Abstract: An example method includes obtaining, by processing circuitry, an image depicting a face of a person wearing eyewear and a reflection pattern generated by projecting light onto a lens of the eyewear and determining, by the processing circuitry, an optical parameter of the lens based on the image. The method further includes receiving, by the processing circuitry and from an electronic database, a personal characteristic data relating to a previously identified person and comparing, by the processing circuitry, the optical parameter of the lens to the personal characteristic data. The method further includes determining, by the processing circuitry and based on the comparison, a score indicative of a match between the person wearing eyewear and the previously identified person.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing splinting activity detection. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform splinting activity detection using at least one of splinting activity detection machine learning models, observed inspiration-expiration waveform pattern, and expected inspiration-expiration waveform patterns.

Abstract: Embodiments of the invention provide apparatuses, systems, and methods for more accurate remote monitoring of a user's body. In some embodiments, a system for monitoring a user's body comprises a wearable device, a video sensor attached at a collar portion of the wearable device, a plurality of audio sensors spaced and attached at a body portion of a wearable device and a controller configured to determine a Jugular Venous Pressure (JVP) of the user, and determine audio characteristics of an output of the plurality of audio sensors to generate an audio heat map corresponding to at least one internal organ of the user.

Abstract: A computing system includes a storage device and processing circuitry. The processing circuitry is configured to obtain an image frame that comprises a plurality of pixels that form a pixel array. Additionally, the processing circuitry is configured to determine that a region of the image frame belongs to a trigger content type. Based on determining that the region of the image frame belongs to the trigger content type, the processing circuitry is configured to modify the region of the image frame to adjust a luminance of pixels of the region of the image frame based on part on an ambient light level in a viewing area of the user; and output, for display by a display device in the viewing area of the user, a version of the image frame that contains the modified region.

Abstract: Embodiments of the invention provide methods for identifying suspect heart or lung sounds and methods for generating an isolated sound sample. In some embodiments, a method for identifying suspect heart or lung sounds comprises obtaining, by processing circuitry, an instance of data samples comprising at least two audio samples and respiratory and/or cardiac cycle data, the audio samples comprising auscultation sounds of an individual, based on the respiratory and/or cardiac cycle data, processing the at least two audio samples to generate a plurality of sound samples, identifying a primary sound sample, generating at least one of a modified secondary sound or a modified baseline sample and combining the modified secondary sound sample or the modified baseline sample with the primary sound sample to generate an isolated sound sample.

Abstract: A computing system includes a storage device and processing circuitry. The processing circuitry is configured to obtain an image frame that comprises a plurality of pixels that form a pixel array. Additionally, the processing circuitry is configured to determine that a region of the image frame belongs to a trigger content type. Based on determining that the region of the image frame belongs to the trigger content type, the processing circuitry is configured to modify the region of the image frame to adjust a luminance of pixels of the region of the image frame based on part on an ambient light level in a viewing area of the user; and output, for display by a display device in the viewing area of the user, a version of the image frame that contains the modified region.

Abstract: An example method comprises determining, by a computing system, that a message-sending computing device has received an indication of user input indicating an intent to send a message to a user of a message-recipient computing device; prior to the message being delivered to the message-recipient computing device, calculating, by the computing system, a screen sharing risk score (SSRS) that indicates a risk that the message-recipient computing device is currently sharing screen content of a screen of the message-recipient computing device with a screen-recipient computing device associated with an untrusted screen-recipient user; and based on the SSRS indicating that the risk is above a risk threshold, causing the message-sending computing device to output an alert indicating that the message-recipient computing device is possibly sharing the screen content of the message-recipient computing device with the screen-recipient computing device associated with the untrusted screen-recipient user.

Abstract: A centrifuge includes a chamber configured to contain a set of one or more samples, an image sensor configured to generate image data, and processing circuitry. The processing circuitry is configured to: initiate centrifugation of the set of samples about a central axis; obtain a set of image data generated by the image sensor during centrifugation of the set of samples; and for each respective sample of the set of samples, apply a machine learning model configured to generate, based on image data representative of the respective sample in the set of image data, a viability score for the respective sample; determine whether the viability score for the respective sample satisfies a viability condition; and output whether the viability score for the respective sample satisfies the viability condition.

Abstract: An example method includes obtaining, by processing circuity, an image depicting a face of a person wearing eyewear and a reflection pattern generated by projecting light onto a lens of the eyewear and determining, by the processing circuitry, an optical parameter of the lens based on the image. The method further includes receiving, by the processing circuitry and from an electronic database, a personal characteristic data relating to a previously identified person and comparing, by the processing circuitry, the optical parameter of the lens to the personal characteristic data. The method further includes determining, by the processing circuitry and based on the comparison, a score indicative of a match between the person wearing eyewear and the previously identified person.

Abstract: Various embodiments of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for providing audio stimulation and monitoring patient response information associated therewith. For example, various embodiments provide techniques for generating audio treatment profiles using audio stimulus prediction machine learning models and for use in conjunction with patient monitoring devices.

Abstract: Apparatus, systems, and methods for real time monitoring of a patient's breathing utilizing automatically controlled devices and machine learning based techniques to determine a full breath of a patient and to identify splinting points, and to thereby transmit stimulation signals to the patient so as to assist the patient breathe through splinting points. In some embodiments, a wearable breathing monitoring device comprising of one or more sensors configured to monitor the user's breathing and a stimulator apparatus comprising one or more transmitters configured to transmit stimulation signals to the patient at a time corresponding to a detected splinting point is provided. The stimulator apparatus is configured to apply electrical pulses according to a stimulation schedule via the transmitters to target nerves of the user's body.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing optimized breathing therapy. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform optimized breathing therapy using at least one of interruption score generation machine learning models, observed inspiration-expiration pattern, expected inspiration-expiration patterns, expected musical patterns, and inferred musical patterns.

Abstract: Various embodiments of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for monitoring a user's movement in real-time and providing or augmenting stimulation. For example, various embodiments provide techniques generating movement prediction profiles using movement prediction machine learning models and for use in conjunction with wearable devices.

Abstract: Various embodiments of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for detecting and preventing seizure events in real-time. For example, various embodiments provide techniques for detecting and preventing seizure events in real-time that use seizure prediction machine learning models.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive respiratory quality score assignment. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive respiratory quality score assignment using at least one of respiratory quality evaluation scoring machine learning models, explanation generation machine learning model, supplemental feature extraction machine learning model, and observed sensory data.

Abstract: A computing device may receive, from a remote computing device, a request to establish a communication session with the remote computing device and contextual information indicative of an urgency level of the communication session. The computing device may output, at one or more output devices, the contextual information indicative of the urgency level of the communication session and at least one of: haptic output or an audible alert that indicates the request to establish the communication session.

Abstract: Embodiments of the invention provide apparatuses, systems, and methods for more accurate remote monitoring of a user’s body. In some embodiments, a system for monitoring a user’s body comprises a wearable device, a video sensor attached at a collar portion of the wearable device, a plurality of audio sensors spaced and attached at a body portion of a wearable device and a controller configured to determine a Jugular Venous Pressure (JVP) of the user, and determine audio characteristics of an output of the plurality of audio sensors to generate an audio heat map corresponding to at least one internal organ of the user.

Abstract: To provide objective indications of the progression of peripheral neuropathy of patients, a transmitter apparatus is utilized to produce reproducible pulse signals to specified locations on the human body to determine a minimum level of stimulation necessary to elicit a consciously detectable sensation through the generation of a series of pulse signals of varying intensities, and the recordation of the number of pulse signals felt by the patient. Moreover, the nerve velocity of the patient is additionally determined for a patient via the transmitter apparatus and a receiver apparatus detecting body-signals passing along a nerve within the patient and corresponding to the pulse signals applied to the patient. The results of these tests are recorded over time, thereby enabling generation of patient-specific models indicative of the progression of the patient's peripheral neuropathy over time.

Abstract: A controller for an artificial heart enables activity-specific adjustments to the operation of an artificial heart by obtaining sensor data from a plurality of sensors monitoring characteristics of a patient's body, and using the sensor data as input to one or more control parameter models for identifying control parameters to be provided to the artificial heart to adjust the operational parameters of the artificial heart. The controller is in wireless communication with the artificial heart via an application program interface (API)-based communication channel that facilitates communication between the controller and the artificial heart. Moreover, a cloud-based management computing entity may be utilized to train and/or execute one or more models to enable real-time updates to the operational characteristics of the artificial heart to enable the artificial heart to appropriately accommodate activities of the patient.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing optimized equipment allocation. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform optimized equipment allocation using at least one of equipment evaluation scoring machine learning models, equipment optimized allocation machine learning models, and equipment history events.