Systems and methods to connect care seekers with care providers for caretaking needs are disclosed. Exemplary implementations may: store seeker profiles for care seekers and/or provider profiles for care providers; present a user interface configured to facilitate generation of individual provider profiles; receive care seeker-defined characteristics of potential care providers; generate new individual provider profiles for individual potential care providers; and/or perform other operations.

Systems and methods to connect care seekers with care providers for caretaking needs are disclosed. Exemplary implementations may: store seeker profiles for care seekers and/or provider profiles for care providers; present a user interface configured to facilitate generation of individual provider profiles; receive care seeker-defined characteristics of potential care providers; generate new individual provider profiles for individual potential care providers; and/or perform other operations.

A therapy platform can leverage mood tracking to personalize delivery of therapy. User input data is collected to generate one or more mood scores that change over time. Tracked mood scores can include an overall mood score (e.g., −100 to 100 where −100 represents a strongly negative or “bad” mood and 100 represents a strongly positive or “happy” mood) and/or enumerated mood scores (e.g., numerical scores tracking individual, enumerated moods, such as “anxious,” “sad,” “tired,” “happy,” and the like). In some cases, an overall mood score can be made up of enumerated mood scores. Tracked mood scores can be used to inform the selection of what therapy to provide. For example, a first therapy tool may be selected for delivery when the user evidences a first set of mood scores, whereas a second therapy tool may be selected when the user evidences a second set of mood scores.

A computer-implemented system may include an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac condition or a cardiac outcome, generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.

An excrement management system according to an embodiment includes: a closet bowl in which a bowl part for receiving excrement is formed; a light emitting unit configured to emit light toward an inner part of the closet bowl; a light receiving unit comprising an image sensor configured to receive light; a cloud server and an edge server configured to analyze light reception data received by the light receiving unit; a first communication device configured to transmit the light reception data to the cloud server; and a second communication device configured to transmit the light reception data to the edge server. The cloud server analyzes the light reception data to determine a characteristic of excrement, and the edge server analyzes the light reception data to determine whether to transmit the light reception data to the cloud server by the first communication device.

A system and method for providing an individual with information on the actual healthcare utilization of other members of that individual's social network, the method including de-identifying or encrypting individually identifiable social network data associated with a first user, de-identifying or encrypting individually identifiable healthcare transaction data associated with the first user, and linking the de-identified social network data and the de-identified healthcare transaction data.

A system and method for providing an individual with information on the actual healthcare utilization of other members of that individual's social network, the method including de-identifying or encrypting individually identifiable social network data associated with a first user, de-identifying or encrypting individually identifiable healthcare transaction data associated with the first user, and linking the de-identified social network data and the de-identified healthcare transaction data.

Techniques disclosed herein relate to monitoring changes in conditions of multiple individuals in areas. In some embodiments, a patient monitoring queue may be established (504) that includes a plurality of patients in an area (104, 304) such as a waiting room. The area may be capturable by vital sign acquisition camera(s) (276. 376, 476) mounted in or near the area. Updated vital sign(s) may be unobtrusively acquired (510) by the vital sign acquisition camera(s) from a given patient selected (506) from the patient monitoring queue. Based on the updated vital sign(s) and prior vital signs acquired previously from the given patient, deterioration of the given patient may be detected (512). Output may be provided (514) alerting medical personnel of the deterioration of the given patient.

A system, method and wireless earpieces for populating an electronic health record utilizing wireless earpieces. Sensor measurements of a user are performed utilizing sensors of the wireless earpieces. The sensor measurements are analyzed. The sensor measurements are associated with the electronic health record of the user. The electronic health record of the user is populated with the sensor measurements. Communications including information from the electronic health record are communicated.

A system, method and wireless earpieces for populating an electronic health record utilizing wireless earpieces. Sensor measurements of a user are performed utilizing sensors of the wireless earpieces. The sensor measurements are analyzed. The sensor measurements are associated with the electronic health record of the user. The electronic health record of the user is populated with the sensor measurements. Communications including information from the electronic health record are communicated.