Intelligent system for multi-function electronic caregiving to facilitate advanced health diagnosis, health monitoring, fall and injury prediction, health maintenance and support, and emergency response
Inventors
Dohrmann, Anthony • Keeley, David W. • Salcido, Robert • Mitchell, James
Assignees
Interested in licensing this patent?
MTEC can help explore whether this patent might be available for licensing for your application.
Publication Number
US-10813572-B2
Publication Date
2020-10-27
Expiration Date
Abstract
A system for monitoring and detecting the gait and other health related parameters of a user. One such parameter is monitoring of medication compliance and treatment session attendance done by a medication and liquid dispensing apparatus, which combines mechanical dispensing of medication. These parameters are provided in standard of care summaries to care providers, and are continually reported by the Optimum Recognition Blueprint as Standard of Care Summaries to care providers, as well as communicated to the end-user by the Virtual Caregiver Interface.
Core Innovation
An Electronic Caregiver system is provided with a front-end network of sensing devices configured to capture data about a human, including a depth camera and other sensor devices. The system uses an Optimum Recognition Blueprint (ORB) to map device and user data to models for gait/fall detection, risk assessment, and actioning alerts to relevant parties.
In the context of fall detection, virtual movement markers are received from a depth camera, where a first data set indicates virtual movement markers comprising a cluster of data points in a shape of a body of the human. The virtual movement markers include a movement marker estimated to a head location, a movement marker estimated to a spine location, and a movement marker estimated to a joint location, and a second data set indicating volume in an area of a location of the human is also received.
Using the received movement marker data and activity/volume data, the virtual system detects rapid acceleration and rapid deceleration of at least two movement markers from an accelerometer, where at least one of the rapid acceleration and the rapid deceleration includes a rapid change in direction of at least one movement marker. The system then detects an irregular pattern of activity for the human from changes in the first data set of virtual movement markers and the second data set, and sends an alert indicating that the human has fallen to a reporting device.
Claims Coverage
The independent claim family element clm-00001 covers an automated method for fall detection and reporting via a virtual system using depth camera virtual movement markers, accelerometer-based detection of rapid acceleration/deceleration with direction change, irregular activity pattern detection, and sending an alert indicating a fall to a reporting device. The dependents primarily refine the alert destination path and specify processing using an optimum recognition blueprint.
Virtual movement markers from a depth camera
Receiving, at a processor in the virtual system, from a depth camera configured to be pointed at a human, a first data set of virtual movement markers comprising a cluster of data points in a shape of the human body; the first data set comprises a movement marker estimated to a head location, a movement marker estimated to a spine location, and a movement marker estimated to a joint location.
Volume-in-area data reception
Receiving, at the processor in the virtual system, from the depth camera a second data set indicating volume in an area of a location of the human.
Rapid acceleration/deceleration with direction change across movement markers
Detecting, at the processor in the virtual system, from an accelerometer, a rapid acceleration of at least two of the movement markers comprising the first data set, followed by a rapid deceleration of at least two of the movement markers comprising the first data set, wherein at least one of the rapid acceleration and the rapid deceleration includes a rapid change in direction of the location of at least one of the movement markers comprising the first data set.
Irregular activity pattern detection from marker and volume changes
Detecting, at the processor in the virtual system, an irregular pattern of activity for the human from changes in the first data set of virtual movement markers and the second data set.
Alert sending indicating a fall to a reporting device
Sending, at the processor in the virtual system, an alert to a reporting device indicating that the human has fallen based on the detected irregular pattern of activity.
Optimum recognition blueprint processing
Processing first and second data sets from the depth camera using an optimum recognition blueprint.
Monitoring central station communication for dispatching emergency services
Including a communication from the virtual system to a monitoring central station containing information used to dispatch local emergency services to the location of the human.
User computing device warning alert
Sending an alert from the virtual system to a user computing device to warn that the human has fallen.
Overall, the claim coverage centers on a virtual-system fall detection pipeline that receives depth-camera virtual movement markers and volume-in-area data, detects rapid acceleration/deceleration with direction change across at least two movement markers from accelerometer data, detects an irregular activity pattern using changes in the received datasets, and sends an alert indicating a fall to a reporting device; dependent elements refine whether the alert goes to a monitoring central station for dispatch or to a user computing device for warning, and further incorporate an optimum recognition blueprint.
Stated Advantages
Automated fall detection and reporting indicating that the human has fallen.
Alerting a reporting device based on detected irregular pattern of activity.
Generation of standard-of-care summaries for care providers.
Provision of alerts to end users.
Dispatch emergency services via a monitoring central station based on an alert.
Output of fall risk profiles using proprietary algorithms in a Comprehensive Falls Risk Screening Instrument (CFRSI).
Medication compliance tracking for a medication dispenser/organizer usage tracking context.
Documented Applications
Automated fall detection and reporting via a virtual system, including sending alerts based on irregular activity patterns.
Emergency-call/dispatch actions to a monitoring central station for dispatching emergency services to the location of the human.
Warning alerts to an end user via a user computing device.
Medication dispenser/organizer compliance tracking as part of an electronic caregiver system.
Comprehensive Falls Risk Screening Instrument (CFRSI) output of fall risk profiles using proprietary algorithms and additional sensor/history data.
Generation of standard-of-care summaries for care providers and alerts to end users.
Pharmacogenetic saliva sample kit shipment with lab reporting and a lab genetic screening report.
Interested in licensing this patent?