Personal emergency response (PER) system

• US 9,204,796 B2
• Filed: 07/27/2013
• Issued: 12/08/2015
• Est. Priority Date: 06/30/2006
• Status: Active Grant

• Current Assignee: BT Wearables LLC (Empire IP LLC)
• Original Assignee: Empire IP LLC
• Inventors: Tran, Bao
• Primary Examiner(s): POPE, DARYL C
• Application Number:
  US13/952,607
• Publication Number:
  US 20140077946A1
• Time in Patent Office: 864 Days
• Field of Search: 340/506, 340/3.1, 340/539.1, 340/539.11, 340/539.13, 340/573.6
• US Class Current: 1/1
• 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 system includes one or more sensors to detect activities of a mobile object; and a processor coupled to the sensor and the wireless transceiver to classify sequences of motions into groups of similar postures each represented by a model and to apply the models to identify an activity of the object.

Claims

1. A system, comprising:

one or more sensors to detect movement of a mobile object; and

a processor coupled to the one or more sensors and a wireless transceiver to classify sequences of movements of the mobile object into groups of similar postures represented by a model and to apply the model to identify an activity of the mobile object,

wherein the processor identifies each elemental motion of a sequence of elemental motions of the mobile object, and identifies the activity of the mobile object by matching the sequence of identified elemental motions with one or more stored sequences of elemental motions, wherein each stored sequence of elemental motions corresponds with an activity.

2. The system of claim 1, wherein the identification of each elemental motion comprises code for:

generating an acceleration signature based on sensed acceleration of the one or more sensors;

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 one or more sensors based on the matching of the acceleration signature with the stored acceleration signature.

3. The system of claim 1, further comprising computer readable code for refining identification of the activity by analyzing timing of the identified activity, by analyzing at least one identified location of the identified activity, by analyzing a rate of change of a location of the object, or by analyzing an age of the object.

4. The system of claim 1, further comprising computer readable code for identifying a behavior of the object by matching the sequence of identified activities of the object with a stored sequence of activities, wherein each stored sequence of activities corresponds with an identified behavior.

5. The system of claim 1, further comprising computer readable code tracking at least one behavior of the object over time.

6. The system of claim 1, wherein the stored acceleration signatures are useable for matching acceleration signatures of motions of multiple humans, and the stored acceleration signatures are useable for matching acceleration signatures of motions of a particular human.

7. The system of claim 1, wherein the processor automatically notifies a third party for assistance upon detecting the fall without a user pressing a button to call for help.

8. The system of claim 1, wherein the processor captures movement activities and comparing the movement activities to fall patterns.

9. The system of claim 1, wherein the processor determines an in-door position of the patient using triangulation of signals between the wireless transceiver and a remote station.

10. The system of claim 1, wherein the processor waits for a predetermined period to detect if the patient can recover from the fall and automatically requests assistance if the patient is unable to recover from the fall.

11. The system of claim 1, comprising a call center coupled to the processor to provide a human response.

12. The system of claim 1, wherein the processor detects a gradual slide from a seated position.

13. The system of claim 1, wherein the processor detects a position of the mobile object using a global positioning system and/or geolocation data.

14. The system of claim 1, wherein the processor automatically alerts a monitoring center.

15. The system of claim 14, wherein the object is a patient and wherein the processor transfers voice data between the patient and the monitoring center.

16. The system of claim 1, wherein the processor plays an audio reminder at a predetermined time to take medication.

17. The system of claim 1, wherein the object is a patient and wherein the sensor is worn on the patient'"'"'s neck.

18. The system of claim 1, wherein the sensor is an accelerometer and wherein the processor detects the position of the mobile object using a global positioning system and WiFi geolocation data.

19. The system of claim 1, wherein the processor detects activities of daily life.

20. The system of claim 1, comprising a plurality of sensors coupled to the processor and wherein the sensors measure one or more of:

height, orientation and acceleration.