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: 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: 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: 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: 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 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: 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: 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 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: A method comprising determining, by a processing system, based on a first oral gesture detected by an intra-oral device located in a mouth of a user, an intended communication partner from among a plurality of available communication partners; determining, by the processing system, a message based on a series of one or more second oral gestures detected by the intra-oral device; and sending, by the processing system, the message to a communication device associated with the intended communication partner.

Abstract: A system includes sample containers and a computing system. The sample containers include one or more data storage media configured to store sample information relating to the respective sample contained in each sample container. The sample information include data indicating a sample type, an intended use of the sample contained within the respective sample container, and a sample collection time. The computing system is configured to receive the sample information from the sample containers and determine, based on the sample information, an action for increasing a likelihood that one or more applicable samples of the plurality of samples will be viable for the intended uses of the applicable samples. The computing system is further configured to perform the action.