Abstract: According to some embodiments, system and methods for representing nodes and data flows in a network are provided, comprising providing a hierarchical taxonomy for one or more concepts; providing one or more hierarchical taxonomies for one or more boundary types, wherein one or more values from each boundary type are combined to form a definition of a boundary; and associating the at least one concept and at least one boundary with a transmission of data between a first node and a second node, wherein the transmitted data is a data flow. Numerous other aspects are provided.

Abstract: According to some embodiments, system and methods for representing nodes and data flows in a network are provided, comprising providing a hierarchical taxonomy for one or more concepts; providing one or more hierarchical taxonomies for one or more boundary types, wherein one or more values from each boundary type are combined to form a definition of a boundary; and associating the at least one concept and at least one boundary with a transmission of data between a first node and a second node, wherein the transmitted data is a data flow. Numerous other aspects are provided.

Abstract: Certain embodiments provide a method for viewing biometrical information, determining the clinical state of the patient, and dynamically adapting schedule and process interdependencies in a clinical environment. The method includes deriving a schedule including at least one patient treatment protocol based on a mathematical model using people and asset information as input. The method also includes processing input biometrical data indicating a patient status. Additionally, the method includes adapting the at least one patient treatment protocol based on the biometrical data. Further, the method includes revising the schedule based on adapting the at least one patient treatment protocol. In certain embodiments, the method includes recalculating a critical path, schedule tasks, and resource allocation based on adapting the at least one patient treatment protocol and revising the schedule.

Abstract: An apparatus in one example comprises a user wearable, non-encumbering, movement sensor and an analyzer. The user wearable, non-encumbering, movement sensor substantially continuously measures daily-activity data of a patient. The analyzer makes a determination from the daily-activity data of the patient that a change in condition of the patient has occurred. The analyzer generates an indication of the change in condition of the patient for access by a remote caregiver.

Abstract: A device, system and method for monitoring the activity of one or more residents in a habitable structure so as to ascertain whether the activity, or inactivity, is unusual. A variety of sensors distributed around the home collect data on activity in the home. The monitored person or persons wear an independent activity detector that monitors individual activity of a specific person. The house data is communicated to a remote monitoring center, and the individual data is communicated to an analyzing mechanism, which may be a communication panel or the remote monitoring center. The house data and individual data are analyzed and compared to ascertain whether any specific person within the habitable structure is engaged in unusual activity or inactivity. The independent activity detector may be configured to transmit an authentication signal to authenticate specific detected activity with a specific person.

Abstract: A system and method for detecting a period of unusual inactivity of a person is provided. The system comprises a monitoring system, which is in communication with location and motion sensors. The monitoring system comprises a processor-based device programmed to develop a model of the person's periods of inactivity within a structure based on data received from the sensors. The processor-based device may also be programmed to determine if a current period of inactivity within the structure is a period of normal inactivity or a period of unusual inactivity based on the model of the person's periods of inactivity.

Abstract: A system and method for identifying a change in walking speed of a person is provided. The system comprises a plurality of sensors disposed in various rooms of a structure. The sensors are operable to provide a signal representative of motion and/or the location of the person within the structure. The system may also include a processor-based system that may receive signals representative of the motion and/or location of the person from the sensors. The processor-based system may establish a travel time for a path traveled by the person through the structure based on the signals representative of the motion and/or location of the person and may store the travel time within the processor-based system. The processor-based system may identify at least one path traveled by the person through the structure from among various travel paths traveled by the person through the structure as having a consistent travel time over a period of time.

Abstract: A system and method for monitoring whether a resident is away from home or inactive within the home. A sensor, which includes a transmitter, a processor, a timer, and a detector, watches for motion to occur within a home. Upon sensing motion, the sensor sends a first signal indicative of the motion if the timer is not currently running and waits for the motion to end. If the timer already is running, the timer is restarted at zero. Upon expiration of a predetermined timing period, the sensor transmits a second signal indicative of inactivity. By comparing the timing of the second signal and the predetermined timing period, with a third signal sent by an exterior door sensor, a determination can be made whether the resident has left the home or is inactive within the home. The system includes a database, a CPU and State Model for determining the activity state of a home.

Abstract: A system and method for monitoring the activities of a resident living independently to distinguish normal activity from unusual activity. A variety of sensors distributed around the home collect data on activity in the home. The data is communicated to a remote monitoring center and collated in a database according to applicable time slots. The time slots for a twenty-four hour cycle are at least three and can be as many as forty-eight or more. Historical activity time lines are created and a buffer time is added to and offset from the maximum historical activity time line. If a new data point comes in that exceeds both the maximum historical activity time line and the buffer time, an alert is issued indicating the activity is unusual.

Abstract: A system and method for monitoring the activities of a resident living independently. Activity sensors distributed around the home collect data on activity in the home. The data is communicated to a remote monitoring center and analyzed. The data is buffered to ascertain whether an event or important transition has occurred in the home. The system also may be utilized to ascertain long-term mobility changes in the resident, deviations from normal sleep patterns, and deviations from a normal wake up time.