Comprehensive monitoring system

• US 7,394,385 B2
• Filed: 08/02/2004
• Issued: 07/01/2008
• Est. Priority Date: 07/31/2003
• Status: Expired due to Fees

• Current Assignee: Wellcare Systems Incorporated
• Original Assignee: Wellcare Systems Incorporated
• Inventors: DiMario, William G., Franco, Thomas S. Jr.
• Primary Examiner(s): TRIEU, VAN THANH
• Application Number:
  US10/910,263
• Publication Number:
  US 20050093709A1
• Time in Patent Office: 1,429 Days
• Field of Search: 340/573.1, 340/573.4, 340/573.7, 340/539.11, 340/539.12, 340/539.13, 340/539.16, 340/539.17, 340/539.24, 340/669, 340/689, 600/300, 600/549, 702/150, 702/151
• US Class Current: 340/573.1
• CPC Class Codes: A61B 2503/08 Elderly
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: G08B 21/0446 worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A monitoring system for physically challenged clients can have a base hub unit, one or more sensor units, one or more repeater units, and a mobile unit for a client to wear in a residential setting. In an institutional setting, a mobile repeater can be used for monitoring outside premises. A three-axis accelerometer can be used to detect falls and to monitor for other life activities, such as sleeping.

Claims

1. A client monitoring method comprising:

using three-axis data from one or more accelerometers in a client-carried device mounted on a wrist of a client to determine if a client has fallen;

computing an approximate velocity of the one or more accelerometers; and

comparing the resulting approximate velocity to a threshold value wherein a damping factor is applied to the resulting approximate velocity when the resulting approximate velocity is less than the threshold value and wherein a more accurate velocity of the one or more accelerometers is calculated when the resulting approximate velocity is more than the threshold value.

2. The method of claim 1 wherein said comparing step includes applying a damping factor that has an antialiasing and median filtering applied to the resulting approximate velocity.

3. The method of claim 1 wherein said computing step includes integrating the difference between a 1 G normal force and an acceleration that opposes the normal force over a pre-determined period of time.

4. The method of claim 1 wherein said comparing step includes using higher bandwidth data that has been high-pass filtered to remove a static acceleration component when the more accurate velocity of the one or more accelerometers is calculated.

5. The method of claim 4 wherein said comparing step includes integrating the x, y and z axis acceleration of the one or more accelerometers over a pre-determined period of time when the more accurate velocity is calculated.

6. The method of claim 4 wherein the pre-determined time period is about 500 milliseconds to about 750 milliseconds.

7. The method of claim 1 further comprising providing position information to enable the determination of the location of the client.

8. The method of claim 7 wherein the providing position information step includes using a received signal strength indication that detects the signal strength to determine where the client is located and whether the client is moving.

9. The method of claim 1 further comprising using the data from the one or more accelerometers to determine information about one or more life activities other than falling.

10. The method of claim 9 further comprising comparing current accelerometer data with historic accelerometer data to determine if there is a possible wellness problem.

11. A monitoring system for monitoring a patient in a monitoring region, the system comprising:

a mobile device with one or more accelerometers capable of providing three-axis data for detecting an acceleration by a patient when worn by a patient on the wrist wherein an algorithm uses the three-axis data to compute an approximate velocity of the one or more accelerometers and compare the approximate velocity to a threshold value wherein a damping factor is applied to the resulting approximate velocity when the resulting approximate velocity is less than the threshold value and wherein a more accurate velocity of the one or more accelerometers is calculated when the resulting approximate velocity is more than the threshold value;

at least one sensor node disposed in a fixed geographical location within said monitoring region for detecting a physical condition in the monitoring region;

a repeater node for transmitting signals from at least one of the mobile device and the at least one sensor node; and

a hub node for receiving signals from the repeater node.

12. The system of claim 11 wherein the physical condition includes one of an ambient condition or a condition of a device in said monitoring region.

13. The system of claim 12 wherein the device includes one of a home appliance, a door, a toilet, a faucet, a heater, and an air conditioner and the ambient condition includes one of temperature and humidity.

14. The system of claim 11 wherein the hub node is capable of transmitting data to a location remote from the monitoring region.

15. A client monitoring method for determining a fall event, the method comprising:

using three-axis data from one or more accelerometers contained within a client-carried device to determine if a client has fallen;

measuring a duration of the fall event;

measuring an impact magnitude of the fall event; and

calculating a fall velocity of the fall event;

computing an approximate velocity of the one or more accelerometers; and

comparing the resulting approximate velocity to a threshold value wherein a damping factor is applied to the resulting approximate velocity when the resulting approximate velocity is less than the threshold value and wherein a more accurate velocity of the one or more accelerometers is calculated when the resulting approximate velocity is more than the threshold value.

16. The method of claim 15 further comprising measuring a recovery motion after the fall event.

17. The method of claim 15 wherein said comparing step includes applying a damping factor that has an antialiasing filtering and a median filtering applied to the resulting approximate velocity.

18. The method of claim 15 wherein said comparing step includes using higher bandwidth data that has been high-pass filtered to remove a static acceleration component when the more accurate velocity of the one or more accelerometers is calculated.

19. The method of claim 18 wherein said comparing step includes integrating the x, y and z axis acceleration of the one or more accelerometers over a pre-determined period of time when the more accurate velocity is calculated.