Electronic device with hearing device based on health characterization and / or monitoring and related methods

Abstract

The invention provides an electronic device. The electronic device includes a memory, an interface, and a processor. The processor is configured to: acquire external sensor data from the hearing device via the interface; a health parameter, such as a parameter indicative of a cognitive state of the hearing device user, is determined based on the external sensor data. The processor is configured to determine whether the health parameter satisfies a first criterion indicative of a decline of cognitive ability. The processor is configured to output a health representation related to the cognitive state, for example, in accordance with the health parameter satisfying a first criterion (e.g., via the interface).

Description

Technical Field

[0001] The present invention relates to the field of electronic devices, and in particular to an electronic device with a hearing device based on health characterization and / or monitoring and a related method. Background Art

[0002] Hearing loss has been linked to cognitive impairment and dementia, and has been identified as the largest modifiable risk factor for dementia if addressed in early middle age, such as in the age group of 45-65. Furthermore, the risk of developing dementia increases for every 10-decibel increase in hearing loss, according to the Lancet report.

[0003] Additionally, for patients with mild cognitive impairment, the use of hearing aids was associated with a significantly lower risk of developing dementia compared to patients with hearing loss who did not use hearing aids. The scientific hypothesis is that hearing loss leads to an increased cognitive load, which calls on other parts of the brain at the expense of other functions and over time leads to a reduction in cognitive reserve until dementia sets in. The World Health Organization (WHO) estimates that 55 million people worldwide have dementia, most of whom live in low- and middle-income countries. WHO predicts that the global prevalence of dementia 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 long-term, accurate and convenient technology to characterize and / or monitor a user's health, such as characterizing and / or monitoring a user's cognitive state and its development.

[0005] Therefore, there is a need for systems for health characterization and / or monitoring and methods for health characterization and / or monitoring that can alleviate, mitigate or address existing deficiencies and can provide users with improved health characterization and / or monitoring through improved cognitive state characterization and / or monitoring and greater awareness of cognitive health.

[0006] The present invention discloses a hearing device. The hearing device can be regarded as a hearing device with health representation and / or monitoring functions. The hearing device includes a memory, an interface, a processor, and one or more sensors, wherein the processor is configured to obtain (e.g., receive and / or retrieve) sensor data from the one or more sensors; determine a health parameter (e.g., a parameter indicating a cognitive state of a hearing device user) based on the sensor data; and optionally determine whether the health parameter meets a first criterion (e.g., a criterion indicating cognitive decline). Optionally, the processor is configured to output a health representation related to the cognitive state (e.g., via the interface), for example, based on the health parameter meeting the first criterion.

[0007] The present invention discloses a method for operating a hearing device. The method includes: acquiring sensor data from one or more sensors of the hearing device; determining a health parameter (e.g., a parameter indicating a cognitive state of a user of the hearing device) based on the sensor data; and determining whether the health parameter meets a first criterion (e.g., a criterion indicating cognitive decline). Optionally, the method includes, for example, outputting a health representation associated with the cognitive state based on the health parameter meeting the first criterion.

[0008] The present invention further discloses an electronic device. The electronic device includes a memory, an interface, and a processor. The processor is configured to obtain external sensor data from a hearing device via the interface; determine a health parameter (e.g., a parameter indicating a cognitive state of a user of the hearing device) based on the external sensor data. 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 (e.g., via the interface), e.g., based on the health parameter meeting the first criterion.

[0009] In addition, the present invention discloses a method for operating an electronic device. The method includes: obtaining sensor data, such as external sensor data from a hearing device; determining a health parameter (such as a parameter indicating a cognitive state of a user of the hearing device) based on the sensor data (such as the external sensor data); and determining whether the health parameter meets a first criterion (such as a criterion indicating cognitive decline). Optionally, the method includes, for example, outputting a health representation related to the cognitive state based on the health parameter meeting the first criterion.

[0010] The present invention also discloses a hearing system. The hearing system includes an electronic device, which includes a memory, an interface, and a processor. The hearing system includes a hearing device, which includes 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 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 a decline in cognitive ability. Optionally, the system is configured to output a health representation related to the cognitive state according to 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 accordance with the health parameter satisfying the first criterion, outputting a health representation associated with the cognitive state.

[0012] The hearing systems, hearing devices, electronic devices and related methods of the present invention provide improved health characterization and / or monitoring. That is, the present invention can provide improved sensor-based (e.g., audio-based) health characterization and / or monitoring of hearing device users with greater 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 greater accuracy. In addition, by using the hearing device to provide sensor data, the sensor can be placed in a position close to the artery, which can provide better measurement results and thus obtain more accurate sensor data. It will be appreciated that by using the hearing device to provide sensor data, motion artifacts can be reduced, for example, compared to sensors placed on the user's hands and feet.

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

[0014] It will be appreciated that the present invention may improve feedback about a user's cognitive state, which feedback may be more understandable to the user. The present invention improves health awareness of users, in particular about cognitive health awareness of hearing device users. That is, the present invention may raise awareness of the importance of cognitive health and diseases associated with cognitive decline. For example, by providing a health representation, the present invention may improve visualization and / or comprehensibility for hearing device users. Thus, the health representation may, for example, provide information about cognitive state based on health parameters. It is well known that hearing devices are worn for long periods of time during the day, and therefore hearing devices with health characterization and / or monitoring capabilities increase the likelihood of, for example, detecting cognitive decline.

[0015] Thereby, the present invention may provide a user of a hearing device with a customized representation of health, e.g. based on long-term sensor data. Furthermore, the present invention may encourage increased use of hearing devices, e.g. in order to reduce the risk of cognitive decline.

[0016] It will be appreciated that the present invention provides for health characterization and / or monitoring of hearing device users, for example, early detection and / or identification of cognitive decline in hearing device users. For example, hearing device users may be screened for cognitive decline (e.g., cognitive impairment) on an ongoing basis. This may reduce long-term healthcare costs and reduce the burden on caregivers and healthcare systems. The present invention provides a flexible and non-invasive way of characterizing and / or monitoring the health of hearing device users, for example, by using sensor data from the hearing device. In other words, the present invention may provide a low-cost technique for health characterization and / or monitoring of hearing device users, which the user may also perform remotely from home.

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

[0018] The above and other features and advantages of the present invention will become apparent to those skilled in the art through the following detailed description of the embodiments of the present invention in conjunction with the accompanying drawings, in which: Figure 1 schematically illustrates an exemplary hearing system according to the present invention; Figure 2 is a flow chart of an exemplary method according to the present invention; Figure 3 is a flow chart of an exemplary method according to the present invention; Figure 4A-4B is a flow chart of an exemplary method according to the present invention. DETAILED DESCRIPTION

[0019] The following will describe various embodiments and details with reference to the relevant drawings. It should be noted that these drawings may not be drawn to scale, and that elements with similar structures or functions are represented by similar reference numerals throughout the drawings. It should also be noted that the drawings are intended only to facilitate the description of the embodiments and are not intended to be an exhaustive description of the invention or to limit the scope of the invention. In addition, the illustrated embodiments do not necessarily have all the aspects or advantages shown. Aspects or advantages associated with a particular embodiment are not limited to that embodiment and may be implemented in any other embodiment even if not shown or explicitly described in other embodiments.

[0020] For the sake of clarity, the accompanying drawings are schematic and simplified, and they only show details that are helpful for understanding the present invention, while other details are omitted. In this article, the same reference numerals are used to represent the same or corresponding components.

[0021] The present invention discloses a hearing system. The hearing system can be regarded as a system for health characterization and / or monitoring. In other words, the hearing system can be regarded as a system for health characterization and / or monitoring of a hearing device user (eg, a user wearing the hearing device).

[0022] The hearing system includes an electronic device, which includes a memory, an interface, and a processor. The electronic device of the hearing system may be the electronic device disclosed in the present invention. The hearing system includes a hearing device, which includes a memory, an interface, a processor, and one or more sensors. The hearing device of the hearing system may be the hearing device disclosed in the present invention.

[0023] The hearing device of the present invention may comprise one or more processors, a memory, an interface and one or more transducers, such as one or more microphones (eg a first microphone) and / or a receiver (eg a hearing device speaker).

[0024] 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.

[0025] A hearing device may be an earplug, hearing aid, headset, personal sound amplification product (PSAP), over-the-counter (OTC) hearing device, hearing protection device, custom hearing device, or other hearing device that is worn over the ear. Hearing devices may include both prescription and over-the-counter devices.

[0026] Hearing devices may be embodied in various 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 the ear of a user and an in-the-ear (ITE) component configured to be partially or fully inserted into the ear canal of a user. Typically, the 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., output transducer) is included in the BTE component and sound is conducted to the ITE component via an acoustic tube connecting the BTE and ITE components, while the term "RIE, RIC, and MaRIE devices" may refer to a hearing device in which a receiver is included in the ITE component and the ITE component is connected to the BTE component via a connecting cable or wire configured to transmit electrical signals between the BTE and ITE components.

[0027] Hearing devices can be behind the ear (BTE), in the ear (ITE), in the ear canal (ITC), receiver in the ear canal (RIC), or receiver in the ear (RITE). Hearing aids can be binaural.

[0028] In one or more exemplary hearing systems, hearing devices and / or electronic devices, the hearing device may be considered a user hearing device, such as a headphone, an in-ear headset, a hearing aid, an over-the-counter (OTC) hearing device and / or a hearing protection device. In one or more exemplary hearing systems and / or hearing devices, the hearing device may include one or more transceivers for wireless communication. In one or more exemplary hearing systems and / or hearing devices, the hearing device may facilitate wired communication, such as by using a wire (e.g., a cable).

[0029] The hearing device can be configured to wirelessly communicate with one or more devices, such as another hearing device (e.g., as part of a binaural hearing system) and / or with one or more accessory devices / electronic devices (e.g., a smartphone and / or a smart watch), such as via an interface. The hearing device optionally includes an antenna for converting one or more wireless input signals. The wireless input signal can 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 can 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 in the present invention can be based on one or more wireless input signals, such as wireless input signals from an external source. This can, for example, provide information about the user's environment, which can be used to determine the health parameters disclosed in the present invention.

[0030] The hearing device may optionally comprise a radio transceiver connected 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 the transceiver input signal or provided as separate transceiver input signals at different transceiver outputs of the radio transceiver. The hearing device may comprise a plurality of antennas and / or an antenna which may be configured to operate in one or more antenna modes.

[0031] In one or more hearing systems, hearing devices and / or electronic devices, one or more sensors include a microphone for providing microphone input data. That is, one or more sensors may include a group of microphones. In one or more hearing systems and / or electronic devices, the 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 to provide N microphone signals, where N is an integer between 1 and 10. In one or more exemplary hearing devices, the number of microphones N is two, three, four, five or more. The microphone may include a third microphone for providing a third microphone input signal. In one or more exemplary hearing devices, the microphone input data may come from a single microphone signal, such as 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 ambient microphone for picking up self-sound (e.g., the user's own voice). This may filter out external speech and / or sounds of the user's environment, for example, substantially picking up only the user's voice. In one or more hearing systems, hearing devices and / or electronic devices, the health parameters are based on microphone input data.

[0032] In one or more hearing systems, hearing devices and / or electronic devices, one or more sensors include one or more of a microphone, an optical sensor, a magnetic sensor, a galvanic sensor, a motion sensor and a capacitive sensor. An example of an optical sensor is a photoplethysmogram (PPG) sensor. An example of a galvanic 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, for example, include a magnetic sensor (e.g., a magnetometer). An example of a capacitive sensor may include a capacitive microphone and / or a temperature sensor.

[0033] 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, a bioimpedance sensor and / or a temperature sensor. The one or more sensors of the hearing device may include a body sensor that is a capacitance and / or conductivity sensor, for example for measuring and / or determining a stress level.

[0034] The sensor data disclosed herein may be obtained from one or more of the above-mentioned sensors. That is, the sensor data may be generated and / or provided by any one or more of the above-mentioned sensors.

[0035] 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 based on the signal input to the processor. The input of the processor is optionally connected to an output of a corresponding microphone and / or a 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.

[0036] The hearing system, hearing device and / or electronic device may be configured to communicate wirelessly via a wireless communication system, for example a short range wireless communication system such as Wi-Fi, Bluetooth, Zigbee, IEEE 802.11, IEEE 802.15, infrared or the like.

[0037] 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 the following: New Radio (NR), Narrow-band IoT, NB-IoT, and Long Term Evolution - enhanced Machine Type Communication (LTE-M), millimeter wave communication (e.g., millimeter wave communication within a licensed band, such as device-to-device millimeter wave communication within a licensed band).

[0038] 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 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 comprise a Bluetooth antenna and / or a magnetic interference antenna.

[0039] The system is configured to acquire external sensor data from one or more sensors. That is, the system is configured to acquire external sensor data on a hearing device and / or an electronic device. That is, the external sensor data may be acquired, received and / or retrieved by the electronic device from the hearing device. The external sensor data may be transmitted and / or sent by the hearing device 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. That is, 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 on a processor of the hearing device and / or a processor of the electronic device. The system is configured to determine, for example using a processor of the hearing device and / or a processor of the electronic device, whether the health parameter meets a first criterion indicating cognitive decline. That is, the system is configured to determine, for example on a processor of the hearing device and / or a processor of the electronic device, 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 via an interface of the hearing device and / or an interface of the electronic device, for example by using a processor of the hearing device and / or a processor of the electronic device, based on the health parameter meeting the first criterion.

[0040] The present invention discloses a hearing device. The hearing device can be regarded as a hearing device with health characterization and / or monitoring functions. 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 via the interface according to the health parameter meeting the first criterion.

[0041] The present invention discloses an electronic device. The electronic device includes a memory, an interface, and a processor. The processor is configured to obtain external sensor data from a hearing device via 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 meets a first criterion indicating cognitive decline. Optionally, the processor is configured to output a health representation related to the cognitive state via the interface according to the health parameter meeting the first criterion.

[0042] The external sensor data and sensor data disclosed herein may be used interchangeably. The external sensor data may be considered as sensor data acquired from a hearing device. That is, the external sensor data may be considered as sensor data generated by one or more sensors of a hearing device.

[0043] 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. That is, the internal sensor data can be regarded as sensor data generated by one or more sensors of the electronic device. It can be understood that the health parameters are determined based on sensor data (e.g., external sensor data) and / or internal sensor data.

[0044] One or more sensors of an electronic device (e.g., an accessory device) may include one or more of 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 (e.g., a magnetometer). An example of a capacitive sensor may include a capacitive microphone and / or a temperature sensor.

[0045] In one or more hearing systems, hearing devices and / or electronic devices, one or more sensors of the electronic device (e.g., 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, a bioimpedance sensor, and a temperature sensor. The one or more sensors of the hearing device may include a body sensor that is a capacitance and / or conductivity sensor, for example, for measuring and / or determining a stress level.

[0046] The internal sensor data disclosed herein can be obtained from one or more of the above-mentioned sensors. That is, the internal sensor data can be generated and / or provided by any one or more of the above-mentioned sensors.

[0047] In one or more exemplary hearing systems, hearing devices and / or electronic devices, the one or more sensors include one or more motion sensors, for example, accelerometers, inertial motion sensors, gyroscopes, altimeters and / or location sensors such as GPS sensors.

[0048] In one or more exemplary 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 exemplary 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.

[0049] In one or more exemplary 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, an accessory device).

[0050] In one or more exemplary hearing systems and / or electronic devices, the electronic device is a server device.

[0051] In one or more exemplary hearing systems and / or electronic devices, the electronic device is an accessory device.

[0052] The 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. That is, the electronic device may be configured to act as a server device and / or an accessory device. The accessory device may, for example, be or include a mobile phone (e.g., a smartphone), a smart watch, a smart speaker, a tablet computer, a computer (e.g., a laptop or PC), or a tablet computer. That is, the electronic device may, for example, be a user device, such as a mobile phone or a computer, which is configured to perform health characterization and / or monitoring. In one or more exemplary 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 small electronic device. In one or more exemplary hearing systems, the accessory device may include one or more transceivers for wireless communication. In one or more exemplary hearing systems, the accessory device may facilitate wired communication, for example, by using a cable (e.g., a cable).

[0053] The server device may be configured in the 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 on an electronic device and / or a server device.

[0054] 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 referred to as cognitive parameters. That is, 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. That is, 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 series of features that together constitute a biomarker. For example, based on microphone input data, the cognitive parameters may be considered as a series 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.

[0055] It is understood that the health parameter may include a score indicating the cognitive state of the user of the hearing device, such as a health score. That is, 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 resistance (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 affect the user's cognitive ability. Therefore, the cognitive state may indicate the presence of a mental illness.

[0056] In one or more exemplary hearing systems, based on the health parameter not satisfying a first criterion, the system is configured to inhibit outputting a health representation associated with the cognitive state.

[0057] In one or more exemplary hearing devices, based on the health parameter not satisfying the first criterion, the processor of the hearing device is configured to disable outputting the health representation associated with the cognitive state.

[0058] In one or more exemplary electronic devices, based on the health parameter not satisfying a first criterion, a processor of the electronic device is configured to disable output of a health representation associated with the cognitive state.

[0059] The first criterion may comprise a threshold value indicating cognitive decline of the hearing device user, 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 user's age. Thus, the first criterion may indicate cognitive decline relative to one or more user parameters. For example, the first criterion may indicate cognitive decline relative to the user's age, for example, compared with normal cognitive ability of a peer. One or more user parameters may also comprise historical user data of the hearing device user. 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 hearing device user. Thus, it may be determined whether the user has experienced cognitive decline over time based on the user's own historical health parameters (e.g. cognitive ability).

[0060] 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 specific range indicating the first criterion. That is, 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. That is, if the health parameter satisfies the first criterion, the hearing device user may be considered to have cognitive decline. That is, when the health parameter satisfies the first criterion, it is determined that one or more cognitive abilities of the hearing device user are declining. For example, the user's ability to hear, speak, see, and / or move may be determined to be declining.

[0061] A cognitive decline in a health parameter, such as a decline in a user's cognitive state, can be determined based on a previous (e.g., historical) cognitive state of the user, and / or based on a normal cognitive state of the person. That is, a cognitive decline in a 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, the same gender, and / or having approximately the same physiological state. A cognitive decline can be considered a deterioration in cognitive abilities (such as memory, attention, problem-solving abilities, verbal abilities, and / or language skills, etc.). That is, a cognitive decline can be considered a deterioration in cognitive abilities over time, for example, compared to a user's historical cognitive state, and / or compared to a normal cognitive state of a person of approximately the same age, the same gender, and / or having approximately the same physiological state.

[0062] In one or more exemplary hearing systems, the system is configured to determine a health indicator related to a cognitive state based on sensor data (e.g. based on external sensor data), e.g. on an electronic device and / or a hearing device. That is, the system is configured to determine a health indicator related to a cognitive state based on sensor data (e.g. based on external sensor data), e.g. using a processor of the electronic device and / or a processor of the hearing device.

[0063] In one or more exemplary electronic devices, the processor is configured to determine a health indicator related to a cognitive state based on sensor data (eg, based on external sensor data).

[0064] In one or more exemplary hearing devices, the processor is configured to determine a health indicator related to a cognitive state based on the sensor data.

[0065] In one or more exemplary hearing systems, the system includes a machine learning circuit configured to operate according to a machine learning model. In one or more exemplary hearing systems, determining the health parameter includes, for example, using an electronic device and / or a hearing device, using a machine learning model to determine the health parameter based on external sensor data. That is, the electronic device and / or the hearing device may include a machine learning circuit configured to operate according to the machine learning model. That is, the system may be configured to, for example, use an electronic device and / or a hearing device to determine the health parameter based on external sensor data using a machine learning model.

[0066] In one or more exemplary hearing devices, the processor includes a machine learning circuit configured to operate according to the machine learning model. In one or more exemplary hearing devices, determining the health parameter includes determining the health parameter using the machine learning model based on the sensor data.

[0067] In one or more exemplary electronic devices, the processor includes a machine learning circuit configured to operate according to the machine learning model. In one or more exemplary electronic devices, determining the health parameter includes determining the health parameter using the machine learning model based on the external sensor data.

[0068] That is, the electronic device and / or the 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 considered 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).

[0069] The machine learning model may, for example, include or utilize neural networks, artificial intelligence, deep learning, and / or machine learning.

[0070] In one or more exemplary hearing systems, electronic devices and / or hearing devices, the machine learning model includes a model layer, which includes an input layer, one or more intermediate layers, and an output layer for providing health parameters. In one or more exemplary hearing systems, electronic devices and / or hearing devices, the machine learning model includes a neural network. In one or more exemplary hearing systems, electronic devices and / or hearing devices, the machine learning model includes a neural network layer, which includes an input layer, one or more intermediate layers, and an output layer for providing health parameters. That is, the input layer, 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 considered as hidden layers (e.g., hidden features). One or more intermediate layers can include a first intermediate layer. The machine learning model may include a lookup table with multiple parameters (e.g., at least four parameters).

[0071] The models described herein (e.g., machine learning models) can be viewed as models and / or schemes and / or mechanisms and / or methods 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 described herein (e.g., machine learning models) can be based on the same model architecture. The model architecture can be based on a neural network, for example including one or more different types of layers and / or number of layers. The model architecture can be viewed as a configuration of a model, for example including one or more parameters of a model.

[0072] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the models described 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 an electronic device and / or hearing device configured to execute the model. In one or more exemplary 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. That is, 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 described herein, such as health parameters, speech biomarkers, physiological biomarkers, and / or biodynamic biomarkers. In general, the biomarkers described herein, such as voice biomarkers, physiological biomarkers, and / or biodynamic biomarkers, can indicate and / or represent a user's energy usage and / or energy level. Energy usage and / or energy level can provide an indication of the user's cognitive state (e.g., cognitive load).

[0073] In one or more exemplary electronic devices, machine learning circuitry includes a neural network module configured to operate according to a neural network.

[0074] In one or more exemplary 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.

[0075] In one or more exemplary hearing systems, electronic devices and / or hearing devices, the machine learning circuitry includes a regressor module configured to operate according to a regression model.

[0076] 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 recognize) 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., recognize) a health parameter over time based on sensor data and / or audio input data.

[0077] 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, 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, for example, utilize the results of a signal processing method (e.g., a filter), statistics of a signal (e.g., a mean, maximum, median, and / or quantile), and / or an unsupervised learning method (e.g., a dimensionality reduction method, clustering, and / or an autoencoder) to first extract one or more features from the input sensor data. Then, the one or more features can be input into a regression and / or classification model trained using machine learning techniques.

[0078] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the system is configured to train the machine learning model to provide an updated machine learning model, and transmit the updated machine learning model to the electronic device and / or hearing device. That is, the server device is configured to train the machine learning model to provide an updated machine learning model, and transmit the updated machine learning model to the electronic device and / or hearing device.

[0079] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the server device is configured to train and / or update the machine learning model based on one or more of the sensor data and the health parameters. In one or more embodiments, the processor can be configured to train and / or update the machine learning model based on the results of the health characterization (e.g., by comparing the health parameters to known health parameters). The machine learning model on which the machine learning circuit operates can be trained and / or updated (e.g., retrained or fine-tuned). The training of the machine learning model can be a supervised learning setting, in which sensor data in the input data can be characterized. The machine learning model or changes made to the machine learning model can be based on new data, such as new sensor data and / or new prediction data.

[0080] The health representation disclosed herein can be considered as a representation indicating all or part of the health parameters and / or cognitive state of the user. That is, the health representation can be considered as a cognitive state representation. The health representation can be considered as and / or includes an assessment of the user's cognitive state. That is, the health representation can be considered as and / or includes an assessment of the user's cognitive ability. In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the health representation includes a score, such as a cognitive score, which indicates (for example, when wearing a hearing device) the performance of the user's cognitive state. The health representation can indicate whether the user's cognitive state indicates cognitive decline. Therefore, the health representation can provide feedback about 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 can indicate cognitive decline. For example, the processor of the system, the electronic device, and / or the processor of the hearing device can be configured to determine whether the score meets the standard (for example, the first standard). When the score is higher than or equal to a threshold (for example, a first threshold), it can be determined that the score meets the standard (for example, the first standard). The health representation can 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, more severe cognitive decline, or severe cognitive decline. Mild cognitive decline, moderate cognitive decline, more severe cognitive decline, and / or severe cognitive decline may indicate and / or represent the extent of cognitive decline, for example, the progression from mild cognitive impairment to dementia, wherein mild cognitive decline may be considered mild cognitive impairment and severe cognitive decline may be considered the progression of dementia. Cognitive decline is not necessarily associated with a mental disorder or condition, but may be caused by one or more factors, such as fatigue, aging, overstimulation, lifestyle factors, medications, and stress. Cognitive decline may be temporary and may be caused by one or more of the above factors, for example. For example, it may be determined or detected that the user's cognitive ability deteriorates over a period of time, but after a period of time, the user's cognitive ability may return to the state before the deterioration was detected. The determination of cognitive decline may be different from the determination of cognitive load or the determination of a mental disorder.

[0081] In one or more exemplary 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 disclosed herein. The health representation may include one or more of a speech biomarker representation, a physiological biomarker representation, and a biodynamic biomarker representation.

[0082] In one or more exemplary hearing systems, electronic devices and / or hearing devices, the health representation indicates an assessment of a user's cognitive state.

[0083] In one or more exemplary 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.

[0084] In one or more exemplary hearing systems and / or electronic devices, outputting the health representation includes displaying a user interface representing the health representation via an interface of the electronic device. That is, outputting the health representation includes displaying a user interface representing the health representation via an interface of an accessory device disclosed herein.

[0085] Outputting the health representation may include displaying a user interface indicating the health representation. In one or more exemplary 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. via an interface of the electronic device.

[0086] Outputting the health representation may include displaying a user interface indicative of the health representation.

[0087] The user interface may include one or more (e.g., 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 small application that a user can use. Outputting a health representation may include outputting a health representation including 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 one or more of the user interface objects including the foregoing. For example, outputting a health representation may include outputting a health representation including a report of a user's cognitive state. For example, outputting a health representation may include outputting a health representation including a score (e.g., an assessment score of a cognitive state when a user wears a hearing device).

[0088] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, based on a health parameter satisfying a first criterion, a processor of the system, electronic device, and / or a 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 the user's cognitive state. The first suggestion may be considered as a first assessment. The first suggestion may indicate a suggestion to avoid and / or mitigate cognitive decline. The first suggestion may be considered as and / or include a suggested action that the user of the hearing device should take based on the health parameter satisfying 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 your hearing device to reduce your cognitive decline”, “Please take your hearing device to a hearing specialist to adjust and / or update the configuration of your hearing device to reduce your cognitive decline”, “Please increase your brain activity and / or motor activity to reduce your cognitive decline”, “Please get checked 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 the amount you smoke”, “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, seek treatment”, “Please avoid excessive drinking”, and / or “Please try to maintain frequent social contacts”.

[0089] In one or more exemplary 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 the first suggestion via an interface (e.g., an interface of the electronic device and / or an interface of the hearing device). That is, 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.

[0090] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the first suggestion is included in the health representation. That is, the processor of the system, 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 processor of the system, the electronic device, and / or the processor of the hearing device is configured to output the health representation including the first suggestion.

[0091] In one or more exemplary hearing systems and / or electronic devices, based on the first criterion being met, the system is configured to perform a cognitive test protocol via an interface of the electronic device. That is, based on the first criterion being met, the system is configured to perform a cognitive test protocol via an interface of an accessory device. In one or more exemplary hearing systems and / or electronic devices, based on the first criterion being met, the system is configured to perform a cognitive test protocol via an interface of a hearing device.

[0092] For example, the system may be configured to output and / or display a user interface representing a cognitive test scheme, for example, via an interface of an electronic device (e.g., a display) and / or via an interface of a hearing device (e.g., via a receiver of a hearing device). The cognitive test scheme may be configured to be executed by a user of a hearing device on an electronic device. Executing the cognitive test scheme may include, for example, outputting one or more of audio data, visual data, text data (e.g., a questionnaire) via an interface of an electronic device (e.g., a display) and / or via an interface of a hearing device (e.g., via a receiver of a hearing device), and receiving one or more inputs of a user via an interface of an electronic device and / or an interface of a hearing device. Executing the cognitive test scheme may be used to obtain more information about the cognitive state of the hearing device user, for example, when it is determined that the first criterion is met. The health representation may be based on health parameters and user input from the cognitive test scheme. The cognitive test scheme may, for example, include having the hearing device user 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 may, for example, test 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.

[0093] The cognitive test protocol may, for example, include asking the hearing device user to perform one or more actions and / or activities, for example, testing the user's physiological biomarkers and / or biodynamic biomarkers while performing the one or more actions and / or activities. The cognitive test protocol may, for example, test one or more of blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters. The cognitive test protocol may, for example, test one or more of motion parameters, trembling parameters, shaking parameters, and tic parameters.

[0094] In one or more exemplary 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 the cognitive testing protocol.

[0095] In one or more exemplary 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 signature in the microphone input data, such as a sound signature.

[0096] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the first criterion is based on a first voice biomarker. That is, the first criterion includes the first voice biomarker criterion. That is, determining whether the health parameter meets the first criterion may include determining whether the health parameter meets the first voice biomarker criterion.

[0097] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, determining the first speech biomarker comprises 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 exemplary hearing systems, the system 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, for example using an electronic device and / or a hearing device.

[0098] In one or more exemplary 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.

[0099] In one or more exemplary 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.

[0100] In one or more exemplary 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.

[0101] Language parameters can be considered as parameters indicating language biomarkers. That is, language parameters can include specific semantically related words and / or sentences, such as incomplete words and / or sentences spoken by the user, which can indicate a decline in cognitive ability. For example, language parameters can, for example, indicate that the user is experiencing vocabulary and / or grammatical simplification, and / or loss of semantic ability. Language parameters can be determined based on a text transcription of microphone input data. The text transcription can be obtained through an automatic speech recognition (speech to text) algorithm or service. Language parameters can include embedded features generated by a deep neural network (such as a BERT transformer network or other sequence to sequence autoencoder).

[0102] Acoustic parameters may be considered as parameters indicative of acoustic biomarkers. That is, acoustic parameters may include specific acoustic sounds and / or acoustic features, such as acoustic sounds emitted by a user and / or acoustic features in a user's voice, which may indicate cognitive decline. Acoustic parameters may include pitch, energy level, spectral parameters (Mel-frequency cepstral coefficients, MFCC; e.g., logMelSpec), spectral statistics (slope, roll-off point), speech spectral envelope features (e.g., formants, harmonics, ratio of harmonics to formants), and / or one or more of speech quality metrics such as harmonic-to-noise ratio (HNR), jitter, and / or shimmer.

[0103] The speech fluency parameter may be considered as a parameter indicating a speech fluency biomarker. That is, the speech fluency parameter may contain information about the speech fluency of the user when speaking. For example, when the speech fluency of the user decreases and / or indicates that the speech fluency is low, the speech fluency parameter may indicate cognitive decline. A hearing device user may, for example, increasingly frequently search for words when speaking, which may indicate that his speech fluency is decreasing. The speech fluency parameter may, for example, indicate that the user stutters when speaking and / or that the stuttering is exacerbated when speaking. The speech fluency parameter may, for example, indicate that the user has circumlocutions and / or frequently uses filler sounds such as "uh", "um", semantic errors, unclear terms, corrections, repetitions and / or new words.

[0104] 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 user speaks with decreased coherence and / or indicates low coherence, the coherence parameter may indicate cognitive decline. The hearing device user may, for example, increasingly state untrustworthy and / or irrelevant details.

[0105] As will be appreciated, the use of voice biomarkers is a simple and non-invasive method for characterizing and / or monitoring health parameters.

[0106] The first criterion may include a first speech fluency criterion. That is, 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.

[0107] The mumbling parameter may be considered a parameter indicative of a mumbling biomarker. That is, the mumbling parameter may include information about the mumbling of the user while speaking. For example, when the user's mumbling increases and / or indicates a high level of mumbling, the mumbling parameter may indicate cognitive decline. Determining the mumbling parameter may include determining that the user is speaking softly and slurring. That is, determining the mumbling parameter may include determining that the user is slurring and / or has unclear pronunciation, for example, speech and / or wording is difficult to understand.

[0108] The first criterion may include a first grunt criterion. That is, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first grunt criterion. For example, the first threshold may include a first grunt threshold. When the grunt parameter is above the first grunt threshold, the first criterion is met and the user may have cognitive decline.

[0109] The pitch parameter may be considered as a parameter indicating a pitch biomarker. That is, 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 voice pitch increases and / or decreases, the pitch parameter may indicate cognitive decline.

[0110] The first criterion may include a first pitch criterion. That is, determining whether the health parameter meets the first criterion may include determining whether the health parameter meets 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.

[0111] The speech rhythm parameter may be considered as a parameter indicating a speech rhythm biomarker. That is, 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 is hesitant when speaking.

[0112] The first criterion may include a first speech rhythm criterion. That is, 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 higher than the first speech rhythm threshold, the first criterion is met and the user may have cognitive decline.

[0113] Pitch features and speech rhythm features can be considered prosodic features.

[0114] In one or more exemplary hearing systems, electronic devices and / or hearing devices, the sensor data (eg external sensor data) comprises physiological data. In one or more exemplary hearing systems, electronic devices and / or hearing devices, the health parameter is based on the physiological data.

[0115] In one or more exemplary 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 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 that is a capacitance and / or conductivity sensor, for example, for measuring and / or determining stress levels.

[0116] In one or more exemplary 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 a physiological biomarker (e.g., a first physiological biomarker) may include extracting one or more features (e.g., physiological features) from the sensor data. Determining a physiological biomarker (e.g., a first physiological biomarker) may include extracting one or more physiological features from the physiological data. A physiological biomarker may be considered a biomarker of one or more parameters indicating a physiological condition of a user of the hearing device. A physiological biomarker may include and / or indicate a feature (e.g., a 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 are supposed to 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.

[0117] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the first criterion is based on a first physiological biomarker. That is, the first criterion includes the first physiological biomarker criterion. That is, determining whether the health parameter meets the first criterion may include determining whether the health parameter meets the first physiological biomarker criterion.

[0118] In one or more exemplary hearing systems, electronic devices and / or hearing devices, determining the first physiological biomarker comprises 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 exemplary hearing systems, the system is configured to 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, for example using an electronic device and / or a hearing device.

[0119] In one or more exemplary 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.

[0120] In one or more exemplary 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.

[0121] In one or more exemplary 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.

[0122] The blood pressure parameter may be considered as a parameter indicating a blood pressure biomarker. That is, the blood pressure parameter may include information about the blood pressure of the user while wearing the hearing device. For example, when the blood pressure of the user 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.

[0123] The first criterion may include a first blood pressure criterion. That is, 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 be at increased risk of cognitive decline and / or indicate cognitive decline.

[0124] The blood flow parameters may be considered as parameters indicative of blood flow biomarkers. That is, the blood flow parameters may include information about the blood flow of the user while wearing 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.

[0125] The first criterion may include a first blood flow criterion. That is, 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 be at risk of cognitive decline and / or an increased risk of cognitive decline in the user.

[0126] The heart rate parameter may be considered as a parameter indicative of a heart rate biomarker. That is, 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, such as increases and / or decreases, the heart rate parameter may indicate cognitive decline. The heart rate parameter may indicate heart rate variability.

[0127] The first criterion may include a first heart rate criterion. That is, 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 be at risk of cognitive decline and / or an increased risk of cognitive decline in the user.

[0128] The breathing parameters may be considered as parameters indicating a breathing biomarker. That is, the breathing parameters may include information about the breathing condition of the user when wearing the hearing device. For example, when the user's breathing rate changes abnormally, such as increases and / or decreases, the breathing parameters may indicate cognitive decline and / or indicate an increased risk of cognitive decline.

[0129] The first criterion may include a first breathing criterion. That is, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first breathing criterion. For example, the first threshold may include a first respiratory rate threshold and / or a second respiratory rate threshold. When the respiratory parameter is above the first respiratory rate threshold and / or below the second respiratory rate threshold, the first criterion is met and the user may be at risk of cognitive decline and / or an increased risk of cognitive decline in the user.

[0130] The temperature parameter may be considered as a parameter indicative of a temperature biomarker. That is, the temperature parameter may include information about the temperature of the user when the user wears the hearing device. For example, when the temperature of the user changes abnormally, such as increases and / or decreases, the temperature parameter may indicate cognitive decline and / or an increased risk of cognitive decline for the user.

[0131] The first criterion may include a first temperature criterion. That is, 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 be at risk of cognitive decline and / or an increased risk of cognitive decline in the user.

[0132] The oxygen parameter may be considered a parameter indicative of an oxygen biomarker. That is, the oxygen parameter may include information about the user's oxygen when the user wears the hearing device. For example, when the user's oxygen rate changes abnormally, such as increases and / or decreases, the oxygen parameter may indicate cognitive decline and / or an increased risk of cognitive decline for the user.

[0133] The first criterion may include a first oxygen criterion. That is, 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 be at risk of cognitive decline and / or an increased risk of cognitive decline for the user.

[0134] The brain activity parameter may be considered as a parameter indicating a brain activity biomarker. That is, the brain activity parameter 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 parameter may indicate cognitive decline and / or indicate an increased risk of cognitive decline.

[0135] The first criterion may include a first brain activity criterion. That is, 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 be at risk of cognitive decline and / or an increased risk of cognitive decline in the user.

[0136] In one or more exemplary hearing systems, electronic devices and / or hearing devices, the sensor data (eg external sensor data) comprises biokinetic data. In one or more exemplary hearing systems, electronic devices and / or hearing devices, the health parameter is based on the biokinetic data.

[0137] In one or more exemplary hearing systems and / or electronic devices, the one or more sensors include one or more biokinetic sensors for providing biokinetic data. The biokinetic sensors may, for example, include one or more of a motion sensor, an inertial measurement unit (IMU) sensor, an accelerometer, and / or a gyroscope. The biokinetic sensors may be configured to measure one or more movements of a user of the hearing device. For example, the biokinetic sensors may be configured to measure one or more head movements of a user of the hearing device.

[0138] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, determining a health parameter includes determining a first biodynamic biomarker based on biodynamic data. Determining the health parameter may, for example, include determining a second biodynamic biomarker, a third biodynamic biomarker, a fourth biodynamic biomarker, a fifth biodynamic biomarker, and / or a sixth biodynamic biomarker. Determining the biodynamic biomarker (e.g., the first biodynamic biomarker) may include extracting one or more features (e.g., biodynamic features) from the sensor data. Determining the biodynamic biomarker (e.g., the first biodynamic biomarker) may include extracting one or more biodynamic features from the biodynamic data. The biodynamic biomarker may be considered a sign indicating one or more actions of the hearing device user. The biodynamic biomarker may include and / or indicate a feature in the biodynamic data, such as a biodynamic feature.

[0139] In one or more exemplary hearing systems, electronic devices, and / or hearing devices, the first criterion is based on a first biodynamic biomarker. That is, the first criterion includes the first biodynamic biomarker criterion. That is, determining whether the health parameter satisfies the first criterion may include determining whether the health parameter satisfies the first biodynamic biomarker criterion.

[0140] In one or more exemplary hearing systems, electronic devices and / or hearing devices, determining the first biodynamic biomarker comprises determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter.

[0141] In one or more exemplary hearing systems, the system is configured to determine one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter, for example using an electronic device and / or a hearing device.

[0142] In one or more exemplary 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.

[0143] In one or more exemplary hearing devices, the processor of the hearing device is configured to determine one or more of a movement parameter, a tremor parameter, a jitter parameter, and a twitch parameter.

[0144] In one or more exemplary hearing systems, electronic devices and / or hearing devices, the first biodynamic biomarker is based on one or more of a motion parameter, a tremor parameter, a jitter parameter and a twitch parameter.

[0145] The motion parameters may be considered as parameters indicative of motion biomarkers. That is, 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, such as increasing and / or decreasing, the motion parameters may indicate cognitive decline.

[0146] The tremor parameter may be considered as a parameter indicative of a tremor biomarker. That is, 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, such as increases and / or decreases, the tremor parameter may indicate cognitive decline.

[0147] The jitter parameter may be considered as a parameter indicating a jitter biomarker. That is, the jitter parameter may include information about the jitter of the user when the user wears the hearing device. For example, when the jitter of the user changes abnormally, such as increases, the jitter parameter may indicate cognitive decline.

[0148] The twitch parameter may be considered as a parameter indicating a twitch biomarker. That is, the twitch parameter may include information about one or more twitches of the user while the user is wearing the hearing device. For example, when the user's twitches change abnormally, such as increase, the twitch parameter may indicate cognitive decline.

[0149] It should be understood that descriptions about features of a hearing device and / or an electronic device also apply 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.

[0150] Figure 1 An exemplary hearing system is schematically shown, for example a hearing system 2 according to the present invention. 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.

[0151] The electronic device 10 includes a memory 10A, an interface 10B (eg, one or more interfaces), and a processor 10C.

[0152] Optionally, the electronic device is a server device 20. That is, the hearing system 2 may include a server device 20. The server device 20 includes a memory 20A, an interface 20B (eg one or more interfaces) and a processor 20C (eg one or more processors).

[0153] Optionally, the system 2 includes a machine learning circuit configured to operate according to a machine learning model. In one or more exemplary hearing systems, determining a health parameter includes, for example, using the electronic device 10, 20 and / or the hearing device 30, using a machine learning model to determine the health parameter based on external sensor data. That is, 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. That is, the system 2 can be configured to, for example, use the electronic device 10, 20 and / or the hearing device 30 to determine a health parameter based on external sensor data using a machine learning model.

[0154] 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 exemplary electronic devices and / or systems, the models described herein may be stored on a non-transitory storage medium (e.g., stored on a memory 10A of the electronic device 10, a memory 20A of the server device 20, and / or a memory 30A of the hearing device 30).

[0155] Optionally, the one or more sensors 10D and / or the one or more sensors 30D comprise a microphone for providing microphone input data. Optionally, the external sensor data comprises microphone input data.

[0156] Optionally, the health parameter is based on microphone input data.

[0157] Optionally, the one or more sensors 30D and / or the one or more sensors 30D include one or more of a microphone, an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor.

[0158] Optionally, the interface 10B of the electronic device 10 and / or the interface 30B of the hearing device 30 includes one or more of a Bluetooth interface, a low-power Bluetooth 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.

[0159] 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). That is, the system 2 is configured to acquire external sensor data at the hearing device 30 and / or at the electronic device as the accessory device 10 and / or at the electronic device as the server device 20. That is, the external sensor data may be acquired, received and / or retrieved from the hearing device 30 by the electronic device as the accessory device 10 and / or the electronic device as the server device 20. The external sensor data may be transmitted and / or sent to the electronic device as the accessory device 10 and / or the electronic device as the server device 20 by the hearing device 30. The system 2 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, for example, using a processor 30C of the hearing device 30 and / or a processor 10C of the electronic device as the accessory device 10 and / or an electronic device as the server device 20. That is, the system 2 is configured to determine, based on the external sensor data, a health parameter indicating a cognitive state of the user 1, 1B of the hearing device 30, for example, on a processor 30C of the hearing device 30 and / or on a processor 10C of an electronic device as an accessory device 10 and / or on a processor 20C of a server device 20. The system 2 is configured to determine, for example, using the processor 30C of the hearing device 30 and / or the processor 10C of an electronic device as an accessory device 10 and / or on an electronic device as a server device 20, whether the health parameter meets a first criterion indicating cognitive decline. That is, the system 2 is configured to determine, for example, on a processor 30C of the hearing device 30 and / or on a processor 10C of an electronic device as an accessory device 10 and / or on an electronic device as a server device 20, whether the health parameter meets a first criterion indicating cognitive decline. Optionally, the system 2 is configured to output a health representation related to the cognitive state via an interface 30B of the hearing device 30 and / or an interface 10B of the electronic device as the accessory device 10 and / or an interface 20B of the electronic device as the server device 20, for example, using a processor 30C of the hearing device 30 and / or a processor 10C of the electronic device as the accessory device 10 and / or an electronic device as the server device 20, based on the health parameter satisfying the first criterion.

[0160] The present invention discloses a hearing device 30. The hearing device 30 can be regarded as a hearing device with health representation and / or monitoring functions. 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 (see reference numerals 24, 34) internal sensor data from one or more sensors 10D of the electronic device 10 via a network 40 (e.g., a global network (such as the Internet and / or a local area 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 (see reference numerals 22, 36) a health representation related to the cognitive state via the interface 30B according to the health parameter meeting the first criterion. Optionally, the user 1, 1B may provide input 38 (e.g., user input) to the hearing device 30, e.g., via the interface 30B. The determination of one or more of the sensor data, health parameters, and health indications may be based on the input 38 from the user 1, 1B. The user 1, 1B may, for example, provide one or more inputs in response to a cognitive test protocol.

[0161] The present invention discloses an electronic device as an accessory device 10. The electronic device 10 includes a memory 10A, an interface 10B and a processor 10C. The processor 10C is configured to obtain (see reference numerals 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, e.g., a global network (such as the Internet and / or a local area 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 a decline in cognitive ability. Optionally, the processor 10C is configured to output (see reference numerals 6, 34) a health representation related to the cognitive state via the interface 10B based on the health parameter meeting the first criterion.

[0162] The present invention discloses an electronic device as a server device 20. The electronic device 20 includes a memory 20A, an interface 20B and a processor 20C. The processor 20C is configured to obtain (see reference numeral 16) external sensor data from a hearing device (e.g., a hearing device 30) via the interface 20B (e.g., via a network 40, such as a global network (such as the Internet and / or a local area 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 a decline in cognitive ability. Optionally, the processor 20C is configured to output (see reference numeral 18) a health representation related to the cognitive state via the interface 20B (such as via the network 40, to the electronic device 10) based on the health parameter meeting the first criterion.

[0163] 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. That is, 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.

[0164] Optionally, the system 2, such as the server device 20, is configured to train the machine learning model to provide an updated machine learning model, and transmit the updated machine learning model (see reference numerals 14, 18, 24) to the electronic device 10 and / or the hearing device 30. That is, the server device 20 is configured to train the machine learning model to provide an updated machine learning model, and transmit the updated machine learning model (see reference numeral 18) to the electronic device 10 and / or the hearing device 30.

[0165] Optionally, outputting the health representation includes displaying (see reference numeral 6) a user interface representing the health representation via the interface 10B of the electronic device 10. That is, outputting the health representation includes displaying (see reference numeral 6) a user interface representing the health representation to, for example, the user 1, 1A via the interface 10B of the accessory device 10 disclosed herein.

[0166] Optionally, the system 2 is configured to execute the cognitive test protocol via the interface 10B of the electronic device 10 based on the first criterion being met. That is, the system 2 is configured to execute the cognitive test protocol via the interface 10B of the accessory device 10 based on the first criterion being met. In one or more exemplary hearing systems and / or electronic devices, the system 2 is configured to execute the cognitive test protocol via the interface 30B of the hearing device 30 based on the first criterion being met.

[0167] 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.

[0168] Optionally, the system 2 is configured to determine a health parameter, including determining a first speech biomarker based on microphone input data, for example using the electronic device 10 , 20 and / or the hearing device 30 .

[0169] 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 .

[0170] Optionally, the one or more sensors 10D, 30D include one or more physiological sensors for providing physiological data.

[0171] Optionally, the sensor data (eg external sensor data) comprises physiological data, eg physiological data related to the user 1 , 1B. In one or more exemplary hearing systems, electronic devices and / or hearing devices, the health parameter is based on the physiological data.

[0172] 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 .

[0173] 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 .

[0174] 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 .

[0175] Optionally, the one or more sensors 10D, 30D include one or more biokinetic sensors for providing biokinetic data.

[0176] Optionally, the sensor data (eg external sensor data) comprises biokinetic data, eg biokinetic data relating to the user 1 , 1B.

[0177] Optionally, the system 2 is configured to determine a first biokinetic biomarker based on the biokinetic data, for example using the electronic device 10 , 20 and / or the hearing device 30 .

[0178] Optionally, the system 2 is configured to determine one or more of a movement parameter, a tremor parameter, a jitter parameter and a twitch parameter, for example using the electronic device 10 , 20 and / or the hearing device 30 .

[0179] The hearing device 30 may be configured to perform Figure 2 Any method disclosed in.

[0180] Processor 30C is optionally configured to execute Figure 2 The operations disclosed in the hearing device 30 (e.g., any one or more of S104A, S104A_1, S104B, S104B_1, S104C, S104C_1, S104D, S107) may be implemented 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.

[0181] Additionally, 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, these functions may also be performed by dedicated hardware or firmware, or some combination of hardware, firmware and / or software.

[0182] 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 configuration, 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.

[0183] Memory 30A can be configured to store information such as sensor data, sound data, audio data, image data, health parameters, health indications, biomarkers, recommendations and / or machine learning models disclosed herein in a portion of the memory.

[0184] The electronic device 10 may be configured to perform Figure 3 Any method disclosed in.

[0185] The processor 10C may optionally be configured to execute Figure 2 The operation of the electronic device 10 may be embodied in the form of an executable logic routine (e.g., a line of code, a software program, etc.) stored on a non-transitory computer-readable medium (e.g., memory 10A) and executed by the processor 10C.

[0186] Additionally, the operation of the electronic device 10 may be viewed as a method that the electronic device 10 is configured to perform. Furthermore, although the functions and operations described may be implemented by software, these functions may also be performed by dedicated hardware or firmware, or some combination of hardware, firmware and / or software.

[0187] 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 configuration, 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. There may also be a control line and an address bus ( Figure 1 Memory 10A is considered a non-transitory computer-readable medium.

[0188] Memory 10A may be configured to store information such as sensor data, sound data, audio data, image data, health parameters, health indications, biomarkers, recommendations, and / or machine learning models disclosed herein in a portion of the memory.

[0189] The server device 20, such as the processor 20C, may be configured to perform any operation performed by the electronic device 10 (e.g., the accessory device 10, such as the processor 10C) as described herein. That is, the description related to the processor 10C may be applicable 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 may be considered as the same device and / or two independent devices.

[0190] System 2 can be configured to execute Figure 4A-4B Any method disclosed in.

[0191] System 2 is optionally configured to perform Figure 4A-4B The operations disclosed in the system 2 may include 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.) stored on a non-transitory computer-readable medium (e.g., memory 10A, 30A) and executed by the processor 10C, 30C.

[0192] Additionally, 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 by software, these functions may also be performed by dedicated hardware or firmware, or some combination of hardware, firmware, and / or software.

[0193] Figure 2 A flow chart showing an exemplary method, such as the method 100 . The present invention discloses a method 100 of operating a hearing device. The method 100 may be performed by a hearing device, such as the hearing device 30 , disclosed herein.

[0194] The method 100 comprises acquiring sensor data from one or more sensors of a hearing device ( S102 ).

[0195] 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 in accordance with the health parameter satisfying the first criterion (S108).

[0196] Optionally, according to the health parameter not satisfying the first criterion, the method 100 includes prohibiting the step S108 ( S107 ) of outputting the health representation related to the cognitive state.

[0197] In one or more exemplary methods, the one or more sensors include a microphone for providing microphone input data. In one or more exemplary methods, the health parameter is based on the microphone input data.

[0198] In one or more exemplary methods, the step of determining a health parameter (S104) includes determining a first voice biomarker based on the microphone input data (S104A). In one or more exemplary methods, the first criterion is based on the first voice biomarker.

[0199] In one or more exemplary methods, determining a first speech biomarker (S104A) 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 (S104A_1). In one or more exemplary methods, 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.

[0200] In one or more exemplary methods, the one or more sensors include one or more physiological sensors for providing physiological data. In one or more exemplary methods, the health parameter is based on the physiological data.

[0201] In one or more exemplary methods, determining a health parameter (S104) includes determining a first physiological biomarker based on the physiological data (S104B). In one or more exemplary methods, the first criterion is based on the first physiological biomarker.

[0202] In one or more exemplary methods, determining a first physiological biomarker (S104B) includes 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 (S104B_1). In one or more exemplary 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.

[0203] In one or more exemplary methods, the one or more sensors include one or more biokinetic sensors for providing biokinetic data. In one or more exemplary methods, the health parameter is based on the biokinetic data.

[0204] In one or more exemplary methods, determining a health parameter (S104) includes determining a first biokinetic biomarker based on the biokinetic data (S104C). In one or more exemplary methods, the first criterion is based on the first biokinetic biomarker.

[0205] In one or more exemplary methods, determining a first biokinetic biomarker (S104) includes determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter (S104C_1). In one or more exemplary methods, the first biokinetic biomarker is based on one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter.

[0206] In one or more exemplary 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.

[0207] In one or more exemplary methods, the processor includes a machine learning configured to operate according to the machine learning model. In one or more exemplary methods, determining the health parameter (S104) includes determining the health parameter using the machine learning model based on the sensor data (S104D).

[0208] Figure 3 A flowchart of an exemplary method (eg, method 200) is shown. The present invention discloses a method 200 for operating an electronic device. The method 200 may be performed by an electronic device (eg, electronic device 10) disclosed herein.

[0209] The present invention discloses a method 200 for operating an electronic device. The method 200 includes acquiring external sensor data from a hearing device (S202). The method 200 includes determining a health parameter indicating a cognitive state of a user of the hearing device based on the external sensor data (S206). The method 200 includes determining whether the health parameter satisfies a first criterion indicating cognitive decline (S208). The method 200 includes outputting a health representation related to the cognitive state in accordance with the health parameter satisfying the first criterion (S210).

[0210] Optionally, according to the health parameter not satisfying the first criterion, the method 200 includes prohibiting the step S210 ( S209 ) of outputting the health representation related to the cognitive state.

[0211] In one or more exemplary methods, outputting a health (S210) representation includes displaying a user interface (S210A) representing the health representation.

[0212] In one or more exemplary methods, based on the first criterion being met, the method includes executing a cognitive testing regimen ( S212 ).

[0213] In one or more exemplary methods, the external sensor data includes microphone input data. In one or more exemplary methods, the health parameter is based on the microphone input data.

[0214] In one or more exemplary methods, determining the health parameter (S206) includes determining a first voice biomarker based on the microphone input data (S206A). In one or more exemplary methods, the first criterion is based on the first voice biomarker.

[0215] In one or more exemplary methods, determining a first speech biomarker (S206A) 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 (S206A_1). In one or more exemplary methods, 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.

[0216] In one or more exemplary methods, the external sensor data includes physiological data. In one or more exemplary methods, the health parameter is based on the physiological data.

[0217] In one or more exemplary methods, determining a health parameter (S206) includes determining a first physiological biomarker based on the physiological data (206B). In one or more exemplary methods, the first criterion is based on the first physiological biomarker.

[0218] In one or more exemplary methods, determining the first physiological biomarker (S206B) includes 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 (determining S206B_1). In one or more exemplary 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.

[0219] In one or more exemplary methods, the external sensor data includes biokinetic data. In one or more exemplary methods, the health parameter is based on the biokinetic data.

[0220] In one or more exemplary methods, determining a health parameter (S206) includes determining a first biokinetic biomarker based on the biokinetic data (S206C). In one or more exemplary methods, the first criterion is based on the first biokinetic biomarker.

[0221] In one or more exemplary methods, determining a first biokinetic biomarker (S206C) includes determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter (S206C_1). In one or more exemplary methods, the first biokinetic biomarker is based on one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter.

[0222] In one or more exemplary methods, the electronic device includes one or more sensors, and the method includes acquiring internal sensor data from the one or more sensors (S204). In one or more exemplary methods, the health parameter is based on the internal sensor data.

[0223] In one or more exemplary methods, the processor includes a machine learning circuit configured to operate according to the machine learning model. In one or more exemplary methods, determining the health parameter (S206) includes determining the health parameter using the machine learning model based on the sensor data (S206D).

[0224] In one or more exemplary methods, the interface includes one or more of a Bluetooth interface, a Bluetooth low energy interface, and a magnetic induction interface.

[0225] Figure 4A-4B A flow chart of an exemplary method, such as method 300 , is shown.

[0226] The present invention discloses a method 300 for operating a hearing system. The method 300 may be performed by a system disclosed herein (eg, the system 2).

[0227] The method 300 includes acquiring external sensor data from a hearing device (S302). The method 300 includes determining a health parameter indicative of a cognitive state of a user of the hearing device based on the sensor data (S306). The method 300 includes determining whether the health parameter satisfies a first criterion indicative of cognitive decline (S308). The method 300 includes outputting a health representation associated with the cognitive state in accordance with the health parameter satisfying the first criterion (S310).

[0228] Optionally, according to the health parameter not satisfying the first criterion, the method 300 includes prohibiting the step S310 ( S309 ) of outputting the health representation related to the cognitive state.

[0229] In one or more exemplary methods, outputting a health representation ( S310 ) includes displaying a user interface representing the health representation ( S310A).

[0230] In one or more exemplary methods, based on the first criterion being met, the method includes executing a cognitive testing regimen ( S312 ).

[0231] In one or more exemplary methods, the external sensor data includes microphone input data. In one or more exemplary methods, the health parameter is based on the microphone input data.

[0232] In one or more exemplary methods, determining the health parameter (S306) includes determining a first voice biomarker based on the microphone input data (S306A). In one or more exemplary methods, the first criterion is based on the first voice biomarker.

[0233] In one or more exemplary methods, determining a first speech biomarker (S306A) 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 (S306A_1). In one or more exemplary methods, 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.

[0234] In one or more exemplary methods, the external sensor data includes physiological data. In one or more exemplary methods, the health parameter is based on the physiological data.

[0235] In one or more exemplary methods, determining a health parameter (S306) includes determining a first physiological biomarker based on the physiological data (S306B). In one or more exemplary methods, the first criterion is based on the first physiological biomarker.

[0236] In one or more exemplary methods, determining the first physiological biomarker (S306B) includes 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 (S306B_1). In one or more exemplary 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.

[0237] In one or more exemplary methods, the external sensor data includes biokinetic data. In one or more exemplary methods, the health parameter is based on the biokinetic data.

[0238] In one or more exemplary methods, determining a health parameter (S306) includes determining a first biokinetic biomarker based on the biokinetic data (S306C). In one or more exemplary methods, the first criterion is based on the first biokinetic biomarker.

[0239] In one or more exemplary methods, determining a first biokinetic biomarker (S306C) includes determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter (S306C_1). In one or more exemplary methods, the first biokinetic biomarker is based on one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter.

[0240] In one or more exemplary methods, the electronic device includes one or more sensors, and the method includes acquiring internal sensor data from the one or more sensors (S304). In one or more exemplary methods, the health parameter is based on the internal sensor data.

[0241] In one or more exemplary methods, the electronic device includes a machine learning circuit configured to operate according to the machine learning model. In one or more exemplary methods, determining the health parameter (S306) includes determining the health parameter using the machine learning model based on the external sensor data (S306D).

[0242] In one or more exemplary 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.

[0243] In one or more exemplary methods, the electronic device is a server device.

[0244] In one or more exemplary methods, the method includes training a machine learning model (S314), providing an updated machine learning model (S316), and transmitting the updated machine learning model to an electronic device (S318).

[0245] In one or more exemplary methods, the electronic device is an accessory device.

[0246] Embodiments of electronic devices, systems and methods according to the present invention are listed in the following items: A1. A hearing device, comprising: Memory; interface; Processor; and one or more sensors; Wherein, the processor is configured as follows: acquiring sensor data from the one or more sensors; determining a health parameter indicative of a cognitive state of a user of the hearing device based on the sensor data; determining whether the health parameter meets a first criterion indicative of cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output via the interface.

[0247] 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.

[0248] A3. The hearing device of item A2, wherein determining a health parameter comprises determining a first speech biomarker based on the microphone input data, and wherein the first criterion is based on the first speech biomarker.

[0249] A4. A hearing device according to item A3, 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.

[0250] A5. The hearing device according to any of the preceding clauses, wherein the one or more sensors comprise one or more physiological sensors for providing physiological data, and wherein the health parameter is based on the physiological data.

[0251] A6. The hearing device according to 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.

[0252] A7. A hearing device according to item A6, wherein determining the first physiological biomarker includes determining one or more of 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 blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters.

[0253] A8. The hearing device according to any of the preceding clauses, wherein the one or more sensors comprise one or more biokinetic sensors for providing biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0254] A9. The hearing device of item A8, wherein determining the health parameter comprises determining a first biodynamic biomarker based on the biodynamic data, and wherein the first criterion is based on the first biodynamic biomarker.

[0255] A10. A hearing device according to item A9, wherein determining the first biodynamic biomarker includes determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter; and wherein the first biodynamic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

[0256] A11. The hearing device according to any of the preceding clauses, wherein the one or more sensors comprise one or more of an optical sensor, a magnetic sensor, a current sensor, a motion sensor and a capacitive sensor.

[0257] 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 using the machine learning model based on the sensor data.

[0258] A13. A method of operating a hearing device, the method comprising: acquiring sensor data from one or more sensors of the hearing device; determining a health parameter indicative of a cognitive state of a user of the hearing device based on the sensor data; determining whether the health parameter meets first criteria indicative of cognitive decline; and Outputting a health representation related to a cognitive state according to the health parameter satisfying the first criterion.

[0259] 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.

[0260] A15. The method of operating a hearing device according to item A14, wherein determining the health parameter (S104) comprises: A first voice biomarker is determined based on the microphone input data (S104A), and wherein the first criterion is based on the first voice biomarker.

[0261] A16. The method of operating a hearing device according to item A15, wherein determining the first speech biomarker (S104A) comprises: Determining one or more of language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters (S104A_1); 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.

[0262] 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.

[0263] A18. The method of operating a hearing device according to item A17, wherein determining the health parameter (S104) comprises: A first physiological biomarker is determined based on the physiological data (S104B), and wherein the first criterion is based on the first physiological biomarker.

[0264] A19. A method for operating a hearing device according to item A18, wherein determining a first physiological biomarker (S104B) includes: determining one or more of blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters (S104B_1); and wherein the first physiological biomarker is based on one or more of blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters.

[0265] 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 biodynamic sensors for providing biodynamic data, and wherein the health parameter is based on the biodynamic data.

[0266] A21. The method of operating a hearing device according to item A20, wherein determining the health parameter (S104) comprises: A first biokinetic biomarker is determined based on the biokinetic data (S104C), and wherein the first criterion is based on the first biokinetic biomarker.

[0267] A22. The method of operating a hearing device according to item A21, wherein determining a first biodynamic biomarker (S104C) comprises: One or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter are determined (S104C_1); and wherein the first biodynamic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

[0268] 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 an optical sensor, a magnetic sensor, a current sensor, a motion sensor, and a capacitive sensor.

[0269] A24. The method of operating a hearing device according to any one of items A13-A23, wherein the processor comprises a machine learning circuit configured to operate according to a machine learning model, wherein determining a health parameter (S104) comprises: A health parameter is determined using the machine learning model based on the sensor data (S104D).

[0270] B1. An electronic device, comprising: Memory; Interfaces; and processor; Wherein, the processor is configured as follows: acquiring external sensor data from the hearing device via the interface; determining, based on the external sensor data, a health parameter indicative of a cognitive state of a user of the hearing device; determining whether the health parameter meets a first criterion indicative of cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output via the interface.

[0271] B2. The electronic device according to item B1, wherein outputting the health representation includes displaying a user interface representing the health representation via the interface.

[0272] B3. An electronic device according to any of items B1-B2, wherein, based on satisfying the first criterion, the electronic device is configured to perform a cognitive testing regimen.

[0273] B4. An electronic device according to any one 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.

[0274] B5. An electronic device according to item B4, wherein determining the health parameter includes determining a first voice biomarker based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0275] B6. An electronic device according to item B5, 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.

[0276] B7. An electronic device according to any one of items B1-B6, wherein the external sensor data includes physiological data, and wherein the health parameter is based on the physiological data.

[0277] 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.

[0278] B9. An electronic device according to item B8, wherein determining the first physiological biomarker includes determining one or more of 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 blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters.

[0279] B10. An electronic device according to any one of items B1-B9, wherein the external sensor data includes biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0280] B11. An electronic device according to item B10, wherein determining the health parameter includes determining a first biodynamic biomarker based on the biodynamic data, and wherein the first criterion is based on the first biodynamic biomarker.

[0281] B12. An electronic device according to item B11, wherein determining the first biodynamic biomarker includes determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter; and wherein the first biodynamic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

[0282] B13. An electronic device according to any one of items B1-B12, wherein the electronic device includes one or more sensors, and wherein the processor is configured to obtain internal sensor data from the one or more sensors, and wherein the health parameter is based on the internal sensor data.

[0283] B14. An electronic device according to any one 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 the external sensor data.

[0284] B15. An electronic device according to any one of items B1-B14, wherein the interface comprises one or more of a Bluetooth interface, a low-power Bluetooth interface, and a magnetic induction interface.

[0285] B16. A method of operating an electronic device, the method comprising: Acquiring external sensor data from hearing devices; determining, based on the external sensor data, a health parameter indicative of a cognitive state of a user of the hearing device; determining whether the health parameter meets first criteria indicative of cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output.

[0286] B17. The method of operating an electronic device according to item B16, wherein outputting the health representation (S110) comprises: A user interface showing the health indicator is displayed ( S110A).

[0287] B18. A method of operating an electronic device according to any one of items B16-B17, wherein, based on satisfying the first criterion, the method comprises: A cognitive test protocol is performed ( S112 ).

[0288] B19. A method of operating an electronic device according to any one 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.

[0289] B20. The method of operating an electronic device according to item B19, wherein determining the health parameter (S106) comprises: A first voice biomarker is determined based on the microphone input data (S106A), and wherein the first criterion is based on the first voice biomarker.

[0290] B21. The method of operating an electronic device according to item B20, wherein determining the first voice biomarker (S106A) comprises: Determining one or more of language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters (S106A_1); 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.

[0291] B22. A method of operating an electronic device according to any one of items B16-B21, wherein the external sensor data includes physiological data, and wherein the health parameter is based on the physiological data.

[0292] B23. The method of operating an electronic device according to item B22, wherein determining the health parameter (S106) comprises: A first physiological biomarker is determined based on the physiological data (S106B), and wherein the first criterion is based on the first physiological biomarker.

[0293] B24. The method of operating an electronic device according to item B23, wherein determining the first physiological biomarker (S106B) comprises: Determine one or more of blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters (S106B_1); and wherein the first physiological biomarker is based on: one or more of blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters and brain activity parameters.

[0294] B25. A method of operating an electronic device according to any one of items B16-B24, wherein the external sensor data includes biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0295] B26. The method of operating an electronic device according to item B25, wherein determining the health parameter (S106) comprises: A first biokinetic biomarker is determined based on the biokinetic data (S106C), and wherein the first criterion is based on the first biokinetic biomarker.

[0296] B27. The method of operating an electronic device according to item B26, wherein determining the first biodynamic biomarker (S106C) comprises: One or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter are determined (S106C_1); and wherein the first biodynamic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

[0297] B28. A method of operating an electronic device according to any one of items B16-B27, wherein the electronic device includes one or more sensors, and the method comprises: Internal sensor data is acquired from the one or more sensors ( S104 ), and wherein the health parameter is based on the internal sensor data.

[0298] B29. The method of operating an electronic device according to any one of items B16-B28, wherein the processor includes a machine learning circuit configured to operate according to a machine learning model, wherein determining the health parameter (S106) includes: A health parameter is determined using the machine learning model based on the sensor data (S106D).

[0299] 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.

[0300] C1. A hearing system, comprising: An electronic device comprising a memory, an interface and a processor; and A hearing device comprising a memory, an interface, a processor, and one or more sensors; Wherein, the system configuration is: acquiring external sensor data from the one or more sensors; determining, based on the external sensor data, a health parameter indicative of a cognitive state of a user of the hearing device; determining whether the health parameter meets a first criterion indicative of cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output.

[0301] C2. The hearing system according to item C1, wherein outputting the health representation comprises displaying a user interface representing the health representation via an interface of the electronic device.

[0302] C3. A hearing system according to any of items C1-C2, wherein, based on satisfying the first criterion, the system is configured to execute a cognitive testing regimen via an interface of the electronic device.

[0303] C4. A hearing system according to any of items C1-C3, wherein the external sensor data includes microphone input data, and wherein the health parameter is based on the microphone input data.

[0304] C5. A hearing system according to item C4, wherein determining the health parameter includes determining a first voice biomarker based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

[0305] 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.

[0306] 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.

[0307] C8. A hearing system according to item C7, 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.

[0308] C9. A hearing system according to item C8, wherein determining the first physiological biomarker includes determining one or more of 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 blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters.

[0309] C10. A hearing system according to any of items C1-C9, wherein the external sensor data includes biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0310] C11. A hearing system according to item C10, wherein determining the health parameter comprises determining a first biodynamic biomarker based on the biodynamic data, and wherein the first criterion is based on the first biodynamic biomarker.

[0311] C12. A hearing system according to item C11, wherein determining a first biodynamic biomarker includes determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter; and wherein the first biodynamic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

[0312] C13. A hearing system according to any one of items C1-C12, wherein the electronic device includes one or more sensors, and wherein the 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.

[0313] C14. A hearing system according to any one 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 using the machine learning model based on the external sensor data.

[0314] 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 a Bluetooth interface, a low-power Bluetooth interface, and a magnetic induction interface.

[0315] C16. A hearing system according to any one of items C1-C15, wherein the electronic device is a server device.

[0316] C17. A hearing system according to item C16, wherein the server device is configured to train the machine learning model, provide an updated machine learning model, and transmit the updated machine learning model to the electronic device and / or the hearing device.

[0317] C18. A hearing system according to any one of items C1-C17, wherein the electronic device is an accessory device.

[0318] C19. A method of operating a hearing system, the method comprising: Acquiring external sensor data from hearing devices; determining, based on the external sensor data, a health parameter indicative of a cognitive state of a user of the hearing device; determining whether the health parameter meets a first criterion indicative of cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output.

[0319] C20. The method of operating a hearing system according to item C19, wherein outputting the health representation (S110) comprises: A user interface showing the health indicator is displayed ( S110A).

[0320] C21. A method of operating a hearing system according to any of items C19-C20, wherein, in accordance with satisfying the first criterion, the method comprises: A cognitive test protocol is performed ( S112 ).

[0321] C22. A method of operating a hearing system according to any of items C19-C21, wherein the external sensor data comprises microphone input data, and wherein the health parameter is based on the microphone input data.

[0322] C23. The method of operating a hearing system according to item C22, wherein determining the health parameter (S106) comprises: A first voice biomarker is determined based on the microphone input data (S106A), and wherein the first criterion is based on the first voice biomarker.

[0323] C24. The method of operating a hearing system according to item C23, wherein determining the first speech biomarker (S106A) comprises: Determining one or more of language parameters, acoustic parameters, speech fluency parameters, mumbling parameters, pitch parameters, and speech rhythm parameters (S106A_1); 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.

[0324] 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.

[0325] C26. The method of operating a hearing system according to item C25, wherein determining the health parameter (S106) comprises: A first physiological biomarker is determined based on the physiological data (S106B), and wherein the first criterion is based on the first physiological biomarker.

[0326] C27. The method of operating a hearing system according to item C26, wherein determining the first physiological biomarker (S106B) comprises: Determine one or more of blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters (S106B_1); and wherein the first physiological biomarker is based on one or more of the blood pressure parameters, blood flow parameters, heart rate parameters, breathing parameters, temperature parameters, oxygen parameters, and brain activity parameters.

[0327] C28. A method of operating a hearing system according to any of items C19-C27, wherein the external sensor data comprises biokinetic data, and wherein the health parameter is based on the biokinetic data.

[0328] C29. The method of operating a hearing system according to item C28, wherein determining the health parameter (S106) comprises: A first biokinetic biomarker is determined based on the biokinetic data (S106C), and wherein the first criterion is based on the first biokinetic biomarker.

[0329] C30. The method of operating a hearing system according to item C29, wherein determining the first biodynamic biomarker (S106C) comprises: One or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter are determined (S106C_1); and wherein the first biodynamic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

[0330] 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: Internal sensor data is acquired from the one or more sensors ( S104 ), and wherein the health parameter is based on the internal sensor data.

[0331] C32. The method of operating a hearing system according to any one of items C19-C31, wherein the electronic device comprises a machine learning circuit configured to operate according to a machine learning model, wherein determining the health parameter (S106) comprises: A health parameter is determined using the machine learning model based on the external sensor data (S106D).

[0332] C33. A method for 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.

[0333] C34. A method for operating a hearing system according to any one of items C19-C33, wherein the electronic device is a server device.

[0334] C35. A method of operating a hearing system according to item C34, wherein the method comprises: Training the machine learning model (S114); providing an updated machine learning model (S116); and The updated machine learning model is transmitted to the electronic device (S118).

[0335] C36. A method of operating a hearing system according to any one of items C19-C35, wherein the electronic device is an accessory device.

[0336] The use of the terms "first", "second", "third" and "fourth", "primary", "secondary", "tertiary", etc. does not imply any particular order, but is used to identify individual elements. Furthermore, the use of the terms "first", "second", "third" and "fourth", "primary", "secondary", "tertiary", etc. does not indicate any order or importance, but rather the terms "first", "second", "third" and "fourth", "primary", "secondary", "tertiary", etc. are used to distinguish between different elements. It should be noted 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, the labeling of a first element does not imply the presence of a second element, and vice versa.

[0337] It is understood that the accompanying drawings include some circuits or operations shown in solid lines, and some circuits, components, features or operations shown in dotted lines. The circuits or operations included in the solid lines are circuits, components, features or operations included in the broadest embodiments. The circuits, components, features or operations included in the dotted lines are embodiments that can be included or as part of them, or other circuits, components, features or operations that can be used in addition to the circuits, components, features or operations of the solid line embodiments. It should be understood that these operations do not need to be performed in order. In addition, it should be understood that not all operations need to be performed. The exemplary 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 order. The circuits, components, features or operations included in the dotted lines can be considered optional.

[0338] Other operations not described herein may also be incorporated into the exemplary operations. For example, one or more additional operations may be performed before, after, simultaneously, or between any of the operations described.

[0339] Certain features discussed above as separate implementations may also be combined and implemented as a single implementation. Conversely, multiple features described as a single implementation may also be implemented as multiple separate implementations, or in any suitable subcombination. Furthermore, although the above features may be described as acting in certain combinations, in some cases one or more features may be removed from the claimed combination, and the combination may be claimed as any subcombination or variation of any subcombination.

[0340] It should be noted that the word "comprising" does not necessarily exclude the presence of other elements or steps than those listed.

[0341] It should be noted that the word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements.

[0342] It should also be noted that any reference signs do not limit the scope of the claims, that embodiments may be implemented at least partially by hardware and software, and that multiple "means," "units," or "devices" may be represented by the same item of hardware.

[0343] The measurement language used herein, such as the terms "approximately", "about", "usually" and "substantially" used herein, represents a value, amount or characteristic that is close to the value, amount or characteristic but still can perform the required function or achieve the required result. For example, the terms "approximately", "about", "usually" and "substantially" can refer to an amount below 10%, below 5%, below 1%, below 0.1% and below 0.01% of the amount. If the amount is 0 (e.g., nothing, no), the above range can be a specific range, rather than within a specific percentage of the value. For example, below 10 wt. / vol.%, below 5 wt. / vol.%, below 1 wt. / vol.%, below 0.1 wt. / vol.% and below 0.01 wt. / vol.% of the amount.

[0344] Although features have been shown and described, it should be understood that they are not intended to limit the claimed invention, and 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 invention. Therefore, the description and drawings should be regarded as illustrative rather than restrictive. The claimed invention is intended to cover all alternatives, modifications and equivalents.

[0345] List of reference numerals: 1.1A, 1B: User 2: System 4: Input, user input 6: Health indication, output 10: Electronic equipment, accessories 10A: One or more interfaces 10B: Memory 10C: Processor 10D: One or more sensors 12: Machine Learning Circuits 13: Control, transmission 14: Get 16: Get 18: Control, transmission 20: Electronic equipment, server equipment 20A: Memory 20B: One or more interfaces 20C: Processor 21: Machine Learning Circuits 22: Control, transmission 24: Get 30: Hearing equipment 30A: One or more interfaces 30B: Memory 30C: Processor 30D: One or more sensors 31: Machine Learning Circuits 32: Control, transmission 34: Get 36: Health indication, output 38: Input, user input 40: Network

Claims

1. An electronic device, comprising: Memory; interface; as well as processor; Wherein, the processor is configured as follows: acquiring external sensor data from the hearing device via the interface; determining, based on the external sensor data, a health parameter indicative of a cognitive state of a user of the hearing device; determining whether the health parameter meets a first criterion indicative of cognitive decline; and Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output via the interface.

2. The electronic device according to claim 1, wherein: Outputting the health representation includes displaying, via the interface, a user interface representing the health representation.

3. An electronic device according to any one of the preceding claims, wherein: Based on satisfying the first criterion, the electronic device is configured to perform a cognitive testing regimen.

4. An electronic device according to any one of the preceding claims, wherein: The external sensor data includes microphone input data, and wherein the health parameter is based on the microphone input data.

5. The electronic device according to claim 4, wherein: Determining a health parameter includes determining a first voice biomarker based on the microphone input data, and wherein the first criterion is based on the first voice biomarker.

6. The electronic device according to claim 5, wherein: Determining the 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; and wherein 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.

7. An electronic device according to any one of the preceding claims, wherein: The external sensor data includes physiological data, and wherein the health parameter is based on the physiological data.

8. The electronic device according to claim 7, wherein: Determining a 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.

9. The electronic device according to claim 8, wherein: Determining a 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 the blood pressure parameter, the blood flow parameter, the heart rate parameter, the breathing parameter, the temperature parameter, the oxygen parameter, and the brain activity parameter.

10. An electronic device according to any one of the preceding claims, wherein: The external sensor data includes biokinetic data, and wherein the health parameter is based on the biokinetic data.

11. The electronic device according to claim 10, wherein: Determining a health parameter comprises determining a first biokinetic biomarker based on the biokinetic data, and wherein the first criterion is based on the first biokinetic biomarker.

12. The electronic device according to claim 11, wherein: Determining a first biokinetic biomarker comprises determining one or more of a motion parameter, a tremor parameter, a jitter parameter, and a twitch parameter; and wherein the first biokinetic biomarker is based on one or more of the motion parameter, the tremor parameter, the jitter parameter, and the twitch parameter.

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

14. An electronic device according to any one of the preceding claims, wherein: The processor includes a machine learning circuit configured to operate according to a machine learning model, wherein determining a health parameter includes determining the health parameter using the machine learning model based on the external sensor data.

15. An electronic device according to any one of the preceding claims, wherein: The interface includes one or more of a Bluetooth interface, a low-power Bluetooth interface, and a magnetic induction interface.

16. A method of operating an electronic device, the method comprising the steps of: Acquiring external sensor data from hearing devices; determining, based on the external sensor data, a health parameter indicative of a cognitive state of a user of the hearing device; determining whether the health parameter meets a first criterion indicative of cognitive decline; as well as Based on the health parameter satisfying the first criterion, a health representation associated with a cognitive state is output.

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