Personal emergency response appliance

• US 8,525,673 B2
• Filed: 04/29/2010
• Issued: 09/03/2013
• Est. Priority Date: 06/30/2006
• Status: Active Grant

• Current Assignee: BT Wearables LLC (Empire IP LLC)
• Original Assignee: Bao Tran
• Inventors: Tran, Bao
• Primary Examiner(s): POPE, DARYL C
• Application Number:
  US12/770,553
• Publication Number:
  US 20110115624A1
• Time in Patent Office: 1,223 Days
• Field of Search: 340/506, 340/3.1, 340/539.1, 340/539.13, 340/540
• US Class Current: 340/540
• 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 5/384 : Recording apparatus or displays specially adapted therefor
• CPC Class Codes: A61B 5/389 : Electromyography [EMG]
• CPC Class Codes: A61B 5/395 : Details of stimulation, e.g. nerve stimulation to elicit EMG response
• 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
• 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 monitoring system includes one or more wireless nodes forming a wireless mesh network; a user activity sensor including a wireless mesh transceiver adapted to communicate with the one or more wireless nodes using the wireless mesh network; and a digital monitoring agent coupled to the wireless transceiver through the wireless mesh network to request assistance from a third party based on the user activity sensor.

Claims

1. A system, comprising:

one or more wireless nodes forming a wireless network;

a user activity sensor including an accelerometer and a wireless transceiver adapted to communicate with the one or more wireless nodes using the wireless network; and

a processor analyzing accelerometer data and coupled to the wireless transceiver to request assistance from a third party based on the user activity sensor by distinguishing between falls and other types of normal body movement, the processor initiating a telephone call seeking assistance for the user if the user pushes a help button or if the processor detects a dangerous condition, and wherein sequences of human motions are classified into groups of similar postures represented by model-states with a posture model depicting inter-relationships among model-states.

2. The system of claim 1, wherein the user activity sensor comprises one of:

an indoor position sensor, a motion sensor, a door sensor, a bathroom sensor, a water overflow sensor, an exercise equipment sensor, a smoke detector, an oven sensor, a cooking range sensor, a dish washer sensor, a cabinet door sensor, a refrigerator sensor, a refrigerator container sensor, a kitchen water flow sensor, a dish sensor, a bowl sensor, a chair sitting sensor, a sofa sitting sensor, a bed sensor, a weight sensor, a television viewing sensor, a radio listening sensor, an EMG detector, EEG detector, an EKG detector, an ECG detector, a bioimpedance sensor, an electromagnetic detector, an ultrasonic detector, an optical detector, a differential amplifier, an accelerometer, a video camera, a sound transducer, a digital stethoscope.

3. The system of claim 1, wherein the processor comprises one of:

a Hidden Markov Model (HMM) recognizer, a dynamic time warp (DTW) recognizer, a neural network, a fuzzy logic engine, a Bayesian network, an expert system, a rule-driven system.

4. The system of claim 1, wherein the processor monitors user activity without requiring the sensor to be worn on the body.

5. The system of claim 1, wherein the processor monitors cooking appliances for a hazardous condition and shuts down the appliances using the wireless network.

6. The system of claim 1, comprising an in-door positioning system to provide location information.

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

8. The system of claim 1, comprising a base station coupled to the wireless network and to the plain old telephone service (POTS) to provide information to an authorized remote user.

9. The system of claim 1, comprising a wireless router coupled to the network and wherein the wireless router comprises one of:

802.11 router, 802.16 router, WiFi router, WiMAX router, Bluetooth router, X10 router.

10. The system of claim 1, comprising a network appliance coupled to a power line to communicate X10 data to and from the network.

11. The system of claim 1, wherein the processor transmits and receives voice from the person over the network.

12. The system of claim 1, comprising a bioimpedance sensor, wherein bioimpedance data is used to determine one of:

total body water, compartmentalization of body fluids, cardiac monitoring, blood flow, skinfold thickness, dehydration, blood loss, wound monitoring, ulcer detection, deep vein thrombosis, hypovolemia, hemorrhage, blood loss, heart attack, stroke attack.

13. The system of claim 1, comprising a patch having a BI or EKG sensor in communication with the wireless transceiver.

14. The system of claim 1, wherein the processor transmits and receives voice from the person over the network to one of:

a doctor, a nurse, a medical assistant, a caregiver, an emergency response unit, a family member.

15. The system of claim 1, comprising code to store and analyze patient information.

16. The system of claim 15, wherein the patient information includes medicine taking habits, television viewing habits, radio listening habits, eating and drinking habits, sleeping habits, or excise habits.

17. The system of claim 1, comprising a housing having one or more bioelectric contacts coupleable to the patient, the housing selected from one of:

a patch, a wristwatch, a band, a wristband, a chest band, a leg band, a sock, a glove, a foot pad, a head-band, an ear-clip, an ear phone, a shower-cap, an armband, an ear-ring, eye-glasses, sun-glasses, a belt, a sock, a shirt, a garment, a jewelry, a bed spread, a pillow cover, a pillow, a mattress, a blanket, each having one or more sensors in communication with the wireless mesh network.

18. The system of claim 1,

wherein the processor receives location data from a positioning system or from of wireless base station location data.

19. A method to monitor a person, comprising:

capturing and transmitting the person'"'"'s daily activities over a wireless network;

determining a pattern associated with the person'"'"'s daily activities using a statistical recognizer to distinguish between falls and other types of normal body movement, including extracting features from body signature sequences representing one or more motion types and matching a sequence of motions corresponding to the one or more motion types; and

requesting assistance with a telephone call if the person'"'"'s current activity varies from the pattern or if a dangerous condition is detected or if the user manually requests assistance, and wherein sequences of human motions are classified into groups of similar postures represented by model-states with a posture model depicting inter-relationships among model-states.

20. The method of claim 19, comprising attaching a housing having one or more bioelectric contacts coupleable to the person, the housing selected from one of:

a patch, a wristwatch, a band, a wristband, a chest band, a leg band, a sock, a glove, a foot pad, a head-band, an ear-clip, an ear phone, a shower-cap, an armband, an ear-ring, eye-glasses, sun-glasses, a belt, a sock, a shirt, a garment, a jewelry, a bed spread, a pillow cover, a pillow, a mattress, a blanket, each having one or more sensors in communication with the wireless network.

21. A method to monitor a person, comprising:

capturing and transmitting the person'"'"'s daily activities over a wireless network;

determining a pattern associated with the person'"'"'s daily activities using a statistical recognizer to

distinguish between falls and other types of normal body movement; and

requesting assistance if the person'"'"'s current activity varies from the pattern or if a dangerous condition is detected; and

detecting a weakness in left half and right half of the person'"'"'s body;

a walking pattern for loss of balance or coordination;

requesting hands/feet movement in a predetermined pattern and reading accelerometer output in accordance with the predetermined pattern;

checking whether the person experienced dizziness or headache;

displaying a text image and asking the person to read back the text image one eye at a time;

using a speech recognizer to detect confusion, trouble speaking or understanding; and

/or asking the person if numbness is felt in the body.