PERSONAL EMERGENCY RESPONSE (PER) SYSTEM

• US 20120092156A1
• Filed: 12/28/2011
• Published: 04/19/2012
• Est. Priority Date: 10/16/2005
• Status: Active Grant

• Current Assignee: BT Wearables LLC (Empire IP LLC)
• Original Assignee: Bao Tran
• Inventors: Tran, Bao
• Granted Patent: US 8,461,988 B2
• Time in Patent Office: Days
• US Class Current: 340/539.12
• CPC Class Codes: A43B 3/42 where power is generated by conversion of mechanical movement to electricity, e.g. by piezoelectric means
• CPC Class Codes: A43B 3/46 Global positioning system [GPS] sensors
• CPC Class Codes: A43B 3/48 with transmitting devices, e.g. GSM or Wi-Fi®
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0008 Temperature signals
• CPC Class Codes: A61B 5/0013 Medical image data A61B1/00011, A61B6/56, A61B8/56 take precedence
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0077 Devices for viewing the surface of the body, e.g. camera, magnifying lens
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 : Electromyography [EMG]
• CPC Class Codes: A61B 5/6803 : Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/6806 : Gloves
• CPC Class Codes: A61B 5/6807 : Footwear
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 : Arm or wrist
• CPC Class Codes: A61B 5/6826 : Finger
• CPC Class Codes: A61B 5/6891 : Furniture
• CPC Class Codes: A61B 5/7264 : Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 7/00 : Instruments for auscultation
• CPC Class Codes: A61B 7/04 : Electric stethoscopes microphones, acoustic transducers therefor H04R
• CPC Class Codes: A61B 7/045 : Detection of Korotkoff sounds A61B5/0225 takes precedence; measuring blood pressure A61B5/021
• CPC Class Codes: A61B 8/00 : Diagnosis using ultrasonic, sonic or infrasonic waves imaging of objects using sonar G01S15/00
• CPC Class Codes: A61B 8/06 : Measuring blood flow measuring volume flow in general G01F, e.g. G01F1/66, G01F1/72; measuring speed of fluids in general G01P5/00
• CPC Class Codes: A61B 8/0808 : for diagnosis of the brain
• CPC Class Codes: A61B 8/488 : involving Doppler signals
• CPC Class Codes: A61B 8/565 : involving data transmission via a network
• CPC Class Codes: G08B 21/02 : Alarms for ensuring the safety of persons
• CPC Class Codes: G08B 21/0423 : detecting deviation from an expected pattern of behaviour or schedule
• 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: G08B 21/0453 : worn on the body to detect health condition by physiological monitoring, e.g. electrocardiogram, temperature, breathing detecting, measuring or recording for diagnostic purposes A61B5/00
• CPC Class Codes: G08B 21/0461 : integrated or attached to an item closely associated with the person but not worn by the person, e.g. chair, walking stick, bed sensor
• CPC Class Codes: G08B 21/0476 : Cameras to detect unsafe condition, e.g. video cameras
• CPC Class Codes: G08B 21/0484 : Arrangements monitoring consumption of a utility or use of an appliance which consumes a utility to detect unsafe condition, e.g. metering of water, gas or electricity, use of taps, toilet flush, gas stove or electric kettle
• CPC Class Codes: G08B 21/0492 : Sensor dual technology, i.e. two or more technologies collaborate to extract unsafe condition, e.g. video tracking and RFID tracking
• CPC Class Codes: G08B 25/016 : Personal emergency signalling and security systems emergency non-personal manually actuated alarm activators G08B25/12
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/13 : delivered from dispensers
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 80/00 : ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: G16Z 99/00 : Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: H04M 2250/12 : including a sensor for measuring a physical value, e.g. temperature or motion telephones including GPS signal receivers H04M2250/10
• CPC Class Codes: H04M 3/5116 : for emergency applications
• CPC Class Codes: H04W 84/18 : Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

A method of automatically requesting assistance for a patient includes wearing a wireless device with one or more accelerometers on the patient to detect patient motion; determining a fall based on detected motions; and automatically requesting assistance for the patient if needed.

Claims

1. A method of automatically requesting assistance for a patient, comprising:

wearing a wireless device with one or more accelerometers on the patient to detect patient motion;

determining a fall based on detected patient motion; and

automatically requesting assistance for the patient if needed.

2. The method of claim 1, comprising detecting if the patient has fallen based on a plurality of accelerometer signals and indicating the fall if the accelerometer signals indicate that the patient is unable to get up.

3. The method of claim 1, comprising estimating an indoor location of the wireless device based on detection of local wireless signals.

4. The method of claim 1, comprising distinguishing between falls and other types of normal body movement.

5. The method of claim 1, comprising notifying an emergency service for assistance automatically without a user pressing a button to call for help.

6. The method of claim 1, comprising reading outputs of one or more accelerometers in the wireless device to detect the fall and calling for assistance using the wireless device.

7. The method of claim 1, comprising detecting a fall, sending an alert to a call center which contacts the patient to confirm if a responder can assist and sending local emergency services if needed.

9. The method of claim 1, comprising capturing movement activities and comparing the movement activities to one or more fall patterns and determining if a fall has occurred.

10. The method of claim 1, comprising detecting the fall by analyzing changes in height and accelerations associated with the changes in height.

11. The method of claim 1, comprising confirming the fall by having a call center contact the patient using the wireless device and requesting help if needed.

12. The system of claim 1, wherein the wireless device sends accelerometer patterns to a remote processor to detect falls to conserve battery power.

13. The method of claim 1, wherein patient motions form a sequence of elemental motions, comprising:

identifying each elemental motion of a sequence of elemental motions of the accelerometer; and

identifying the activity of the patient, comprising matching the sequence of identified elemental motions with a library of stored sequences of elemental motions, wherein each stored sequence of elemental motions corresponds with an activity.

14. The method of claim 1, comprising identifying each elemental motion by:

generating an acceleration signature based on sensed acceleration of the device;

matching the acceleration signature with at least one of a plurality of stored acceleration signatures, wherein each stored acceleration signatures corresponds with a type of motion;

identifying the type of motion of the device based on the matching of the acceleration signature with the stored acceleration signature.

15. The method of claim 1, further comprising refining identification of the activity, comprising analyzing timing of the identified activity, analyzing at least one identified location of the identified activity, analyzing a rate of change of a location of the patient, or analyzing patterns of a plurality of identified activities.

16. The method of claim 1, further comprising determining changes in height of the wireless device.

17. The method of claim 1, further comprising determining acceleration of movements from a fall.

18. The method of claim 1, further comprising

determining if the patient has fallen based on a plurality of sensor signals indicating changes in height or accelerations associated with the changes in height;

waiting for a predetermined period to detect if the patient can independently recover from the fall; and

requesting assistance if the sensor signals indicate that the patient is unable to independently recover from the fall.

19. The method of claim 1, further comprising determining a predetermined time between the fall and when the patient gets up.

20. The method of claim 19, further comprising determining a severity of the fall based on the predetermined time or based on one or more accelerometers'"'"' output magnitudes.

21. The method of claim 1, further comprising determining the fall based on acceleration pattern characteristics of a fall.

22. A method to provide personal emergency response for a patient, comprising:

wearing a wireless device with at least one or more accelerometers on the patient to detect patient motion;

determining a fall based on detected motions including one or more changes in height or one or more accelerations associated with movements by the patient;

waiting for a predetermined period to detect if the patient can recover from the fall and automatically requesting assistance if the patient is unable to recover from the fall; and

requesting assistance for the patient if the patient pushes a button requesting assistance.

23. The method of claim 22, comprising calling the patient to determine if the patient needs assistance and requesting help if the patient fails to respond to the call.

24. The method of claim 22, further comprising determining a severity of the fall based on the predetermined period or based on one or more accelerometers'"'"' output magnitudes.

25. The method of claim 22, further comprising determining the fall based on acceleration pattern characteristics of a fall.