Abstract: A processing system includes methods to promote sleep. The system may include a monitor such as a non-contact motion sensor from which sleep information may be determined. User sleep information, such as sleep stages, hypnograms, sleep scores, mind recharge scores and body scores, may be recorded, evaluated and/or displayed for a user. The system may further monitor ambient and/or environmental conditions corresponding to sleep sessions. Sleep advice may be generated based on the sleep information, user queries and/or environmental conditions from one or more sleep sessions. Communicated sleep advice may include content to promote good sleep habits and/or detect risky sleep conditions. In some versions of the system, any one or more of a bedside unit 3000 sensor module, a smart processing device, such as a smart phone or smart device 3002, and network servers may be implemented to perform the methodologies of the system.

Abstract: Provided herein is an engagement and care support platform (“ECSP”) computer system including at least one processor in communication with at least one memory device for facilitating senior user engagement. The processor is programmed to: (i) register a user through an application, (ii) register a caregiver associated with the user through the application, (iii) generate a senior profile based upon user personal and scheduling data, (iv) build a daily interactive user interface that reflects the senior profile, (v) display the daily interactive user interface at a first client device associated with the user, (vi) cause the first client device to initiate a daily interaction prompt to the user, (vii) determine whether any user interaction was received in response to the daily interaction prompt, and (viii) transmit a daily update message to a second client device associated with the caregiver, including an indication of whether any user interaction was received.

Abstract: Provided herein is an engagement and care support platform (“ECSP”) computer system including at least one processor in communication with at least one memory device for facilitating senior user engagement. The processor is programmed to: (i) register a user through an application, (ii) register a caregiver associated with the user through the application, (iii) generate a senior profile based upon user personal and scheduling data, (iv) build a daily interactive user interface that reflects the senior profile, (v) display the daily interactive user interface at a first client device associated with the user, (vi) cause the first client device to initiate a daily interaction prompt to the user, (vii) determine whether any user interaction was received in response to the daily interaction prompt, and (viii) transmit a daily update message to a second client device associated with the caregiver, including an indication of whether any user interaction was received.

Abstract: Provided herein is a digital care circle platform for electronic communication between a senior and virtual care circle members. The digital care circle platform may include a chatbot and an application associated with the senior, a mobile application associated with the plurality of virtual care circle members, at least one processor in communication with at least one memory device, and one or more servers, sensors, wearables, and transceivers. The at least one processor may be configured to: (i) accept event posts from the senior via the chatbot and application and from each virtual care circle member of the plurality of virtual care circle members via the mobile application, (ii) detect pro-active check-ins from the senior, and (iii) generate, once a pro-active check-in is detected, an electronic communication detailing the pro-active check-in as a pro-active check-in event, and transmit the pro-active check-in event to the virtual care circle members.

Abstract: Described herein are systems, mediums, and methods for simultaneously determining multiple types of changes in time series data. A plurality of potential change points may be selected in a signal representing the time series data. For each potential change point the signal may be a split into two segments including data points before and data points after the potential change point, respectively. Estimate of cumulative distribution function for each segment may be determined. A normalized difference of the respective estimates of cumulative distribution functions may be determined. The normalized difference may be compared to a threshold value to determine whether the potential change point qualifies as valid change point. The techniques discussed herein may determine at least two valid change points representing at least two different types of changes in the signal.