as a set of features that together constitute a biomarker. For example, based on microphone input data, the cognitive parameters may be considered as a set of audio features that together constitute a voice biomarker. For example, based on physiological data, the cognitive parameters may be considered as one or more physiological features that together constitute a physiological biomarker. For example, based on biodynamic data, the cognitive parameters may be considered as one or more biodynamic features that together constitute a biodynamic biomarker. The health parameters may indicate the cognitive load of the user. The health parameters may be determined based on one or more biomarkers disclosed herein, such as based on one or more of a voice biomarker, a physiological biomarker and / or a biodynamic biomarker. For example, the cognitive load may be determined based on one or more biomarkers disclosed herein, such as based on one or more of a voice biomarker, a physiological biomarker and / or a biodynamic biomarker.

[0059] It will be appreciated that the health parameter may include a score, such as a health score, indicating the cognitive state of the user of the hearing device. In other words, determining the health parameter may include determining a health score indicating the cognitive state of the user. Determining whether the health parameter meets the first criterion indicating cognitive decline may include determining whether the health score meets the first criterion. For example, when the score is greater than or equal to a threshold (e.g., a first threshold), it may be determined that the score meets the criterion (e.g., the first criterion). The cognitive state may indicate the degree of cognitive ability. Cognitive ability may include memory ability, stress ability (ability to work under load), language ability, thinking ability, and / or judgment ability. The cognitive state may, for example, indicate mild cognitive impairment. Mental illnesses such as anxiety and depression may have an impact on the user's cognitive ability. Therefore, the cognitive state may indicate a mental illness.

[0060] In one or more example hearing systems, based on the health parameter not satisfying a first criterion, the system is configured to refrain from outputting a health representation associated with a cognitive state.

[0061] In one or more example hearing devices, based on the health parameter not meeting the first criterion, the processor of the hearing device is configured to refrain from outputting a health representation related to the cognitive state.

[0062] In one or more example electronic devices, based on the health parameter not satisfying a first criterion, a processor of the electronic device is configured to refrain from outputting a health representation related to a cognitive state.

[0063] The first criterion may comprise a threshold value indicating cognitive decline of a user of the hearing device, such as a health threshold value and / or a cognitive threshold value. The first criterion may be based on one or more user parameters. For example, the first criterion may be based on the age of the user. Thus, the first criterion may indicate cognitive decline with respect to one or more user parameters. For example, the first criterion may indicate cognitive decline with respect to the age of the user, for example compared to normal cognitive abilities of a person of the same age. The one or more user parameters may also comprise historical user data of the user of the hearing device. Thus, the first criterion may indicate cognitive decline of the user over time based on historical data. The first criterion may be based on historical health parameters of the user of the hearing device. Thus, it may be determined whether the user suffers from cognitive decline over time, relative to the user's own historical health parameters, such as cognitive abilities.

[0064] Determining whether the health parameter satisfies the first criterion may include determining whether the health parameter is above, below, or equal to a health threshold and / or within a range indicative of the first criterion. In other words, when the health parameter is above or equal to the first threshold, the health parameter may satisfy the first criterion. For example, when the health parameter is above or equal to the first threshold indicating cognitive decline, the health parameter may satisfy the first criterion. In other words, when the health parameter satisfies the first criterion, the user of the hearing device may be considered to be cognitively declined. In other words, when the health parameter satisfies the first criterion, one or more cognitive abilities of the user of the hearing device are determined to be declined. For example, the user's hearing, speaking, observation, and / or movement abilities may be determined to be declined.

[0065] Cognitive decline of a health parameter (e.g., a user's cognitive state) can be determined based on a previous cognitive state of the user (e.g., a historical cognitive state) and / or based on a normal cognitive state of the person. In other words, cognitive decline of the user's cognitive state can be determined by comparing it to the user's historical cognitive state and / or to a normal cognitive state of a person of approximately the same age, gender, and / or physiological state. Cognitive decline can be viewed as a degradation of cognitive abilities, such as memory, attention, problem solving, verbal abilities, and / or language skills. In other words, cognitive decline can be viewed as a degradation of cognitive abilities over time, for example, a degradation of cognitive abilities over time compared to the user's historical cognitive state and / or compared to a normal cognitive state of a person of approximately the same age, gender, and / or physiological state.

[0066] In one or more example hearing systems, the system is configured to determine (e.g., at the electronic device and / or the hearing device) a health representation associated with the cognitive state based on the sensor data, e.g., based on the external sensor data. In other words, the system is configured to determine (e.g., using a processor of the electronic device and / or a processor of the hearing device) a health representation associated with the cognitive state based on the sensor data (e.g., based on the external sensor data).

[0067] In one or more example electronic devices, a processor is configured to determine a health representation associated with a cognitive state based on sensor data, such as based on external sensor data.

[0068] In one or more example hearing systems, the processor is configured to determine a health indicator associated with a cognitive state based on the sensor data.

[0069] In one or more example hearing systems, the system includes a machine learning circuit configured to operate according to a machine learning model. In one or more example hearing systems, determining the health parameter includes determining the health parameter using a machine learning model based on external sensor data, for example using an electronic device and / or a hearing device. In other words, the electronic device and / or the hearing device may include a machine learning circuit configured to operate according to the machine learning model. In other words, the system may be configured to determine the health parameter using a machine learning model based on external sensor data, for example using an electronic device and / or a hearing device.

[0070] In one or more example hearing devices, the processor includes a machine learning circuit configured to operate according to the machine learning model. In one or more example hearing devices, determining the health parameter includes determining the health parameter using the machine learning model based on the sensor data.

[0071] In one or more example electronic devices, the processor includes a machine learning circuit configured to operate according to a machine learning model. In one or more example electronic devices, determining the health parameter includes determining the health parameter using the machine learning model based on external sensor data.

[0072] In other words, the electronic device and / or hearing device may include one or more processors including a machine learning engine configured to operate according to a machine learning model. The machine learning circuit may be viewed as a predictor circuit configured to operate according to a prediction model. The machine learning circuit may be configured to predict a health parameter using a prediction model based on sensor data (e.g., external sensor data).

[0073] The machine learning model may, for example, include or utilize neural networks, artificial intelligence, deep learning, and / or machine learning.

[0074] In one or more example hearing systems, electronic devices, and / or hearing devices, the machine learning model includes a model layer (including an input layer, one or more intermediate layers, and an output layer for providing health parameters). In one or more example hearing systems, electronic devices, and / or hearing devices, the machine learning model includes a neural network. In one or more example hearing systems, electronic devices, and / or hearing devices, the machine learning model includes a neural network layer (including an input layer, one or more intermediate layers, and an output layer for providing health parameters). In other words, the input layer, the one or more intermediate layers, and / or the output layer can be regarded as layers of the machine learning model, such as layers of the neural network. One or more intermediate layers can be regarded as hidden layers (e.g., hidden features). One or more intermediate layers can include a first intermediate layer. The machine learning model can include a lookup table with multiple parameters (e.g., at least four parameters).

[0075] The models (e.g., machine learning models) mentioned herein may be viewed as models and / or schemes and / or mechanisms and / or methods that are configured to provide one or more health parameters based on operational data (e.g., sensor data, such as audio input data) and / or previous models. The models (e.g., machine learning models) mentioned herein may be based on the same model architecture. The model architecture may be based on a neural network, for example, including one or more different types of layers and / or number of layers. The model architecture may be viewed as a configuration of a model, for example, including one or more parameters of a model.

[0076] In one or more example hearing systems, electronic devices, and / or hearing devices, the models mentioned herein may be stored on a non-transitory storage medium (e.g., on a memory of the electronic device and / or hearing device). The model may be stored on a non-transitory storage medium of the electronic device and / or hearing device and configured to execute the model. In one or more example hearing systems, electronic devices, and / or hearing devices, the model may include model data and / or computer-readable instructions (e.g., based on sensor data and / or audio signals, such as historical sensor data). The model data and / or computer-readable instructions may be used by the electronic device and / or hearing device. The model (e.g., model data and / or computer-readable instructions) may be used by the hearing device and / or electronic device to determine health parameters and health representations. In other words, the model (e.g., model data and / or computer-readable instructions) may be used by the hearing device and / or electronic device to determine one or more parameters, features, and / or biomarkers as described herein, such as health parameters, voice biomarkers, physiological biomarkers, and / or bio-motion biomarkers. In general, biomarkers such as voice biomarkers, physiological biomarkers, and / or bio-motion biomarkers as disclosed herein may indicate and / or represent a user's energy usage and / or levels. Energy usage and / or levels may provide an indication of the user's cognitive state (e.g., cognitive load).

[0077] In one or more example electronic devices, machine learning circuitry includes a neural network module configured to operate according to a neural network.

[0078] In one or more example hearing systems, electronic devices and / or hearing devices, the neural network is a deep neural network, such as a convolutional neural network and / or a recurrent neural network. For example, the neural network may include a one-dimensional convolutional neural network or a two-dimensional convolutional neural network.

[0079] In one or more example hearing systems, electronic devices, and / or hearing devices, the machine learning circuitry includes a regressor module configured to operate according to a regression model.

[0080] The machine learning model can be based on a neural network (e.g., a convolutional neural network, a deep learning neural network, a recurrent neural network, and / or a combination of learning circuits). The machine learning circuit can be configured to determine (and optionally identify) one or more patterns in existing data (sensor data, audio input data, sound patterns (e.g., speech patterns), and / or health parameters) to facilitate determination and / or prediction of subsequent health parameters. For example, the machine learning circuit can be configured to determine (e.g., identify) a health parameter based on changes in sensor data and / or audio input data over time.

[0081] The machine learning circuit (e.g., a neural network module and / or a regressor module) can be configured to operate according to a machine learning scheme that is configured to determine a rule or pattern or relationship that maps an input to an output so that when a subsequent new input is provided, the machine learning circuit can accurately predict the correct output based on the rule, pattern, or relationship. In one or more embodiments, the machine learning model can first extract one or more features from the input sensor data, such as by using a signal processing method (e.g., a filter), statistics of the signal (e.g., mean, maximum, median, and / or quantile), and / or results from an unsupervised learning method (e.g., a dimensionality reduction method, clustering, and / or an autoencoder). One or more features can then be input into a regression and / or classification model trained using machine learning techniques.

[0082] In one or more example hearing systems, electronic devices, and / or hearing devices, the system is configured to train a machine learning model, provide an updated machine learning model, and transmit the updated machine learning model to the electronic device and / or hearing device. In other words, the server device is configured to train a machine learning model, provide an updated machine learning model, and transmit the updated machine learning model to the electronic device and / or hearing device.

[0083] In one or more example hearing systems, electronic devices, and / or hearing devices, a server device is configured to train and / or update a machine learning model based on one or more of: sensor data and health parameters. In one or more examples, a processor may be configured to train and / or update a machine learning model based on a result of a health representation (e.g., by comparing health parameters to known health parameters). The machine learning model based on which the machine learning circuit operates may be trained and / or updated (e.g., retrained or fine-tuned). The training of the machine learning model may be a supervised learning setting, in which sensor data in the input data may be labeled. The machine learning model or changes to the machine learning model may be based on new data, such as new sensor data and / or new prediction data.

[0084] The health representation disclosed herein may be considered as a representation indicating all or part of the health parameters and / or cognitive state of the user. In other words, the health representation may be considered as a cognitive state representation. The health representation may be considered as and / or includes an assessment of the user's cognitive state. In other words, the health representation may be considered as and / or includes an assessment of the user's cognitive ability. In one or more example hearing systems, electronic devices, and / or hearing devices, the health representation includes a score indicating the user's cognitive state performance, such as a cognitive score (e.g., when wearing a hearing device). The health representation may indicate whether the user's cognitive state indicates cognitive decline. Therefore, the health representation may provide feedback on the user's cognitive state and an indication of whether to take action on it. For example, when the health parameter meets the standard, the score may indicate cognitive decline. For example, the processor of the system, the electronic device, and / or the processor of the hearing device may be configured to determine whether the score meets the standard (e.g., a first standard). When the score is higher than or equal to a threshold (e.g., a first threshold), it may be determined that the score meets the standard (e.g., a first standard). The health representation may include information about the degree of cognitive decline. For example, the health representation may indicate whether the user suffers from mild cognitive decline, moderate cognitive decline, severe cognitive decline, or severe cognitive decline. Mild cognitive decline, moderate cognitive decline, severe cognitive decline and / or severe cognitive decline may indicate and / or be expressed as a level of cognitive decline, such as progression from mild cognitive impairment to dementia, wherein mild cognitive decline may be considered as mild cognitive impairment and severe cognitive decline may be considered as progression to dementia. Cognitive decline is not necessarily associated with a mental disorder or condition, but may, for example, be caused by one or more factors, such as: fatigue, aging, overstimulation, lifestyle factors, medications and stress. Cognitive decline may be temporary and may, for example, be triggered by one or more of the above factors. For example, a deterioration in a user's cognitive abilities may be determined or detected over a period of time, but the user's cognitive abilities may return to the state before the deterioration was detected after a period of time. The determination of cognitive decline may be different from the determination of cognitive load or the determination of a mental disorder.

[0085] In one or more example hearing systems, electronic devices, and / or hearing devices, the health representation includes a representation of a health parameter. For example, the health representation may include a representation of a biomarker as described herein. The health representation may include one or more of: a voice biomarker representation, a physiological biomarker representation, and a biodynamic biomarker representation.

[0086] In one or more example hearing systems, electronic devices, and / or hearing devices, the health representation indicates an assessment of a user's cognitive state.

[0087] In one or more example hearing systems, electronic devices, and / or hearing devices, outputting the health representation may include outputting the health representation via an interface of the electronic device and / or an interface of the hearing device.

[0088] In one or more example hearing systems and / or electronic devices, outputting the health representation includes displaying a user interface representing the health representation through an interface of the electronic device. In other words, outputting the health representation includes displaying a user interface representing the health representation through an interface of an accessory device disclosed herein.

[0089] Outputting the health representation may include displaying a user interface indicating the health representation. In one or more example hearing systems and / or electronic devices, outputting the health representation may include outputting the first health representation, the second health representation, the third health representation, etc. through an interface of the electronic device.

[0090] Outputting the health representation may include displaying a user interface indicative of the health representation.

[0091] The user interface may include one or more user interface objects, such as multiple user interface objects. For example, the user interface may include one or more user interface objects, such as a first user interface object and / or a second user interface object. A user interface object may refer to a graphical representation of an object displayed on an interface (e.g., a display) of an electronic device in this article. A user interface object may be user interactive or may be selected by user input. For example, an image (e.g., an icon), a button, and a text (e.g., a hyperlink) each optionally constitute a user interface object. A user interface object may form part of a widget. A widget may be considered a mini-application that a user can use. Outputting a health representation may include outputting a health representation that includes one or more of a text (e.g., a text string) and / or a phrase, a score (e.g., an assessment score and / or a cognitive score), image data (e.g., one or more images), a sound, an audio message, and / or a user interface object including one or more of the above. For example, outputting a health representation may include outputting a health representation containing a user cognitive status report. For example, outputting a health representation may include outputting a health representation containing a score, such as an assessment score of a cognitive status of a user using a hearing device.

[0092] In one or more example hearing systems, electronic devices, and / or hearing devices, based on a health parameter that meets a first criterion, a processor of the system, the electronic device, and / or the processor of the hearing device is configured to determine a first suggestion. The first suggestion may be considered as feedback to a user of the hearing device regarding a cognitive state of the user. The first suggestion may be considered as a first assessment. The first suggestion may indicate a suggestion to avoid and / or reduce cognitive decline. The first suggestion may be considered as and / or include a suggested action that the hearing device user should take based on the health parameter that meets the first criterion and / or something that the user should avoid (e.g., stop doing). The first suggestion may, for example, include text (e.g., a message to the user) and / or phrases such as: "Cognitive decline has been detected, please contact a healthcare provider and / or your doctor (e.g., a general practitioner)", "Please take a cognitive test", "Please increase the use of hearing devices to reduce cognitive decline", "Please take your hearing device to your hearing specialist to adjust and / or update the hearing device configuration to reduce cognitive decline", "Please increase your brain activity and / or motor activity to reduce cognitive decline", "Please check for diabetes", "High blood pressure has been detected, please contact a healthcare provider and / or your doctor (e.g., a general practitioner)", "If you smoke, it is recommended that you quit smoking or at least reduce smoking", "Please try to improve the air quality of your environment, such as reducing the air pollution you are exposed to", "Please try to lose weight to reduce obesity", "Please exercise regularly and / or increase your physical activity level", "If you suffer from depression, treat it", "Please avoid excessive drinking" and / or "Please try to maintain frequent social contacts".

[0093] In one or more example hearing systems, electronic devices, and / or hearing devices, the system, the processor of the electronic device, and / or the processor of the hearing device is configured to output a first suggestion via an interface (e.g., an interface of the electronic device and / or the hearing device). In other words, the processor can be configured to output the first suggestion in the form of text (e.g., a message to a user) and / or a phrase, an evaluation score, image data (e.g., one or more images), an audio message (e.g., output to the user via a receiver of the hearing device), and / or a user interface, as described herein.

[0094] In one or more example hearing systems, electronic devices, and / or hearing devices, the first suggestion is included in the health representation. In other words, the system, the processor of the electronic device, and / or the processor of the hearing device is configured to include the first suggestion in the health representation. For example, the system, the processor of the electronic device, and / or the processor of the hearing device is configured to output the health representation including the first suggestion.

[0095] In one or more example hearing systems and / or electronic devices, based on a first criterion being met, the system is configured to perform a cognitive test protocol through an interface of the electronic device. In other words, based on a first criterion being met, the system is configured to perform a cognitive test protocol through an interface of an accessory device. In one or more example hearing systems and / or electronic devices, based on a first criterion being met, the system is configured to perform a cognitive test protocol through an interface of a hearing device.

[0096] For example, the system can be configured to output and / or display a user interface representing a cognitive test scheme, for example, through an interface of an electronic device (e.g., a display) and / or through an interface of a hearing device (e.g., through a receiver of a hearing device). The cognitive test scheme can be configured to be executed on an electronic device by a user of a hearing device. Executing the cognitive test scheme can include outputting one or more of the following data, for example, through an interface of an electronic device (e.g., a display) and / or through an interface of a hearing device (e.g., through a receiver of a hearing device): audio data, visual data, text data (e.g., a questionnaire), and receiving one or more inputs from a user through an interface of an electronic device and / or through an interface of a hearing device. The cognitive test scheme can be executed to obtain more information about the cognitive state of the user of the hearing device, for example, when it is determined that a first criterion is met. The health representation can be based on health parameters and user input from the cognitive test scheme. The cognitive test scheme can, for example, include having the user of the hearing device repeat and / or speak one or more audio samples, for example, testing the user's voice biomarkers when repeating the audio samples. The cognitive test scheme can, for example, test one or more of the following: language parameters, acoustic parameters, language fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters.

[0097] The cognitive testing protocol may, for example, include causing the user of the hearing device to perform one or more actions and / or activities, for example, testing the user's physiological biomarkers and / or bio-motion biomarkers while performing the one or more actions and / or activities. The cognitive testing protocol may, for example, test one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, body temperature parameters, oxygen parameters, and brain activity parameters. The cognitive testing protocol may, for example, test one or more of the following: movement parameters, tremor parameters, shaking parameters, and twitching parameters.

[0098] In one or more example hearing systems and / or electronic devices, a cognitive testing protocol may be included in the health representation and / or the health representation may be based on a cognitive testing protocol.

[0099] In one or more example hearing systems, electronic devices, and / or hearing devices, determining a health parameter includes determining a first voice biomarker based on microphone input data. Determining the health parameter may, for example, include determining a second voice biomarker, a third voice biomarker, a fourth voice biomarker, a fifth voice biomarker, and / or a sixth voice biomarker. Determining a voice biomarker (e.g., a first voice biomarker) may include extracting one or more features from the sensor data. Determining a voice biomarker (e.g., a first voice biomarker) may include extracting one or more audio features from the microphone input data. A voice biomarker may be considered a biomarker that indicates one or more parameters of a voice (e.g., a voice of a hearing device user). A voice biomarker may include and / or indicate a feature (e.g., a sound feature) in the microphone input data.

[0100] In one or more example hearing systems, electronic devices, and / or hearing devices, the first criterion is based on a first voice biomarker. In other words, the first criterion includes the first voice biomarker criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first voice biomarker criterion.

[0101] In one or more example hearing systems, electronic devices, and / or hearing devices, determining a first speech biomarker includes determining one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a speech rhythm parameter. In one or more example hearing systems, the system is configured to determine (e.g., using an electronic device and / or hearing device) one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a speech rhythm parameter.

[0102] In one or more example electronic devices, a processor of the electronic device is configured to determine one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a speech rhythm parameter.

[0103] In one or more example hearing devices, the processor of the hearing device is configured to determine one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a speech rhythm parameter.

[0104] In one or more example hearing systems, electronic devices, and / or hearing devices, the first speech biomarker is based on one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a speech rhythm parameter.

[0105] Language parameters may be viewed as parameters indicative of language biomarkers. In other words, language parameters may include specific semantically related words and / or sentences, such as incomplete words and / or sentences pronounced by a user, which may indicate cognitive decline. Language parameters may, for example, indicate that a user is undergoing vocabulary and / or grammatical simplification, and / or loss of semantic ability. Language parameters may be determined based on a text transcript of microphone input data. The text transcript may be obtained via an automatic speech recognition (speech to text) algorithm or service. Language parameters may include embedded features of a deep neural network (e.g., a BERT transformer network or other sequence to sequence autoencoder).

[0106] Acoustic parameters can be considered as parameters indicative of acoustic biomarkers. In other words, acoustic parameters can include specific acoustic sounds and / or acoustic features, such as acoustic sounds emitted by a user and / or acoustic features in the user's voice, which may indicate cognitive decline. Acoustic parameters can include one or more of the following: pitch, energy level, spectral parameters (Mel-frequency cepstrum, MFCC; e.g., logMelSpec), spectral statistics (slope, roll-off point), speech spectral envelope characteristics (e.g., formants, harmonics, ratio of harmonics to formants), and / or speech quality measures, such as harmonics to noise ratio, HNR, jitter, and / or sparkle.

[0107] The speech fluency parameter may be considered as a parameter indicative of a speech fluency biomarker. In other words, the speech fluency parameter may include information about the speech fluency of a user when the user speaks. For example, when the speech fluency of the user is declining and / or indicates low speech fluency, the speech fluency parameter may indicate cognitive decline. A user of a hearing device may increasingly search for words when speaking, which may indicate that speech fluency is declining. The speech fluency parameter may, for example, indicate that the user stutters when speaking and / or that the stuttering is getting worse when speaking. The speech fluency parameter may, for example, indicate that the user speaks unclearly and / or frequently uses filler sounds, such as "uh", "um", semantic errors, infinitives, modifications, repetitions and / or new words.

[0108] Determining the first speech biomarker may include determining a coherence parameter. The coherence parameter may include information about the coherence of the user when speaking. For example, when the coherence of the user's speech decreases and / or indicates low coherence, the coherence parameter may indicate cognitive decline. The user of the hearing device may, for example, increasingly state untrustworthy and / or irrelevant details.

[0109] As can be appreciated, the use of voice biomarkers is a simple and non-invasive method of characterizing and / or monitoring health parameters.

[0110] The first criterion may include a first speech fluency criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first speech fluency criterion. For example, the first threshold may include a first speech fluency threshold. When the speech fluency parameter is below the first speech fluency threshold, the first criterion is met and the user may have cognitive decline.

[0111] The mumbling parameter may be considered a parameter indicative of a mumbling biomarker. In other words, the mumbling parameter may include information about the user mumbling while speaking. For example, when the user's mumbling may increase and / or indicate a high level of mumbling, the mumbling parameter may indicate cognitive decline. Determining the mumbling parameter may include determining that the user is speaking quietly and mumbling. In other words, determining the mumbling parameter may include determining that the user is not forming words clearly and / or the user is not articulating words, such as difficult to understand speech and / or words.

[0112] The first criterion may include a first mumbling criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first mumbling criterion. For example, the first threshold may include a first mumbling threshold. When the mumbling parameter is above the first mumbling threshold, the first criterion is met and the user may be experiencing cognitive decline.

[0113] The pitch parameter may be considered as a parameter indicating a pitch biomarker. In other words, the pitch parameter may include information about the pitch of the user's voice when speaking (e.g., pitch variation). For example, when the user's pitch increases and / or decreases, the pitch parameter may indicate cognitive decline.

[0114] The first criterion may include a first pitch criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first pitch criterion. For example, the first threshold may include a first pitch threshold. When the pitch parameter is above the first pitch threshold, the first criterion is met and the user may have cognitive decline.

[0115] The speech rhythm parameter may be considered as a parameter indicating a speech rhythm biomarker. In other words, the speech rhythm parameter may include information about the speech rhythm of the user when speaking. For example, when the speech rhythm of the user decreases, the speech rhythm parameter may indicate cognitive decline. Another example may be that the speech rhythm indicates that the user hesitates when speaking.

[0116] The first criterion may include a first speech rhythm criterion. In other words, determining whether the health parameter meets the first criterion may include determining whether the health parameter meets the first speech rhythm criterion. For example, the first threshold may include a first speech rhythm threshold. When the speech rhythm parameter is above the first speech rhythm threshold, the first criterion is met and the user may be experiencing cognitive decline.

[0117] Tone features and speech rhythm features can be regarded as prosodic features.

[0118] In one or more example hearing systems, electronic devices and / or hearing devices, the sensor data (eg, external sensor data) includes physiological data. In one or more example hearing systems, electronic devices and / or hearing devices, the health parameter is based on the physiological data.

[0119] In one or more example hearing systems and / or electronic devices, the one or more sensors include one or more physiological sensors for providing physiological data. The physiological sensors may include, for example, one or more of the following: body sensors, such as a heart rate sensor, a blood pressure sensor, a pulse sensor, a photoplethysmogram (PPG) sensor, an electrocardiogram (ECG) sensor, an electroencephalogram (EEG) sensor, a bioimpedance sensor, and a temperature sensor. The one or more sensors of the hearing device may include a body sensor, such as a capacitive and / or conductive sensor, for measuring and / or determining stress levels.

[0120] In one or more example hearing systems, electronic devices, and / or hearing devices, determining a health parameter includes determining a first physiological biomarker based on physiological data. Determining the health parameter may, for example, include determining a second physiological biomarker, a third physiological biomarker, a fourth physiological biomarker, a fifth physiological biomarker, and / or a sixth physiological biomarker. Determining the physiological biomarker (e.g., the first physiological biomarker) may include extracting one or more features (e.g., physiological features) from the sensor data. Determining the physiological biomarker (e.g., the first physiological biomarker) may include extracting one or more physiological features from the physiological data. The physiological biomarker may be considered as a biomarker of one or more parameters indicating a physiological condition of a user of the hearing device. The physiological biomarker may include and / or indicate a feature (e.g., physiological feature) in the physiological data. The physiological data may indicate and / or represent one or more physiological processes. For example, the physiological data may indicate and / or represent one or more physiological processes, such as changes in a physiological process of the user. Changes in a physiological process of the user may, for example, include changes in the throat and / or chest and changes in nerves that should control the physiological process. The physiological process may be affected by cognitive decline, and changes in the physiological process may be identified and / or detected as cognitive decline of the user.

[0121] In one or more example hearing systems, electronic devices, and / or hearing devices, the first criterion is based on a first physiological biomarker. In other words, the first criterion includes the first physiological biomarker criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first physiological biomarker criterion.

[0122] In one or more example hearing systems, electronic devices, and / or hearing devices, determining the first physiological biomarker includes determining one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a respiration parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter. In one or more example hearing systems, the system is configured to, for example, using the electronic device and / or hearing device, determine one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a respiration parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0123] In one or more example electronic devices, a processor of the electronic device is configured to determine one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0124] In one or more example hearing devices, the processor of the hearing device is configured to determine one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0125] In one or more example hearing systems, electronic devices, and / or hearing devices, the first physiological biomarker is based on one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0126] The blood pressure parameter may be considered as a parameter indicating a blood pressure biomarker. In other words, the blood pressure parameter may include information about the user's blood pressure when the user wears the hearing device. For example, when the user's blood pressure changes abnormally, such as increases and / or decreases, the blood pressure parameter may indicate cognitive decline and / or indicate an increased risk of cognitive decline.

[0127] The first criterion may include a first blood pressure criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first blood pressure criterion. For example, the first threshold may include a first blood pressure threshold and / or a second blood pressure threshold. When the blood pressure parameter is above the first blood pressure threshold and / or below the second blood pressure threshold, the first criterion is met and the user may have cognitive decline and / or indicate an increased risk of cognitive decline.

[0128] The blood flow parameters may be considered as parameters indicative of blood flow biomarkers. In other words, the blood flow parameters may include information about the blood flow of the user when the user wears the hearing device. For example, when the blood flow of the user changes abnormally, such as increases and / or decreases, the blood flow parameters may indicate cognitive decline and / or indicate an increased risk of cognitive decline.

[0129] The first criterion may include a first blood flow criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first blood flow criterion. For example, the first threshold may include a first blood flow threshold and / or a second blood flow threshold. When the blood flow parameter is above the first blood flow threshold and / or below the second blood flow threshold, the first criterion is met and the user may have cognitive decline and / or the user may have an increased risk of cognitive decline.

[0130] The heart rate parameter may be considered as a parameter indicative of a heart rate biomarker. In other words, the heart rate parameter may include information about the heart rate of the user while wearing the hearing device. For example, when the user's heart rate changes abnormally (e.g., increases and / or decreases), the heart rate parameter may indicate cognitive decline. The heart rate parameter may indicate heart rate variability.

[0131] The first criterion may include a first heart rate criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first heart rate criterion. For example, the first threshold may include a first heart rate threshold and / or a second heart rate threshold. When the heart rate parameter is above the first heart rate threshold and / or below the second heart rate threshold, the first criterion is met and the user may have cognitive decline and / or the user may have an increased risk of cognitive decline.

[0132] The breathing parameters may be considered as parameters indicating a breathing biomarker. In other words, the breathing parameters may include information about the breathing condition of the user when the user wears the hearing device. For example, when the breathing rate of the user changes abnormally (e.g., increases and / or decreases), the breathing parameters may indicate cognitive decline and / or indicate an increased risk of cognitive decline.

[0133] The first criterion may include a first breathing criterion. In other words, determining whether the health parameter meets the first criterion may include determining whether the health parameter meets the first breathing criterion. For example, the first threshold may include a first breathing rate threshold and / or a second breathing rate threshold. When the breathing parameter is above the first breathing rate threshold and / or below the second breathing rate threshold, the first criterion is met and the user may have cognitive decline and / or the user may have an increased risk of cognitive decline.

[0134] The temperature parameter may be considered as a parameter indicative of a temperature biomarker. In other words, the temperature parameter may include information about the temperature of the user when the user wears the hearing device. For example, when the user's body temperature changes abnormally (e.g., increases and / or decreases), the temperature parameter may indicate cognitive decline and / or that the user may have an increased risk of cognitive decline.

[0135] The first criterion may include a first temperature criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first temperature criterion. For example, the first threshold may include a first temperature threshold and / or a second temperature threshold. When the temperature parameter is above the first temperature threshold and / or below the second temperature threshold, the first criterion is met and the user may have cognitive decline and / or the user may have an increased risk of cognitive decline.

[0136] The oxygen parameter may be considered a parameter indicative of an oxygen biomarker. In other words, the oxygen parameter may include information about the user's oxygen while the user is wearing the hearing device. For example, when the user's oxygen rate changes abnormally (e.g., increases and / or decreases), the oxygen parameter may indicate cognitive decline and / or that the user may have an increased risk of cognitive decline.

[0137] The first criterion may include a first oxygen criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first oxygen criterion. For example, the first threshold may include a first oxygen threshold. When the oxygen parameter is below the first oxygen threshold, the first criterion is met and the user may have cognitive decline and / or the user may have an increased risk of cognitive decline.

[0138] The brain activity parameters may be considered as parameters indicating brain activity biomarkers. In other words, the brain activity parameters may include information about the brain activity of the user while wearing the hearing device. For example, when the user's brain activity changes abnormally, such as increases and / or decreases, the brain activity parameters may indicate cognitive decline and / or indicate an increased risk of cognitive decline.

[0139] The first criterion may include a first brain activity criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first brain activity criterion. For example, the first threshold may include a first brain activity threshold. When the brain activity parameter is below the first brain activity threshold, the first criterion is met and the user may have cognitive decline and / or the user may have an increased risk of cognitive decline.

[0140] In one or more example hearing systems, electronic devices and / or hearing devices, the sensor data (eg, external sensor data) includes bio-kinematic data. In one or more example hearing systems, electronic devices and / or hearing devices, the health parameter is based on the bio-kinematic data.

[0141] In one or more example hearing systems and / or electronic devices, the one or more sensors include one or more bio-motion sensors for providing bio-motion data. The bio-motion sensors may, for example, include one or more of: a motion sensor, an IMU sensor, an accelerometer, and / or a gyroscope. The bio-kinetic sensor may be configured to measure one or more movements of a user of the hearing device. For example, the bio-kinetic sensor may be configured to measure one or more head movements of a user of the hearing device.

[0142] In one or more example hearing systems, electronic devices, and / or hearing devices, determining a health parameter includes determining a first biokinetic biomarker based on biokinetic data. Determining the health parameter may, for example, include determining a second biokinetic biomarker, a third biokinetic biomarker, a fourth biokinetic biomarker, a fifth biokinetic biomarker, and / or a sixth biokinetic biomarker. Determining the biokinetic biomarker (e.g., the first biokinetic biomarker) may include extracting one or more features (e.g., biokinetic features) from the sensor data. Determining the biokinetic biomarker (e.g., the first biokinetic biomarker) may include extracting one or more biokinetic features from the biokinetic data. The biokinetic biomarker may be considered a biomarker that indicates one or more movements of a user of the hearing device. The biokinetic biomarker may include and / or indicate a feature in the biokinetic data, such as a biokinetic feature.

[0143] In one or more example hearing systems, electronic devices, and / or hearing devices, the first criterion is based on a first biodynamic biomarker. In other words, the first criterion includes the first biodynamic biomarker criterion. In other words, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first biodynamic biomarker criterion.

[0144] In one or more example hearing systems, electronic devices, and / or hearing devices, determining the first bio-motion biomarker includes determining one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0145] In one or more example hearing systems, the system is configured to determine (eg, using an electronic device and / or a hearing device) one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0146] In one or more example electronic devices, a processor of the electronic device is configured to determine one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0147] In one or more example hearing devices, the processor of the hearing device is configured to determine one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0148] In one or more example hearing systems, electronic devices, and / or hearing devices, the first bio-motion biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0149] The motion parameters may be considered as parameters indicative of motion biomarkers. In other words, the motion parameters may include information about the user's motion while the user is wearing the hearing device. For example, when the user's motion changes abnormally (e.g., increases and / or decreases), the motion parameters may indicate cognitive decline.

[0150] The tremor parameter may be considered as a parameter indicative of a tremor biomarker. In other words, the tremor parameter may include information about the user's tremor when the user wears the hearing device. For example, when the user's tremor changes abnormally (e.g., increases and / or decreases), the tremor parameter may indicate cognitive decline.

[0151] The shaking parameter may be considered as a parameter indicating a shaking biomarker. In other words, the shaking parameter may include shaking information of the user when the user wears the hearing device. For example, when the shaking of the user changes abnormally (e.g., increases), the shaking parameter may indicate cognitive decline.

[0152] The tic parameter may be considered as a parameter indicating a tic biomarker. In other words, the tic parameter may include one or more tic information of the user when the user wears the hearing device. For example, when the user's tic changes abnormally (e.g., increases), the tic parameter may indicate cognitive decline.

[0153] It shall be understood that the description of features relating to a hearing device and / or an electronic device also applies to corresponding features in the system disclosed herein, and / or a method of operating a hearing system, a method of operating a hearing device and / or a method of operating an electronic device.

[0154] Figure 1 An example hearing system is schematically shown, such as a hearing system 2 according to the present disclosure. The hearing system 2 comprises an electronic device 10 comprising a memory 10A, an interface 10B and a processor 10C. The hearing system 2 comprises a hearing device 30 comprising a memory 30A, an interface 30B, a processor 30C and one or more sensors 30D.

[0155] The electronic device 10 includes a memory 10A, an interface 10B (eg, one or more interfaces), and a processor 10C.

[0156] Optionally, the electronic device is a server device 20. In other words, the hearing system 2 may comprise a server device 20. The server device 20 comprises a memory 20A, an interface 20B (eg one or more interfaces) and a processor 20C (eg one or more processors).

[0157] Optionally, the system 2 includes a machine learning circuit configured to operate according to a machine learning model. In one or more example hearing systems, determining a health parameter includes using a machine learning model to determine a health parameter based on external sensor data, for example, using the electronic device 10, 20 and / or the hearing device 30. In other words, the electronic device 10, 20 and / or the hearing device 30 may include a machine learning circuit configured to operate according to a machine learning model. In other words, the system 2 may be configured to use a machine learning model to determine a health parameter based on external sensor data, for example, using the electronic device 10, 20 and / or the hearing device 30.

[0158] Optionally, the processor 10C may include a machine learning circuit 12 configured to operate according to a machine learning model. Optionally, the processor 20C may include a machine learning circuit 21 configured to operate according to a machine learning model. Optionally, the processor 30C may include a machine learning circuit 31 configured to operate according to a machine learning model. In one or more example electronic devices and / or systems, the models mentioned herein may be stored on a non-transitory storage medium (e.g., on a memory 10A of the electronic device 10, on a memory 20A of the server device 20, and / or on a memory 30A of the hearing device 30).

[0159] Optionally, one or more sensors 10D and / or one or more sensors 30D include a microphone for providing microphone input data. Optionally, the external sensor data includes microphone input data.

[0160] Optionally, the health parameter is based on microphone input data.

[0161] Optionally, the one or more sensors 30D and / or the one or more sensors 30D include one or more of the following: a microphone, an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor.

[0162] Optionally, the interface 10B of the electronic device 10 and / or the interface 30B of the hearing device 30 includes one or more of the following: a Bluetooth interface, a Bluetooth low energy interface, and a magnetic induction interface. For example, the interface 10B of the electronic device 10 and / or the interface 30B of the hearing device 30 may include a Bluetooth antenna and / or a magnetic interference antenna.

[0163] The system 2 is configured to acquire external sensor data from one or more sensors (e.g., one or more sensors 10D and / or one or more sensors 30D). In other words, the system 2 is configured to acquire external sensor data at the hearing device 30 and / or at the electronic device acting as the accessory device 10 and / or at the electronic device acting as the server device 20. In other words, the electronic device acting as the accessory device 10 and / or the electronic device acting as the server device 20 can acquire, receive and / or retrieve external sensor data from the hearing device 30. The hearing device 30 can transmit and / or send the external sensor data to the electronic device acting as the accessory device 10 and / or the electronic device acting as the server device 20. The system 2 is configured to determine a health parameter indicating a cognitive state of the user 1, 1B of the hearing device 30 based on the external sensor data, for example using a processor 30C of the hearing device 30 and / or a processor 10C of the electronic device acting as the accessory device 10 and / or the electronic device acting as the server device 20. In other words, the system 2 is configured to determine, based on the external sensor data, a health parameter indicative of a cognitive state of the user 1, 1B of the hearing device 30, e.g. at a processor 30C of the hearing device 30 and / or at a processor 10C of an electronic device acting as an accessory device 10 and / or at a processor 20C of an electronic device acting as a server device 20. The system 2 is configured to determine, e.g. using the processor 30C of the hearing device 30 and / or the processor 10C of an electronic device acting as an accessory device 10 and / or the electronic device acting as a server device 20, whether the health parameter meets a first criterion indicative of cognitive decline. In other words, the system 2 is configured to determine, e.g. at a processor 30C of the hearing device 30 and / or at a processor 10C of an electronic device acting as an accessory device 10 and / or an electronic device acting as a server device 20, whether the health parameter meets a first criterion indicative of cognitive decline. Optionally, the system 2 is configured to output a health representation associated with the cognitive state via an interface 30B of the hearing device 30 and / or an interface 10B of the electronic device acting as the accessory device 10 and / or an interface 20B of the electronic device acting as the server device 20, based on the health parameter satisfying the first criterion, for example using a processor 30C of the hearing device 30 and / or a processor 10C of the electronic device acting as the accessory device 10 and / or an electronic device acting as the server device 20.

[0164] A hearing device 30 is disclosed. The hearing device 30 can be considered as a hearing device with health representation and / or monitoring. The hearing device 30 includes a memory 30A, an interface 30B, a processor 30C and one or more sensors 30D. The processor 30C is configured to obtain sensor data from the one or more sensors 30D. Optionally, the processor 30C is configured to obtain 24, 34 internal sensor data from one or more sensors 10D of the electronic device 10, for example, through a network 40, such as a global network (such as the Internet) and / or a local network. The processor 30C is configured to determine a health parameter indicating a cognitive state of a user 1, 1B of the hearing device 30 based on the sensor data. The processor 30C is configured to determine whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the processor 30C is configured to output 22, 36 a health representation related to the cognitive state through the interface 30B based on the health parameter meeting the first criterion. Optionally, the user 1, 1B can provide an input 38 (such as a user input) to the hearing device 30, for example, through the interface 30B. The determination of one or more of the sensor data, health parameters, and health representations may be based on input 38 from the user 1, 1B. For example, the user 1, 1B may provide one or more inputs in response to a cognitive testing regimen.

[0165] An electronic device for use as an accessory device 10 is disclosed. The electronic device 10 comprises a memory 10A, an interface 10B and a processor 10C. The processor 10C is configured to obtain 14, 32 external sensor data from a hearing device (e.g., a hearing device 30) via the interface 10B (e.g., via a network 40, such as a global network (e.g., the Internet) and / or a local network). The processor 10C is configured to determine a health parameter indicating a cognitive state of a user 1, 1B of the hearing device 30 based on the external sensor data. The processor 10C is configured to determine whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the processor 10C is configured to output 6, 34 a health representation related to the cognitive state via the interface 10B based on the health parameter meeting the first criterion.

[0166] An electronic device used as a server device 20 is disclosed. The electronic device 20 includes a memory 20A, an interface 20B, and a processor 20C. The processor 20C is configured to obtain 16 external sensor data from a hearing device (e.g., a hearing device 30) through the interface 20B (e.g., through a network 40, such as a global network (e.g., the Internet) and / or a local network). The processor 20C is configured to determine a health parameter indicating a cognitive state of a user 1, 1B of the hearing device 30 based on the external sensor data. The processor 20C is configured to determine whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the processor 20C is configured to output 18 a health representation related to the cognitive state through the interface 20B (e.g., through the network 40, to the electronic device 10) based on the health parameter meeting the first criterion.

[0167] Optionally, the electronic device 10 includes one or more sensors 10D, such as one or more internal sensors. In one or more hearing systems, hearing devices and / or electronic devices, the system 2 is configured to obtain internal sensor data from one or more sensors 10D of the electronic device 10. In one or more hearing systems, hearing devices and / or electronic devices, the health parameters are based on the internal sensor data. The internal sensor data can be regarded as sensor data obtained from the electronic device 10. In other words, the internal sensor data can be regarded as sensor data generated by one or more sensors 10D of the electronic device 10. It can be understood that the health parameters are determined based on sensor data (e.g., external sensor data) and / or internal sensor data.

[0168] Optionally, the system 2 (e.g., the server device 20) is configured to train the machine learning model, provide an updated machine learning model, and transmit 14, 18, 24 the updated machine learning model to the electronic device 10 and / or the hearing device 30. In other words, the server device 20 is configured to train the machine learning model, provide an updated machine learning model, and transmit 18 the updated machine learning model to the electronic device 10 and / or the hearing device 30.

[0169] Optionally, outputting the health representation includes displaying 6 a user interface representing the health representation through interface 10B of electronic device 10. In other words, outputting the health representation includes displaying 6 a user interface representing the health representation through interface 10B of accessory device 10 disclosed herein, for example, to user 1, 1A.

[0170] Optionally, based on the first criterion being met, the system 2 is configured to perform the cognitive test protocol via the interface 10B of the electronic device 10. In other words, based on the first criterion being met, the system 2 is configured to perform the cognitive test protocol via the interface 10B of the accessory device 10. In one or more example hearing systems and / or electronic devices, based on the first criterion being met, the system 2 is configured to perform the cognitive test protocol via the interface 30B of the hearing device 30.

[0171] Optionally, a cognitive testing regimen may be included in the health representation and / or the health representation may be based on a cognitive testing regimen.

[0172] Optionally, the system 2 is configured to determine a health parameter, including determining a first voice biomarker based on microphone input data, for example using the electronic device 10 , 20 and / or the hearing device 30 .

[0173] Optionally, the system 2 is configured to determine one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters, for example using the electronic devices 10, 20 and / or the hearing device 30.

[0174] Optionally, the one or more sensors 10D, 30D include one or more physiological sensors for providing physiological data.

[0175] Optionally, the sensor data (eg external sensor data) includes physiological data (eg physiological data associated with the user 1 , 1B). In one or more example hearing systems, electronic devices and / or hearing devices, the health parameter is based on the physiological data.

[0176] Optionally, the system 2 is configured to determine a first physiological biomarker based on the physiological data, for example using the electronic device 10 , 20 and / or the hearing device 30 .

[0177] Optionally, the system 2 is configured to determine one or more of: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters, for example using the electronic devices 10, 20 and / or the hearing device 30.

[0178] Optionally, the system 2 is configured to determine one or more of: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters, for example using the electronic devices 10, 20 and / or the hearing device 30.

[0179] Optionally, the one or more sensors 10D, 30D include one or more bio-motion sensors for providing bio-motion data.

[0180] Optionally, the sensor data (eg, external sensor data) includes bio-kinematic data (eg, bio-kinematic data associated with user 1 , 1B).

[0181] Optionally, the system 2 is configured to determine a first bio-motion biomarker based on the bio-motion data, for example using the electronic device 10 , 20 and / or the hearing device 30 .

[0182] Optionally, the system 2 is configured to determine, for example using the electronic device 10 , 20 and / or the hearing device 30 , one or more of: a motion parameter, a tremor parameter, a shake parameter and a twitch parameter.

[0183] The hearing device 30 may be configured to perform Figure 2 Any method disclosed in.

[0184] Processor 30C is optionally configured to execute Figure 2 The operations of the hearing device 30 may be embodied in the form of executable logic routines (e.g., lines of code, software programs, etc.) stored on a non-transitory computer-readable medium (e.g., memory 30A) and executed by the processor 30C.

[0185] Furthermore, the operation of the hearing device 30 may be viewed as a method that the hearing device 10 is configured to perform. Furthermore, although the functions and operations described may be implemented in software, such functions may also be performed by dedicated hardware or firmware or some combination of hardware, firmware and / or software.

[0186] The memory 30A may be one or more of a buffer, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory, a random access memory (RAM), or other suitable devices. In a typical arrangement, the memory 30A may include a non-volatile memory for long-term data storage and a volatile memory used as a system memory for the processor 30C. The memory 30A may exchange data with the processor 30C via a data bus. There may also be a control line and an address bus ( Figure 1 Memory 30A is considered a non-transitory computer-readable medium.

[0187] Memory 30A may be configured to store information disclosed herein (e.g., sensor data, sound data, audio data, image data, health parameters, health representations, biomarkers, recommendations, and / or machine learning models) in a portion of the memory.

[0188] The electronic device 10 may be configured to perform Figure 3 Any method disclosed in.

[0189] The processor 10C is optionally configured to execute Figure 2 Any operation disclosed in A (e.g., any one or more of S204, S206A, S206A_1, S206B, S206B_1, S206C, S206C_1, S206D, S209, S210A, S212). The operation of the electronic device 10 may be embodied in the form of executable logic routines (e.g., lines of code, software programs, etc.) that are stored on a non-transitory computer-readable medium (e.g., memory 10A) and executed by the processor 10C.

[0190] Furthermore, the operation of the electronic device 10 may be considered as a method that the electronic device 10 is configured to perform. Furthermore, although the functions and operations described may be implemented in software, such functions may also be performed by dedicated hardware or firmware, or some combination of hardware, firmware and / or software.

[0191] The memory 10A may be one or more of a buffer, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory, a random access memory (RAM), or other suitable devices. In a typical arrangement, the memory 10A may include a non-volatile memory for long-term data storage and a volatile memory used as a system memory for the processor 10C. The memory 10A may exchange data with the processor 10C via a data bus. Control lines and an address bus may also exist between the memory 10B and the processor 10C ( Figure 1 Memory 10A is considered a non-transitory computer-readable medium.

[0192] Memory 10A may be configured to store information disclosed herein, such as sensor data, sound data, audio data, image data, health parameters, health indications, biomarkers, recommendations, and / or machine learning models, in a portion of the memory.

[0193] The server device 20, such as the processor 20C, can be configured to perform any operations performed by the electronic device 10, such as the accessory device 10, such as the processor 10C described herein. In other words, the description related to the processor 10C can be applied to the description of the processor 20C. For example, when the electronic device acts as a server device, the electronic device 10 and the server device 20 can be regarded as one device and / or two separate devices.

[0194] System 2 may be configured to perform Figure 4A-4B Any method disclosed in.

[0195] System 2 is optionally configured to perform Figure 4A-4BThe operations disclosed in the system 2 may include any operations disclosed in the system 2 (e.g., any one or more of S304, S306A, S306A_1, S306B, S306B_1, S306C, S306C_1, S306D, S309, S310A, S312, S314, S316, S318). The operations of the system 2 may be embodied in the form of executable logic routines (e.g., lines of code, software programs, etc.) that are stored on a non-transitory computer-readable medium (e.g., memory 10A, 30A) and executed by processors 10C, 30C.

[0196] Furthermore, the operations of system 2 may be viewed as methods that system 2 is configured to perform. Furthermore, although the functions and operations described may be implemented in software, such functions may also be implemented in dedicated hardware or firmware, or some combination of hardware, firmware, and / or software.

[0197] Figure 2 A flow chart of an example method is shown, such as the method 100. A method 100 of operating a hearing device is disclosed. The method 100 may be performed by a hearing device (eg, the hearing device 30) disclosed herein.

[0198] The method 100 comprises acquiring sensor data from one or more sensors of a hearing device ( S102 ).

[0199] The method 100 includes determining a health parameter indicative of a cognitive state of a hearing device user based on the sensor data (S104). The method 100 includes determining whether the health parameter satisfies a first criterion indicative of cognitive decline (S106). The method 100 includes outputting a health representation associated with the cognitive state based on the health parameter satisfying the first criterion (S108).

[0200] Optionally, in dependence on the health parameter not meeting the first criterion, the method 100 comprises refraining S107 from outputting S108 a health representation related to the cognitive state.

[0201] In one or more example methods, the one or more sensors include a microphone for providing microphone input data. In one or more example methods, the health parameter is based on the microphone input data.

[0202] In one or more example methods, determining S104 a health parameter includes determining S104A a first voice biomarker based on the microphone input data. In one or more example methods, the first criterion is based on the first voice biomarker.

[0203] In one or more example methods, determining S104A a first voice biomarker includes determining S104A_1 one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a voice rhythm parameter. In one or more example methods, the first voice biomarker is based on one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a voice rhythm parameter.

[0204] In one or more example methods, the one or more sensors include one or more physiological sensors for providing physiological data. In one or more example methods, the health parameter is based on the physiological data.

[0205] In one or more example methods, determining S104 a health parameter includes determining S104B a first physiological biomarker based on the physiological data. In one or more example methods, the first criterion is based on the first physiological biomarker.

[0206] In one or more example methods, determining S104B a first physiological biomarker includes determining S104B_1 one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a respiration parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter. In one or more example methods, the first physiological biomarker is based on one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a respiration parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0207] In one or more example methods, the one or more sensors include one or more biokinetic sensors for providing biokinetic data. In one or more example methods, the health parameter is based on the biokinetic data.

[0208] In one or more example methods, determining S104 a health parameter includes determining S104C a first biokinetic biomarker based on the biokinetic data. In one or more example methods, the first criterion is based on the first biokinetic biomarker.

[0209] In one or more example methods, determining S104C a first biokinetic biomarker includes determining S104C_1 one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter. In one or more example methods, the first biokinetic biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0210] In one or more example methods, the one or more sensors include one or more of: an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor.

[0211] In one or more example methods, the processor includes a machine learning circuit configured to operate according to the machine learning model. In one or more example methods, determining S104 the health parameter includes determining S104D the health parameter based on the sensor data using the machine learning model.

[0212] Figure 3 A flow chart of an example method is shown, such as method 200. A method 200 of operating an electronic device is disclosed. Method 200 may be performed by an electronic device (such as electronic device 10) disclosed herein.

[0213] A method 200 of operating an electronic device is disclosed. The method 200 comprises acquiring S202 external sensor data from a hearing device. The method 200 comprises determining S206 a health parameter indicative of a cognitive state of a user of the hearing device based on the external sensor data. The method 200 comprises determining S208 whether the health parameter satisfies a first criterion indicating cognitive decline. The method 200 comprises, in dependence on the health parameter satisfying the first criterion, outputting S210 a health representation associated with the cognitive state.

[0214] Optionally, in accordance with the health parameter not satisfying the first criterion, the method 200 comprises refraining S209 from outputting S210 a health representation associated with the cognitive state.

[0215] In one or more example methods, outputting S210 the health representation includes displaying S210A a user interface representing the health representation.

[0216] In one or more example methods, based on satisfying the first criterion, the method includes executing S212 a cognitive testing regimen.

[0217] In one or more example methods, the external sensor data includes microphone input data. In one or more example methods, the health parameter is based on the microphone input data.

[0218] In one or more example methods, determining S206 the health parameter includes determining S206A a first voice biomarker based on the microphone input data. In one or more example methods, the first criterion is based on the first voice biomarker.

[0219] In one or more example methods, determining S206A a first voice biomarker includes determining S206A_1 one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a voice rhythm parameter. In one or more example methods, the first voice biomarker is based on one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a voice rhythm parameter.

[0220] In one or more example methods, the external sensor data includes physiological data. In one or more example methods, the health parameter is based on the physiological data.

[0221] In one or more example methods, determining S206 the health parameter includes determining 206B a first physiological biomarker based on the physiological data. In one or more example methods, the first criterion is based on the first physiological biomarker.

[0222] In one or more example methods, determining S206B the first physiological biomarker includes determining S206B_1 one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter. In one or more example methods, the first physiological biomarker is based on one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0223] In one or more example methods, the external sensor data includes biokinetic data. In one or more example methods, the health parameter is based on the biokinetic data.

[0224] In one or more example methods, determining S206 a health parameter includes determining S206C a first biokinetic biomarker based on the biokinetic data. In one or more example methods, the first criterion is based on the first biokinetic biomarker.

[0225] In one or more example methods, determining S206C a first biokinetic biomarker includes determining S206C_1 one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter. In one or more example methods, the first biokinetic biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0226] In one or more example methods, the electronic device comprises one or more sensors, and the method comprises acquiring S204 internal sensor data from the one or more sensors. In one or more example methods, the health parameter is based on the internal sensor data.

[0227] In one or more example methods, the processor includes a machine learning circuit configured to operate according to the machine learning model. In one or more example methods, determining S206 the health parameter includes determining S206D the health parameter based on the sensor data using the machine learning model.

[0228] In one or more example methods, the interface includes one or more of: a Bluetooth interface, a Bluetooth low energy interface, and a magnetic induction interface.

[0229] Figure 4A-4BA flow chart of an example method (eg, method 300 ) is shown.

[0230] A method 300 of operating a hearing system is disclosed. The method 300 may be performed by a system disclosed herein (eg, the system 2).

[0231] The method 300 comprises acquiring S302 external sensor data from a hearing device. The method 300 comprises determining S306 a health parameter indicative of a cognitive state of a user of the hearing device based on the sensor data. The method 300 comprises determining S308 whether the health parameter satisfies a first criterion indicative of cognitive decline. The method 300 comprises, in dependence on the health parameter satisfying the first criterion, outputting S310 a health representation associated with the cognitive state.

[0232] Optionally, based on the health parameter not satisfying the first criterion, the method 300 comprises refraining S309 from outputting S310 a health representation associated with the cognitive state.

[0233] In one or more example methods, outputting S310 the health representation includes displaying S310A a user interface representing the health representation.

[0234] In one or more example methods, based on satisfying the first criterion, the method includes executing S312 a cognitive testing regimen.

[0235] In one or more example methods, the external sensor data includes microphone input data. In one or more example methods, the health parameter is based on the microphone input data.

[0236] In one or more example methods, determining S306 the health parameter includes determining S306A a first voice biomarker based on the microphone input data. In one or more example methods, the first criterion is based on the first voice biomarker.

[0237] In one or more example methods, determining S306A a first voice biomarker includes determining S306A_1 one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a voice rhythm parameter. In one or more example methods, the first voice biomarker is based on one or more of: a language parameter, an acoustic parameter, a speech fluency parameter, a mumbling parameter, a pitch parameter, and a voice rhythm parameter.

[0238] In one or more example methods, the external sensor data includes physiological data. In one or more example methods, the health parameter is based on the physiological data.

[0239] In one or more example methods, determining S306 the health parameter includes determining 306B a first physiological biomarker based on the physiological data. In one or more example methods, the first criterion is based on the first physiological biomarker.

[0240] In one or more example methods, determining S306B the first physiological biomarker includes determining S306B_1 one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter. In one or more example methods, the first physiological biomarker is based on one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

[0241] In one or more example methods, the external sensor data includes biokinetic data. In one or more example methods, the health parameter is based on the biokinetic data.

[0242] In one or more example methods, determining S306 a health parameter includes determining S306C a first biokinetic biomarker based on the biokinetic data. In one or more example methods, the first criterion is based on the first biokinetic biomarker.

[0243] In one or more example methods, determining S306C a first biokinetic biomarker includes determining S306C_1 one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter. In one or more example methods, the first biokinetic biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0244] In one or more example methods, the electronic device comprises one or more sensors, and the method comprises acquiring S304 internal sensor data from the one or more sensors. In one or more example methods, the health parameter is based on the internal sensor data.

[0245] In one or more example methods, the electronic device includes a machine learning circuit configured to operate according to the machine learning model. In one or more example methods, determining S306 the health parameter includes determining S306D the health parameter based on the external sensor data using the machine learning model.

[0246] In one or more example methods, the interface of the electronic device and / or the interface of the hearing device comprises one or more of: a Bluetooth interface, a Bluetooth low energy interface, and a magnetic induction interface.

[0247] In one or more example methods, the electronic device is a server device.

[0248] In one or more example methods, the method includes training S314 a machine learning model, providing S316 an updated machine learning model, and transmitting S318 the updated machine learning model to an electronic device.

[0249] In one or more example methods, the electronic device is an accessory device.

[0250] Examples of electronic devices, systems, and methods according to the present disclosure are listed in the following items:

[0251] A1. Hearing device, the hearing device comprising

[0252] Memory;

[0253] interface;

[0254] Processor; and

[0255] one or more sensors;

[0256] Wherein, the processor is configured to:

[0257] acquiring sensor data from the one or more sensors;

[0258] determining a health parameter indicative of a cognitive status of a user of the hearing device based on the sensor data;

[0259] determining whether the health parameter meets a first criterion indicative of cognitive decline; and

[0260] Based on the health parameters satisfying the first criterion, a health representation related to the cognitive state is output through the interface.

[0261] A2. The hearing device according to item A1, wherein the one or more sensors include a microphone for providing microphone input data, and wherein the health parameter is based on the microphone input data.

[0262] A3. A hearing device according to item A2, wherein determining the health parameter comprises determining a first voice biomarker based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0263] A4. A hearing device according to item A3, wherein determining the first speech biomarker includes determining one or more of the following: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters; and wherein the first speech biomarker is based on one or more of the following: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters.

[0264] A5. The hearing device according to any of the preceding items, wherein the one or more sensors include one or more physiological sensors for providing physiological data, and wherein the health parameter is based on the physiological data.

[0265] A6. The hearing device of item A5, wherein determining the health parameter comprises determining a first physiological biomarker based on the physiological data, and wherein the first criterion is based on the first physiological biomarker.

[0266] A7. A hearing device according to item A6, wherein determining the first physiological biomarker includes determining one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters; and wherein the first physiological biomarker is based on one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0267] A8. A hearing device according to any of the preceding items, wherein the one or more sensors include one or more bio-motion sensors for providing bio-motion data, and wherein the health parameter is based on the bio-motion data.

[0268] A9. The hearing device according to item A8, wherein determining the health parameter comprises determining a first biodynamic biomarker based on the biodynamic data, wherein the first criterion is based on the first biodynamic biomarker.

[0269] A10. A hearing device according to item A9, wherein determining the first biodynamic biomarker includes determining one or more of the following: movement parameters, tremor parameters, shaking parameters and twitching parameters; wherein the first biodynamic biomarker is based on one or more of the following: movement parameters, tremor parameters, shaking parameters and twitching parameters.

[0270] A11. The hearing device according to any of the preceding items, wherein the one or more sensors include one or more of the following: an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor.

[0271] A12. A hearing device according to any of the preceding items, wherein the processor includes a machine learning circuit configured to operate according to a machine learning model, wherein determining the health parameter includes determining the health parameter based on sensor data using the machine learning model.

[0272] A13. A method of operating a hearing device, the method comprising:

[0273] acquiring sensor data from one or more sensors of the hearing device;

[0274] determining a health parameter indicative of a cognitive state of a user of the hearing device based on the sensor data;

[0275] determining whether the health parameter meets a first criterion indicative of cognitive decline; and

[0276] Based on the health parameter satisfying the first criterion, a health representation associated with the cognitive state is output.

[0277] A14. A method of operating a hearing device according to item A13, wherein the one or more sensors include a microphone for providing microphone input data, and wherein the health parameter is based on the microphone input data.

[0278] A15. The method of operating a hearing device according to item A14, wherein determining (S104) the health parameter comprises:

[0279] A first voice biomarker is determined (S104A) based on the microphone input data, wherein the first criterion is based on the first voice biomarker.

[0280] A16. The method of operating a hearing device according to item A15, wherein determining (S104A) the first speech biomarker comprises:

[0281] Determine (S104A_1) one or more of the following: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters; wherein the first speech biomarker is based on one or more of the following: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters.

[0282] A17. A method of operating a hearing device according to any of items A13-A16, wherein the one or more sensors include one or more physiological sensors for providing physiological data, and wherein the health parameter is based on the physiological data.

[0283] A18. The method of operating a hearing device according to item A17, wherein determining (S104) the health parameter comprises:

[0284] A first physiological biomarker is determined (S104B) based on the physiological data, and wherein the first criterion is based on the first physiological biomarker.

[0285] A19. The method of operating a hearing device according to item A18, wherein determining (S104B) the first physiological biomarker comprises:

[0286] Determine (S104B_1) one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters; wherein the first physiological biomarker is based on one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0287] A20. A method of operating a hearing device according to any of items A13-A19, wherein the one or more sensors include one or more bio-motion sensors for providing bio-motion data, and wherein the health parameter is based on the bio-motion data.

[0288] A21. The method of operating a hearing device according to item A20, wherein determining (S104) the health parameter comprises:

[0289] A first bio-motion biomarker is determined (S104C) based on the bio-motion data, and wherein the first criterion is based on the first bio-motion biomarker.

[0290] A22. The method of operating a hearing device according to item A21, wherein determining (S104C) the first bio-motion biomarker comprises:

[0291] Determining (S104C_1) one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter; and wherein the first bio-motion biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0292] A23. A method of operating a hearing device according to any of items A13-A22, wherein the one or more sensors include one or more of the following: an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor.

[0293] A24. A method of operating a hearing device according to any of items A13-A23, wherein the processor includes a machine learning circuit configured to operate according to a machine learning model, wherein determining (S104) the health parameter includes:

[0294] Based on the sensor data, health parameters are determined (S104D) using a machine learning model.

[0295] B1. Electronic equipment, the electronic equipment comprising

[0296] Memory;

[0297] Interfaces; and

[0298] processor;

[0299] The processor is configured as:

[0300] Obtain external sensor data from the hearing device via an interface;

[0301] determining a health parameter indicative of a cognitive status of a hearing device user based on the external sensor data;

[0302] determining whether the health parameter meets a first criterion indicative of cognitive decline; and

[0303] Based on the health parameters satisfying the first criterion, a health representation associated with the cognitive state is output through the interface.

[0304] B2. The electronic device according to item B1, wherein outputting the health representation comprises displaying a user interface representing the health representation through an interface.

[0305] B3. An electronic device according to any of items B1-B2, wherein the electronic device is configured to perform a cognitive testing regimen based on satisfying the first criterion.

[0306] B4. An electronic device according to any of items B1-B3, wherein the external sensor data includes microphone input data, and wherein the health parameter is based on the microphone input data.

[0307] B5. An electronic device according to item B4, wherein determining the health parameter includes determining a first voice biomarker based on microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0308] B6. An electronic device according to item B5, wherein determining a first voice biomarker comprises determining one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters; and wherein the first voice biomarker is based on one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters.

[0309] B7. An electronic device according to any of items B1-B6, wherein the external sensor data includes physiological data, and wherein the health parameter is based on the physiological data.

[0310] B8. An electronic device according to item B7, wherein determining the health parameter includes determining a first physiological biomarker based on the physiological data, and wherein the first criterion is based on the first physiological biomarker.

[0311] B9. An electronic device according to item B8, wherein determining the first physiological biomarker includes determining one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters; and wherein the first physiological biomarker is based on one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0312] B10. An electronic device according to any of items B1-B9, wherein the external sensor data includes biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0313] B11. An electronic device according to item B10, wherein determining the health parameter comprises determining a first biokinetic biomarker based on the biokinetic data, wherein the first criterion is based on the first biokinetic biomarker.

[0314] B12. An electronic device according to item B11, wherein determining the first biodynamic biomarker comprises determining one or more of the following: motion parameters, tremor parameters, shaking parameters and twitching parameters; wherein the first biodynamic biomarker is based on one or more of the following: motion parameters, tremor parameters, shaking parameters and twitching parameters.

[0315] B13. An electronic device according to any of items B1-B12, wherein the electronic device includes one or more sensors, wherein the processor is configured to obtain internal sensor data from the one or more sensors, wherein the health parameter is based on the internal sensor data.

[0316] B14. An electronic device according to any of items B1-B13, wherein the processor includes a machine learning circuit configured to operate according to a machine learning model, wherein determining the health parameter includes determining the health parameter using the machine learning model based on external sensor data.

[0317] B15. An electronic device according to any one of items B1-B14, wherein the interface comprises one or more of the following: a Bluetooth interface, a Bluetooth low energy interface, and a magnetic induction interface.

[0318] B16. A method of operating an electronic device, the method comprising:

[0319] Acquiring external sensor data from hearing devices;

[0320] determining a health parameter indicative of a cognitive status of a hearing device user based on the external sensor data;

[0321] determining whether the health parameter meets a first criterion indicative of cognitive decline; and

[0322] Based on the health parameters satisfying the first criterion, a health representation associated with the cognitive state is output.

[0323] B17. The method of operating an electronic device according to item B16, wherein outputting (S110) a health indication comprises:

[0324] A user interface showing a health indicator is displayed (S110A).

[0325] B18. A method of operating an electronic device according to any of items B16-B17, wherein, based on satisfying the first criterion, the method comprises:

[0326] A cognitive test protocol is executed ( S112 ).

[0327] B19. A method of operating an electronic device according to any of items B16-B18, wherein the external sensor data includes microphone input data, and wherein the health parameter is based on the microphone input data.

[0328] B20. The method of operating an electronic device according to item B19, wherein determining (S106) the health parameter comprises:

[0329] A first voice biomarker is determined (S106A) based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0330] B21. The method of operating an electronic device according to item B20, wherein determining (S106A) the first voice biometric marker comprises:

[0331] Determine (S106A_1) one or more of the following: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters; wherein the first speech biomarker is based on one or more of the following: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters.

[0332] B22. A method of operating an electronic device according to any of items B16-B21, wherein the external sensor data includes physiological data, wherein the health parameter is based on the physiological data.

[0333] B23. The method of operating an electronic device according to item B22, wherein determining (S106) the health parameter comprises:

[0334] A first physiological biomarker is determined (106B) based on the physiological data, wherein the first criterion is based on the first physiological biomarker.

[0335] B24. The method of operating an electronic device according to item B23, wherein determining (S106B) the first physiological biomarker comprises:

[0336] Determine (S106B_1) one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters; wherein the first physiological biomarker is based on one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0337] B25. A method of operating an electronic device according to any of items B16-B24, wherein the external sensor data includes bio-kinematic data, and wherein the health parameter is based on the bio-kinematic data.

[0338] B26. The method of operating an electronic device according to item B25, wherein determining (S106) the health parameter comprises:

[0339] A first bio-motion biomarker is determined (S106C) based on the bio-motion data, and wherein the first criterion is based on the first bio-motion biomarker.

[0340] B27. The method of operating an electronic device according to item B26, wherein determining (S106C) the first bio-motion biomarker comprises:

[0341] Determining (S106C_1) one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter; and wherein the first bio-motion biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0342] B28. A method of operating an electronic device according to any of items B16-B27, wherein the electronic device includes one or more sensors, and wherein the method comprises:

[0343] Internal sensor data is acquired ( S104 ) from one or more sensors, and wherein the health parameter is based on the internal sensor data.

[0344] B29. A method of operating an electronic device according to any of items B16-B28, wherein the processor includes a machine learning circuit configured to operate according to a machine learning model, wherein determining (S106) the health parameter includes:

[0345] Based on the sensor data, health parameters are determined (S106D) using a machine learning model.

[0346] B30. A method for operating an electronic device according to any one of items B16-B29, wherein the interface comprises one or more of: a Bluetooth interface, a low-power Bluetooth interface, and a magnetic induction interface.

[0347] C1. Hearing system, which includes

[0348] Electronic devices, including memory, interfaces and processors; and

[0349] A hearing device including a memory, an interface, a processor, and one or more sensors;

[0350] The system configuration is:

[0351] acquiring external sensor data from one or more sensors;

[0352] determining a health parameter indicative of a cognitive status of a hearing device user based on the external sensor data;

[0353] determining whether the health parameter meets a first criterion indicative of cognitive decline; and

[0354] Based on the health parameters satisfying the first criterion, a health representation associated with the cognitive state is output.

[0355] C2. The hearing system according to item C1, wherein outputting the health representation comprises displaying a user interface representing the health representation through an interface of an electronic device.

[0356] C3. A hearing system according to any of items C1-C2, wherein upon satisfying the first criterion, the system is configured to perform a cognitive testing regimen through an interface of the electronic device.

[0357] C4. A hearing system according to any of items C1-C3, wherein the external sensor data comprises microphone input data, and wherein the health parameter is based on the microphone input data.

[0358] C5. A hearing system according to item C4, wherein determining the health parameter includes determining a first voice biomarker based on microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0359] C6. A hearing system according to item C5, wherein determining the first speech biomarker includes determining one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters; and wherein the first speech biomarker is based on one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters.

[0360] C7. A hearing system according to any of items C1-C6, wherein the external sensor data includes physiological data, and wherein the health parameter is based on the physiological data.

[0361] C8. A hearing system according to item C7, wherein determining the health parameter comprises determining a first physiological biomarker based on the physiological data, and wherein the first criterion is based on the first physiological biomarker.

[0362] C9. A hearing system according to item C8, wherein determining the first physiological biomarker includes determining one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters; and wherein the first physiological biomarker is based on one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0363] C10. A hearing system according to any of items C1-C9, wherein the external sensor data includes bio-kinematic data, and wherein the health parameter is based on the bio-kinematic data.

[0364] C11. The hearing system according to item C10, wherein determining the health parameter comprises determining a first biodynamic biomarker based on the biodynamic data, wherein the first criterion is based on the first biodynamic biomarker.

[0365] C12. A hearing system according to item C11, wherein determining the first biodynamic biomarker comprises determining one or more of: a motion parameter, a tremor parameter, a shaking parameter, and a twitch parameter; wherein the first biodynamic biomarker is based on one or more of: a motion parameter, a tremor parameter, a shaking parameter, and a twitch parameter.

[0366] C13. A hearing system according to any of items C1-C12, wherein the electronic device includes one or more sensors, wherein the system is configured to obtain internal sensor data from the one or more sensors of the electronic device, wherein the health parameter is based on the internal sensor data.

[0367] C14. A hearing system according to any of items C1-C13, wherein the hearing system includes a machine learning circuit configured to operate according to a machine learning model, wherein determining the health parameter includes determining the health parameter based on external sensor data using the machine learning model.

[0368] C15. A hearing system according to any one of items C1-C14, wherein the interface of the electronic device and / or the interface of the hearing device comprises one or more of the following: a Bluetooth interface, a low-power Bluetooth interface, and a magnetic induction interface.

[0369] C16. A hearing system according to any of items C1-C15, wherein the electronic device is a server device.

[0370] C17. A hearing system according to item C16, wherein the server device is configured to train a machine learning model, provide an updated machine learning model, and transmit the updated machine learning model to an electronic device and / or a hearing device.

[0371] C18. A hearing system according to any of items C1-C17, wherein the electronic device is an accessory device.

[0372] C19. A method of operating a hearing system, the method comprising:

[0373] Acquiring external sensor data from hearing devices;

[0374] determining a health parameter indicative of a cognitive status of a hearing device user based on the external sensor data;

[0375] determining whether the health parameter meets a first criterion indicative of cognitive decline; and

[0376] Based on the health parameter satisfying the first criterion, a health representation associated with the cognitive state is output.

[0377] C20. The method of operating a hearing system according to item C19, wherein outputting (S110) a health indication comprises:

[0378] A user interface showing a health indicator is displayed (S110A).

[0379] C21. A method of operating a hearing system according to any of items C19-C20, wherein, based on satisfying the first criterion, the method comprises:

[0380] A cognitive test protocol is executed ( S112 ).

[0381] C22. A method of operating a hearing system according to any of items C19-C22, wherein the external sensor data includes microphone input data, and wherein the health parameter is based on the microphone input data.

[0382] C23. The method of operating a hearing system according to item C22, wherein determining (S106) the health parameter comprises:

[0383] A first voice biomarker is determined (S106A) based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0384] C24. The method of operating a hearing system according to item C23, wherein determining (S106A) the first speech biomarker comprises:

[0385] Determine (S106A_1) one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters; and wherein the first speech biomarker is based on one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters and speech rhythm parameters.

[0386] C25. A method of operating a hearing system according to any of items C19-C24, wherein the external sensor data includes physiological data, and wherein the health parameter is based on the physiological data.

[0387] C26. The method of operating a hearing system according to item C25, wherein determining (S106) the health parameter comprises:

[0388] A first physiological biomarker is determined (106B) based on the physiological data, and wherein the first criterion is based on the first physiological biomarker.

[0389] C27. The method of operating a hearing system according to item C26, wherein determining (S106B) the first physiological biomarker comprises:

[0390] Determine (S106B_1) one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters; wherein the first physiological biomarker is based on one or more of the following: blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0391] C28. A method of operating a hearing system according to any of items C19-C27, wherein the external sensor data includes biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0392] C29. The method of operating a hearing system according to item C28, wherein determining (S106) the health parameter comprises:

[0393] A first biokinetic biomarker is determined (S106C) based on the biokinetic data, wherein the first standard is based on the first biokinetic biomarker.

[0394] C30. The method of operating a hearing system according to item C29, wherein determining (S106C) the first biokinetic biomarker comprises:

[0395] Determining (S106C_1) one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter; wherein the first biodynamic biomarker is based on one or more of: a motion parameter, a tremor parameter, a shake parameter, and a twitch parameter.

[0396] C31. A method of operating a hearing system according to any of items C19-C30, wherein the electronic device comprises one or more sensors, and wherein the method comprises:

[0397] Internal sensor data is acquired ( S104 ) from one or more sensors, and wherein the health parameter is based on the internal sensor data.

[0398] C32. A method of operating a hearing system according to any of items C19-C31, wherein the electronic device includes a machine learning circuit configured to operate according to a machine learning model, wherein determining (S106) the health parameter includes:

[0399] Using a machine learning model, health parameters are determined (S106D) based on external sensor data.

[0400] C33. A method of operating a hearing system according to any one of items C19-C32, wherein the interface of the electronic device and / or the interface of the hearing device comprises one or more of: a Bluetooth interface, a low-power Bluetooth interface, and a magnetic induction interface.

[0401] C34. A method of operating a hearing system according to any of items C19-C33, wherein the electronic device is a server device.

[0402] C35. A method of operating a hearing system according to C34, wherein the method comprises:

[0403] training ( S114 ) a machine learning model;

[0404] providing (S116) an updated machine learning model; and

[0405] The updated machine learning model is transmitted (S118) to the electronic device.

[0406] C36. A method of operating a hearing system according to any of items C19-C35, wherein the electronic device is an accessory device.

[0407] The use of the terms "first," "second," "third," and "fourth," "primary," "secondary," "tertiary," etc., do not imply any particular order, but are included to identify the individual elements. Furthermore, the use of the terms "first," "second," "third," and "fourth," "primary," "secondary," "tertiary," etc., do not imply any order or importance, but rather the terms "first," "second," "third," and "fourth," "primary," "secondary," "tertiary," etc., are used to distinguish one element from another. Please note that the terms "first," "second," "third," and "fourth," "primary," "secondary," "tertiary," etc., are used here and elsewhere for labeling purposes only and are not intended to indicate any particular spatial or temporal order. Furthermore, labeling a first element does not imply the existence of a second element, and vice versa.

[0408] It is understood that the figure includes some circuits or operations shown with solid lines and some circuits, components, features or operations shown with dotted lines. The circuits or operations included in the solid lines are circuits, components, features or operations included in the most extensive examples. The circuits, components, features or operations included in the dotted lines are examples that can be included in or part of the circuits, components, features or operations of the solid line examples, or other circuits, components, features or operations that can be supplemented as circuits, components, features or operations of the solid line examples. It should be understood that these operations do not need to be performed in the order shown. In addition, it should be understood that not all operations need to be performed. The example operations can be performed in any order and in any combination. It should be understood that these operations do not need to be performed in the order shown. The circuits, components, features or operations included in the dotted lines can be considered optional.

[0409] Other operations not described herein may be incorporated into the example operations. For example, one or more additional operations may be performed before, after, simultaneously, or between the operations described.

[0410] Certain features discussed above as separate implementations may also be implemented in combination as a single implementation. Conversely, features described as single implementations may also be implemented in multiple implementations, either individually or in any suitable subcombination. Furthermore, while the features described above may be described as functioning in certain combinations, in some cases one or more features in a claimed combination may be excised from the combination, and the combination may be claimed as any subcombination or variation of any subcombination.

[0411] It should be noted that the word "comprising" does not necessarily exclude the presence of other elements or steps than those listed.

[0412] It should be noted that the word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements.

[0413] It should also be noted that any reference signs do not limit the scope of the claims, that examples may be implemented at least partially by hardware and software, and that multiple "means," "units," or "devices" may be represented by the same hardware.

[0414] The degree language used herein, such as the terms "approximately", "about", "generally" and "substantially" used herein, means a value, amount or feature close to the value, amount or feature, but still performs the desired function or achieves the desired result. For example, the terms "approximately", "approximately", "generally" and "substantially" can refer to an amount within 10% less than or equal to the amount, within 5% less than or equal to the amount, within 1% less than or equal to the amount, within 0.1% less than or equal to the amount, and within 0.01% less than or equal to the amount. If the amount is 0 (e.g., none, no), the above range can be a specific range, rather than within a specific % of the value. For example, within 10 weight / volume % less than or equal to the amount, within 5 weight / volume % less than or equal to the amount, within 1 weight / volume % less than or equal to the amount, within 0.1 weight / volume % less than or equal to the amount, and within 0.01 weight / volume % less than or equal to the amount.

[0415] Although features have been shown and described, it should be understood that they are not intended to limit the claimed disclosure, and that it will be apparent to those skilled in the art that various changes and modifications may be made without departing from the scope of the claimed disclosure. Accordingly, the specification and drawings should be regarded as illustrative rather than restrictive. The claimed disclosure is intended to cover all alternatives, modifications, and equivalents.

[0416] Reference List

[0417] 1.1A, 1B users

[0418] 2 System

[0419] 4 Input, User Input

[0420] 6 Health display and output

[0421] 10 Electronic equipment and accessory equipment

[0422] 10A One or more interfaces

[0423] 10B memory

[0424] 10C Processor

[0425] 10D One or more sensors

[0426] 12 Machine Learning Circuits

[0427] 13 Control, transmission

[0428] 14 Get

[0429] 16 Get

[0430] 18 Control, transmission

[0431] 20 Electronic equipment, server equipment

[0432] 20A Memory

[0433] 20B One or more interfaces

[0434] 20C Processor

[0435] 21 Machine Learning Circuit

[0436] 22 Control, transmission

[0437] 24 Get

[0438] 30 Hearing equipment

[0439] 30A One or more interfaces

[0440] 30B memory

[0441] 30C Processor

[0442] 30D One or more sensors

[0443] 31 Machine Learning Circuit

[0444] 32 Control, transmission

[0445] 34 Get

[0446] 36 Health display and output

[0447] 38 Input, User Input

[0448] 40 Network

Claims

1. A hearing system, comprising: Electronic devices, including memory, interfaces and processors; and A hearing device including a memory, an interface, a processor, and one or more sensors; Wherein, the system is configured as follows: acquiring external sensor data from one or more sensors; determining a health parameter indicative of a cognitive status of a hearing device user based on the external sensor data; determining whether the health parameter meets a first criterion indicative of cognitive decline; and Based on the health parameters satisfying the first criterion, a health representation associated with a cognitive state is output.

2. The hearing system of claim 1 , wherein outputting the health indication comprises: A user interface representing a health indicator is displayed through an interface of an electronic device.

3. A hearing system according to any one of the preceding claims, wherein: Based on satisfying the first criterion, the system is configured to execute a cognitive testing regimen through an interface of the electronic device. 4 . The hearing system according to claim 1 , wherein the external sensor data comprises microphone input data, and wherein the health parameter is based on the microphone input data.

5. The hearing system of claim 4, wherein determining the health parameter comprises: A first voice biomarker is determined based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

6. The hearing system of claim 5, wherein determining the first speech biomarker comprises: Determining one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters; and wherein the first speech biomarker is based on one or more of: language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters.

7. The hearing system according to any of the preceding claims, wherein the external sensor data comprises physiological data, and wherein the health parameter is based on the physiological data. 8 . The hearing system of claim 7 , wherein determining the health parameter comprises determining a first physiological biomarker based on the physiological data, and wherein the first criterion is based on the first physiological biomarker.

9. The hearing system of claim 8, wherein determining the first physiological biomarker comprises determining one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter; and wherein the first physiological biomarker is based on one or more of: a blood pressure parameter, a blood flow parameter, a heart rate parameter, a breathing parameter, a temperature parameter, an oxygen parameter, and a brain activity parameter.

10. The hearing system according to any of the preceding claims, wherein the external sensor data comprises bio-kinematic data, and wherein the health parameter is based on the bio-kinematic data. 11 . The hearing system of claim 10 , wherein determining the health parameter comprises determining a first bio-motion biomarker based on the bio-motion data, and wherein the first criterion is based on the first bio-motion biomarker.

12. A hearing system according to claim 11, wherein determining the first bio-motion biomarker includes determining one or more of the following: motion parameters, tremor parameters, shaking parameters and twitch parameters; and wherein the first bio-motion biomarker is based on one or more of the following: motion parameters, tremor parameters, shaking parameters and twitch parameters.

13. The hearing system according to any of the preceding claims, wherein the electronic device comprises one or more sensors, and wherein the hearing system is configured to: obtain internal sensor data from the one or more sensors of the electronic device, and wherein the health parameter is based on the internal sensor data.

14. The hearing system according to any of the preceding claims, wherein the hearing system comprises a machine learning circuit configured to operate according to a machine learning model, wherein determining the health parameter comprises: Determine health parameters using machine learning models based on external sensor data. 15 . The hearing system according to claim 1 , wherein the interface of the electronic device and / or the interface of the hearing device comprises one or more of: a Bluetooth interface, a Bluetooth Low Energy interface and a magnetic induction interface.

16. The hearing system according to any of the preceding claims, wherein the electronic device is a server device.

17. The hearing system of claim 16, wherein the server device is configured to train a machine learning model, provide an updated machine learning model, and transmit the updated machine learning model to an electronic device and / or a hearing device.

18. The hearing system according to any of the preceding claims, wherein the electronic device is an accessory device.

19. A method of operating a hearing system, the method comprising: Acquiring external sensor data from hearing devices; determining a health parameter indicative of a cognitive status of a hearing device user based on the external sensor data; Determining whether the health parameters meet the first criteria indicating cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with the cognitive state is output.

Images