The present disclosure relates to an apparatus (100) for passive scanning of an object. The apparatus comprises a distance sensing unit (110) adapted to measure distances to a plurality of points of the object, an orientation sensing unit (120) adapted to determine orientations of the distance sensing unit (110), and a processor (140) adapted to derive information about the object or a scene in which the object is used based on the measured distances and orientations of the distance sensing unit (110).

Systems, methods and media are disclosed for identifying the crossing of a virtual barrier. A person in a 3D image of a room may be circumscribed by a bounding box. The position of the bounding box may be monitored over time, relative to the virtual barrier. If the bounding box touches or crosses the virtual barrier, an alert may be sent to the person being monitored, a caregiver or a clinician. Bounding box tracking may be used in addition to or instead of an initial tracking process, such as skeletal tracking.

A retrofittable commode attachment device that automatically measures and charts electronically one or more types of health data. The device includes a base platform with a back portion, a left side portion, a right side portion and a front portion, a plurality of load cells on the left side of the base platform and a plurality of load cells on the right side of the base platform, at least one microphone, at least one camera, and at least two commode connector brackets that engage the horizontal support of a commode and the base platform is positioned below the toilet seat of the commode and is not part of the toilet seat.

A travel distance calculation device is configured to: add a first distance between a first main sensor and a hub sensor to a travel distance when a person is detected by the hub sensor provided in a third space connecting a first space and a second space after the person is detected by the first main sensor provided in the first space; add a second distance between a second main sensor and the hub sensor to the travel distance when the person is detected by the hub sensor after the person is detected by the second main sensor provided in the second space; and add no third distance between the first main sensor and the second main sensor to the travel distance when the person is detected by the second main sensor after the person is detected by the first main sensor.

A monitoring system is provided for monitoring an infant during bottle feeding. Based on bottle orientation information and movement information in respect of the feeding bottle during feeding, infant orientation information in respect of the infant is obtained.

Various embodiments provide systems and methods for identifying impairment using measurement devices.

Disclosed in the present disclosure is a method, system and apparatus for prediction, estimation and prevention of occurrence of agitation episode in a subject predisposed to agitation. The method comprises receiving, from a first monitoring device attached to a subject, physiological data of sympathetic nervous system activity in the subject and activity data of the subject; receiving, from a computing device, a plurality of indications associated with a plurality of agitation episodes of the subject; analyzing, using at least one machine learning model, the physiological data, the activity data, and the plurality of indications to determine a probability of an occurrence of an agitation episode of the subject; and sending a signal to a second monitoring device to notify the second monitoring device of the probability of the occurrence of the agitation episode of the subject such that treatment can be provided to the subject to decrease sympathetic nervous system activity in the subject.

Certain embodiments of the present disclosure relate to a monitoring device that includes a housing, contactless sensors coupled to the housing, and a processing device disposed in the housing. In at least one embodiment, the monitoring device is configured to measure pulse wave velocity in a subject.

Nocturia has been defined as the need for an individual to wake up one or more times during the night to void. Further, Nocturia detection also requires analysis of sleeping pattern of the person. In such cases a lot of assumptions are made when the person is not in bedroom during nights. A method and system for detection and validation of Nocturia in the person has been provided. The system is utilizing a statistical based analysis, a rule based analysis, a machine learning based analysis and analysis of sleeping pattern of the person to detect and validate Nocturia. The system ensures that the person is not disturbed in his/her daily activities. Further, the processes deployed in the system are completely un-supervisory in nature meaning it does not have the dependency of needing to have trained machine learning dataset.

A detection device, a detection system and a detection method capable of detecting accurate position and orientation of a wearable device on a body are provided. A detection device includes a wireless communicator that receives orientation information indicating an orientation of a wearable device disposed on a body from the wearable device by wireless communication, measures an intensity of a radio wave radiated from the wearable device, and outputs intensity information indicating measured intensity of the radio wave; and a calculator that calculates a position and an orientation of the wearable device on the body based on the orientation information and the intensity information.