Abstract: A method for generating a prediction of a latency of a transaction processing system includes: sampling a first plurality of messages from a database that stores data indicative of messages previously processed by the transaction processing system including a characteristic and a processing time of each previously processed message; generating latency tables based upon the characteristics and the processing times of the sampled first plurality of messages; determining a characteristic of each of a second plurality of messages being processed by the transaction processing system; selecting, for each of the second plurality of messages, a latency table from the plurality of latency tables based upon the respective determined characteristic; simulating a processing time for each of the second plurality of messages based upon the respective selected latency table; and generating a latency prediction for the transaction processing system based upon the simulated processing times for the second plurality of message

Abstract: Disclosed herein, among other things, are systems, apparatus and methods for directional microphone accessories for hearing device applications. An apparatus includes a base, at least one strap configured to attach the base to a top portion of a seat back, and a pivoting mount configured to be attached to the base, the pivoting mount configured to hold a directional microphone assembly. The pivoting mount is further configured to maintain the directional microphone assembly in an approximately horizontal orientation independent of a recline angle of the seat back.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A computing system receives sharing preference data. The sharing preference data indicate, for each respective health-related data type of a plurality of health-related data types: (i) whether a user of an ear-wearable device allows sharing of health-related data belonging to the respective health-related data type, and (ii) if the user of the ear-wearable device allows sharing of health-related data belonging to the respective health-related data type, a set of one or more users allowed by the user of the ear-wearable device to access the health-related data belonging to the respective health-related data type.

Abstract: A computing system receives data from one or more hearing instruments. Additionally, the computing system determines, based on the data received from the one or more hearing instruments, a heart health measure for a user of the one or more hearing instruments. The heart health measure is an indication of one or more aspects of a health of a heart of the user. The computing system may output an indication of the heart health measure.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: Various embodiments relate to a degrade-resistant surge suppressor that detects and suppresses surge events. The surge suppressor includes a high impedance high pass filter, one or more series inductors, and one or more capacitor banks. The capacitor bank may include a bridge rectifier circuit having two diodes and two SCRs (Silicon-Controlled Rectifiers), or a diode bridge rectifier fed by a TRIAC (Node for Alternating Current). The surge suppressor may further include a secondary trigger device to ensure proper attenuation of surge events.

Abstract: Various embodiments relate to a degrade-resistant surge suppressor that detects and suppresses surge events. The surge suppressor includes a high impedance high pass filter, one or more series inductors, and one or more capacitor banks. The capacitor bank may include a bridge rectifier circuit having two diodes and two SCRs (Silicon-Controlled Rectifiers), or a diode bridge rectifier fed by a TRIAC (Node for Alternating Current). The surge suppressor may further include a secondary trigger device to ensure proper attenuation of surge events.