Embodiments herein relate to ear-worn devices and related systems and methods that can be used detect oropharyngeal events and related occurrences such as food and drink intake. In an embodiment, an ear-worn device system is included having a first ear-worn device that has a control circuit, a motion sensor, at least one microphone, an electroacoustic transducer, and a power supply circuit. The system can also include a second ear-worn device. The system can be configured to monitor signals from at least one of the motion sensor and the at least one microphone and evaluate the signals to identify oropharyngeal events and/or related occurrences. Other embodiments are also included herein.

A device can screen swallowing safety and swallowing efficiency. The device includes a processor configured to receive accelerometry data, determine a an A-P and S-I signal summed spectrogram from the accelerometry data, and perform one or more of identifying a missing swallow, identifying that the data was clipped from the start, identifying that the data was clipped from the end, or identifying that the data contains noise. The device can have a user interface configured to provide one or more outputs including at least one of audio or graphics based on these identifications. If the data does not contain these signal quality issues, the device can compare the data against preset classification criteria defined for each of swallowing safety and swallowing efficiency and thus classify each of the swallowing events with a swallowing safety classification and a swallowing efficiency classification.

Various systems and devices are provided for determining a weaning readiness for weaning a patient from a thermoregulated microenvironment. In one example, a method includes receiving current patient parameters of the patient and applying a weaning model to the current patient parameters to calculate a weaning index representing a likelihood that the patient can be successfully weaned from the microenvironment. The method also includes outputting the weaning index for display on a display device or for storage in a medical record of the patient and upon outputting the weaning index, receiving one or more subsequent patient outcomes, the one or more subsequent patient outcomes comprising whether the patient developed any complications within the duration since being weaned from the microenvironment. The method also includes updating the weaning model based on the one or more received subsequent patient outcomes.

A sensor network for measuring physiological parameters of a mammal subject includes a plurality of spatially separated sensor systems that is time-synchronized to each other. Each of the plurality of spatially separated sensor systems is attached to a respective position of the mammal subject and includes a sensor member for measuring at least one physiological parameter, a system on a chip (SoC) having a microprocessor coupled to the sensor member for receiving data from the sensor member and processing the received data, and a transceiver coupled to the SoC for wireless data transmission and wireless power harvesting. The sensor network also includes a microcontroller unit (MCU) adapted in wireless communication with the plurality of spatially separated sensor systems for wirelessly transmitting data to and from the plurality of spatially separated sensor systems.

A swallowing evaluation system (1) includes an ultrasound probe (2), an image acquisition unit that acquires an ultrasound image in a pharynx of a subject by transmitting and receiving an ultrasound beam using the ultrasound probe (2), a sound acquisition unit that acquires a swallowing sound of the subject, and an evaluation unit (19) that evaluates swallowing of the subject using machine learning with a combination of the ultrasound image acquired by the image acquisition unit and the swallowing sound acquired by the sound acquisition unit.

This system for identifying information represented by biological signals is configured so as to detect biological signals (S501), analyze the detected biological signals and then output feature data (S502), determine the respective similarities between the feature data and a plurality of teaching data (S503), store the similarities per time in a time series (S504), and determine information represented by the biological signals on the basis of the plurality of similarities within a prescribed period among the stored similarities in the time series (S505).

Systems, methods, and computer readable media for hyperspectral imaging are provided. An example hyperspectral imaging sensor system to identify item composition includes an imager to capture hyperspectral imaging data of one or more items with respect to a target. The example includes a sensor to be positioned with respect to the target to trigger capture of the image data by the imager based on a characteristic of the target. The example includes a processor to prepare the captured imaging data for analysis to at least: identify the one or more items; determine composition of the one or more items; calculate an energy intake associated with the one or more items; and classify the target based on the energy intake.

An oral care device for placement in the oral cavity. The oral care device may include a support component, a piezoelectric component, and/or a therapeutic element. The support component is configured for placement between one or more maxillary teeth and one or more mandibular teeth. The piezoelectric element is configured to generate an electrical current from relative movement of the maxillary teeth and the mandibular teeth. The therapeutic element is configured to release a therapeutic composition into the oral cavity at least in part in response to receiving the electrical signal. The device may include the piezoelectric component, the therapeutic element, or both.

This system for identifying information represented by biological signals is configured so as to detect biological signals (S501), analyze the detected biological signals and then output feature data (S502), determine the respective similarities between the feature data and a plurality of teaching data (S503), store the similarities per time in a time series (S504), and determine information represented by the biological signals on the basis of the plurality of similarities within a prescribed period among the stored similarities in the time series (S505).

Various systems and devices are provided for determining a weaning readiness for weaning a patient from a thermoregulated microenvironment. In one example, a method includes receiving a plurality of current patient parameters of a patient housed in a thermoregulated microenvironment, applying a weaning model to the plurality of current patient parameters to generate a weaning index representing a likelihood that the patient will be successfully weaned from the microenvironment if weaned at that time, the weaning model trained to correlate the current patient parameters with the likelihood based on historical data of prior patients and known outcomes for those prior patients, and outputting the weaning index for display on a display device and/or for storage in a medical record of the patient.