REMOTE MONITORING SYSTEM AND RELATED METHODS
First Claim
1. A remote monitoring system for monitoring a person in a location comprising:
- at least one body-worn sensor and at least one object-mounted sensor, the body-worn sensor and object-mounted sensor configured to detect information related to a status of the person and an object in the person'"'"'s location;
a gateway configured to receive and transmit data based on the detected information from the at least one body-worn sensor and object-mounted sensor; and
a cloud computing system comprising a server for receiving and processing the data from the gateway, the cloud computing system having an analytics engine using algorithms for analyzing a plurality of abnormal activities relative to a plurality of activity patterns of the person using a coupled hidden Markov model (HMM), wherein at least one of the plurality of activity patterns further comprises an activity signal pattern of the person and the object during an interaction of the person with the object, wherein the cloud computing system initiates an action based on the received data.
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Accused Products
Abstract
This disclosure relates to a system and methods for monitoring a person or animal remotely. The monitored person may be an elderly person, disabled person, or other person who may experience some difficulty or risks in living alone, or an animal. The system and methods use sensors that may be worn by the person or animal or attached to objects in the person'"'"'s or animal'"'"'s location to monitor the status of the person or animal and the objects. In response to certain information detected by the sensors, the system or methods may provide for notifying other individuals, including the person'"'"'s family, friends or emergency response personnel or caretaker, that the person or animal needs assistance.
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Citations
20 Claims
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1. A remote monitoring system for monitoring a person in a location comprising:
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at least one body-worn sensor and at least one object-mounted sensor, the body-worn sensor and object-mounted sensor configured to detect information related to a status of the person and an object in the person'"'"'s location; a gateway configured to receive and transmit data based on the detected information from the at least one body-worn sensor and object-mounted sensor; and a cloud computing system comprising a server for receiving and processing the data from the gateway, the cloud computing system having an analytics engine using algorithms for analyzing a plurality of abnormal activities relative to a plurality of activity patterns of the person using a coupled hidden Markov model (HMM), wherein at least one of the plurality of activity patterns further comprises an activity signal pattern of the person and the object during an interaction of the person with the object, wherein the cloud computing system initiates an action based on the received data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of remotely monitoring a person comprising:
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detecting information related to the status of a person and at least one object in the person'"'"'s location with at least one body-worn sensor and at least one object-mounted sensor located in the person'"'"'s location; transmitting data based on the detected information to a gateway, wherein the gateway forwards the data based on the detected information to a cloud computing system; and receiving and processing the data based on the detected information from the gateway by a cloud computing system comprising a server and an analytics engine by analyzing a plurality of abnormal activities relative to a plurality of activity patterns of the person using a coupled hidden Markov model (HMM), wherein at least one of the plurality of activity patterns further comprises an activity signal pattern of the person and the object during an interaction of the person with the object. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. A method of remotely monitoring an activity of a person, the method comprising:
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receiving sensed data from at least one body-worn, three-axis accelerometer carried on a body of the person; receiving sensed data from an object-mounted sensor connected to an object in a proximate location to the person; and analyzing the sensed data from a body-worn, three-axis accelerometer and the object-mounted sensor with a coupled hidden Markov model (HMM) by; calibrating an orientation of the body-worn sensor on the person'"'"'s body by identifying orthogonal vectors representing anteroposterior (AP) and vertical (VT) axes and calculating a mediolateral (ML) axis by calculating a cross product of the AP and VT axes; converting the sensed data from the body-worn, three-axis accelerometer into AP, ML, and VT human accelerations; and classifying the AP, ML, and VT human accelerations with at least one classification algorithm to yield a classification result.
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Specification