A relaxation mask includes: a main body that defines a pair of eye cavities; and a light diffuser. The light diffuser includes a first lens that is disposed within a first one of the eye cavities. A first ledge is disposed along a top edge of the first lens and extends outwardly therefrom. A first light emitting component is supported on the first ledge and is configured to fire downward into the first lens.

An electronic device and method for providing information for stress relief are disclosed. The electronic device includes a user interface, at least one sensor, at least one processor operatively connected to the user interface and the at least one sensor, and a memory operatively connected to the at least one processor. The memory stores instructions to, when executed, cause the at least one processor to collect stress-related information through at least a part of the at least one sensor, identify contextual information of a user when stress calculated based on the collected stress-related information satisfies a designated condition, and guide at least one of a plurality of stress relief methods through the user interface at least based on the identified contextual information.

An injection system is described that receives, from one or more sensors, a first group of one or more signals indicating a current volume of injection fluid dispensed from a fluid reservoir at a first time. The injection system determines, based on the first group of one or more signals, that a difference between a dispensed volume limit and the current volume of the injection fluid dispensed from the fluid reservoir at the first time is less than a necessary volume of fluid required to complete both a systolic injection phase and a diastolic injection phase. The injection system further, responsive to determining that the difference is less than the necessary volume of fluid required to complete both the systolic injection phase and the diastolic injection phase, controls the injection system to refrain from performing each of the systolic injection phase and the diastolic injection phase.

Systems and methods for managing heart failure are described. The system receives physiological information including a first HS signal corresponding to paced ventricular contractions and a second HS signal corresponding to intrinsic ventricular contractions. The system detects worsening heart failure (WHF) using the received physiological information. A signal analyzer circuit can generate a paced HS metric from the first HS signal and a sensed HS metric from the second HS signal, and determine a concordance indicator between the paced and the sensed HS metrics. In response to the detected WHF, the system can use the concordance indicator to generate a therapy adjustment indicator for adjusting electrostimulation therapy, or a worsening cardiac contractility indicator indicating the detected WHF is attributed to degrading myocardial contractility.

The disclosed system receives various physiological as well as physical information concerning a patient, and operational data from a ventilation device and medication delivery device, and provides the physiological and physical information, together with the operational data, to a neural network configured to analyze the information and data. The system receives, from the neural network, an assessment classification of the patient corresponding to at least one of a pain assessment, a sepsis assessment, and a delirium assessment of the patient based on providing to the neural network the determined physiological state of the patient, the determined physical state of the patient, the determined operational mode of the ventilator, the medication delivery information, and the received diagnostic information for the patient, and adjusts, based on the assessment classification, a ventilation parameter that influences the operational mode of a ventilator providing ventilation to the patient.

The disclosed system receives various physiological as well as physical information concerning a patient, and operational data from a ventilation device and medication delivery device, and provides the physiological and physical information, together with the operational data, to a neural network configured to analyze the information and data. The system receives, from the neural network, an assessment classification of the patient corresponding to at least one of a pain assessment, a sepsis assessment, and a delirium assessment of the patient based on providing to the neural network the determined physiological state of the patient, the determined physical state of the patient, the determined operational mode of the ventilator, the medication delivery information, and the received diagnostic information for the patient, and adjusts, based on the assessment classification, a ventilation parameter that influences the operational mode of a ventilator providing ventilation to the patient.

A sleep-aiding audio signal updating method and apparatus in the artificial intelligence (AI) field is provided. The method includes: obtaining a first biological signal collected when a first audio signal in a sleep-aiding audio library is played, where the first biological signal is a biological signal of a first user; determining a sleep quality of the first user based on the first biological signal; and updating the sleep-aiding audio library based on the sleep quality of the first user, so that a sleep-aiding audio signal can be updated, to provide a proper sleep-aiding audio signal for a user, and ensure a sleep-aiding effect.

A sleep-aiding audio signal updating method and apparatus in the artificial intelligence (AI) field is provided. The method includes: obtaining a first biological signal collected when a first audio signal in a sleep-aiding audio library is played, where the first biological signal is a biological signal of a first user; determining a sleep quality of the first user based on the first biological signal; and updating the sleep-aiding audio library based on the sleep quality of the first user, so that a sleep-aiding audio signal can be updated, to provide a proper sleep-aiding audio signal for a user, and ensure a sleep-aiding effect.

Systems and methods for tracking sympathetic-driven arousal state (SDAS) including nociception under anesthesia is described herein. The method includes obtaining heart rate variability and electrodermal activity of a subject. Point process models are generated for the heart rate variability and the electrodermal activity. A multimodal approach is implemented to determine a state space framework based on these point process models. SDAS can be estimated using the state space framework. In some implementations, an anesthesiologist can modify the dosage of drugs administered to the subject based on this estimation.

A computer system for blue-light therapy comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions including determining a need for blue-light therapy, and providing a blue-light stimulus to a user, wherein the blue-light stimulus comprises a visible range of 380 to 500 nm, and wherein, in response to the blue-light stimulus, a circadian rhythm of the user is shifted to a second rhythm, the second rhythm different than the circadian rhythm prior to the administration of the blue-light stimulus.