Abstract: Methods and systems for an integrated sensor network are described. In one embodiment, sensor data may be accessed from a plurality of motion sensors and a bed sensor deployed in a living unit for a first time period. An activity pattern for the first time period may be identified based on at least a portion of sensor data associated with the first time period. The activity pattern may represent a physical and cognitive health condition of a person residing in the living unit. Additional sensor data may be accessed from the motion sensors and the bed sensor deployed for a second time period. A determination of whether a deviation of the activity pattern of the first time period has occurred for the second time period may be performed. An alert may be generated based on a determination that the derivation has occurred. In some embodiments, user feedback is captured on the significance of the alerts, and the alert method is customized based on this feedback. Additional methods and systems are disclosed.

Abstract: Methods and systems for an integrated sensor network are described. In one embodiment, sensor data may be accessed from a plurality of motion sensors and a bed sensor deployed in a living unit for a first time period. An activity pattern for the first time period may be identified based on at least a portion of sensor data associated with the first time period. The activity pattern may represent a physical and cognitive health condition of a person residing in the living unit. Additional sensor data may be accessed from the motion sensors and the bed sensor deployed for a second time period. A determination of whether a deviation of the activity pattern of the first time period has occurred for the second time period may be performed. An alert may be generated based on a determination that the derivation has occurred. In some embodiments, user feedback is captured on the significance of the alerts, and the alert method is customized based on this feedback. Additional methods and systems are disclosed.

Abstract: Methods and systems for an integrated sensor network are described. In one embodiment, sensor data may be accessed from a plurality of motion sensors and a bed sensor deployed in a living unit for a first time period. An activity pattern for the first time period may be identified based on at least a portion of sensor data associated with the first time period. The activity pattern may represent a physical and cognitive health condition of a person residing in the living unit. Additional sensor data may be accessed from the motion sensors and the bed sensor deployed for a second time period. A determination of whether a deviation of the activity pattern of the first time period has occurred for the second time period may be performed. An alert may be generated based on a determination that the derivation has occurred. In some embodiments, user feedback is captured on the significance of the alerts, and the alert method is customized based on this feedback. Additional methods and systems are disclosed.

Abstract: Methods and systems for an integrated sensor network are described. In one embodiment, sensor data may be accessed from a plurality of motion sensors and a bed sensor deployed in a living unit for a first time period. An activity pattern for the first time period may be identified based on at least a portion of sensor data associated with the first time period. The activity pattern may represent a physical and cognitive health condition of a person residing in the living unit. Additional sensor data may be accessed from the motion sensors and the bed sensor deployed for a second time period. A determination of whether a deviation of the activity pattern of the first time period has occurred for the second time period may be performed. An alert may be generated based on a determination that the derivation has occurred. In some embodiments, user feedback is captured on the significance of the alerts, and the alert method is customized based on this feedback. Additional methods and systems are disclosed.

Abstract: Methods and systems for an integrated sensor network are described. In one embodiment, sensor data may be accessed from a plurality of motion sensors and a bed sensor deployed in a living unit for a first time period. An activity pattern for the first time period may be identified based on at least a portion of sensor data associated with the first time period. The activity pattern may represent a physical and cognitive health condition of a person residing in the living unit. Additional sensor data may be accessed from the motion sensors and the bed sensor deployed for a second time period. A determination of whether a deviation of the activity pattern of the first time period has occurred for the second time period may be performed. An alert may be generated based on a determination that the derivation has occurred. In some embodiments, user feedback is captured on the significance of the alerts, and the alert method is customized based on this feedback. Additional methods and systems are disclosed.

Abstract: Methods and systems for anonymized video analysis are described. In one embodiment, a first silhouette image of a person in a living unit may be accessed. The first silhouette image may be based on a first video signal recorded by a first video camera. A second silhouette image of the person in the living unit may be accessed. The second silhouette image may be of a different view of the person than the first silhouette image. The second silhouette image may be based on a second video signal recorded by a second video camera. A three-dimensional model of the person in voxel space may be generated based on the first silhouette image, the second silhouette image, and viewing conditions of the first video camera and the second video camera. In some embodiments, information on falls, gait parameters, and other movements of the person living unit are determined. Additional methods and systems are disclosed.

Abstract: Methods and systems for anonymized video analysis are described. In one embodiment, a first silhouette image of a person in a living unit may be accessed. The first silhouette image may be based on a first video signal recorded by a first video camera. A second silhouette image of the person in the living unit may be accessed. The second silhouette image may be of a different view of the person than the first silhouette image. The second silhouette image may be based on a second video signal recorded by a second video camera. A three-dimensional model of the person in voxel space may be generated based on the first silhouette image, the second silhouette image, and viewing conditions of the first video camera and the second video camera. In some embodiments, information on falls, gait parameters, and other movements of the person living unit are determined. Additional methods and systems are disclosed.

Abstract: Methods and systems for an integrated sensor network are described. In one embodiment, sensor data may be accessed from a plurality of motion sensors and a bed sensor deployed in a living unit for a first time period. An activity pattern for the first time period may be identified based on at least a portion of sensor data associated with the first time period. The activity pattern may represent a physical and cognitive health condition of a person residing in the living unit. Additional sensor data may be accessed from the motion sensors and the bed sensor deployed for a second time period. A determination of whether a deviation of the activity pattern of the first time period has occurred for the second time period may be performed. An alert may be generated based on a determination that the derivation has occurred. In some embodiments, user feedback is captured on the significance of the alerts, and the alert method is customized based on this feedback. Additional methods and systems are disclosed.