Mesh network stroke monitoring appliance

• US 7,558,622 B2
• Filed: 05/24/2006
• Issued: 07/07/2009
• Est. Priority Date: 05/12/2006
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Bao Tran
• Inventors: Tran, Bao
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): Gedeon, Brian T
• Application Number:
  US11/439,631
• Publication Number:
  US 20070276270A1
• Time in Patent Office: 1,140 Days
• Field of Search: 600/528, 600/509, 600/513
• US Class Current: 600/509
• CPC Class Codes: A61B 2505/01 Emergency care
• CPC Class Codes: A61B 2560/0214 of power generation or supply
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0468 Built-in electrodes
• 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 5/002 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 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/0295 using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
• CPC Class Codes: A61B 5/0537 Measuring body composition by impedance, e.g. tissue hydration or fat content
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1113 Local tracking of patients, e.g. in a hospital or private home
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• 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 5/112 : Gait analysis
• CPC Class Codes: A61B 5/1124 : Determining motor skills
• CPC Class Codes: A61B 5/1128 : using image analysis A61B5/1127 takes precedence
• CPC Class Codes: A61B 5/1176 : Recognition of faces
• CPC Class Codes: A61B 5/14532 : for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/224 : Measuring muscular strength
• CPC Class Codes: A61B 5/30 : Input circuits therefor
• 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 5/4023 : Evaluating sense of balance
• CPC Class Codes: A61B 5/4076 : Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/411 : Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/4519 : Muscles A61B5/389, A61B5/224 take precedence
• CPC Class Codes: A61B 5/4528 : Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61B 5/4803 : Speech analysis specially adapted for diagnostic purposes
• CPC Class Codes: A61B 5/4806 : Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/6816 : Ear lobe
• CPC Class Codes: A61B 5/6822 : Neck
• CPC Class Codes: A61B 5/6826 : Finger
• CPC Class Codes: A61B 5/6838 : Clamps or clips
• CPC Class Codes: A61B 5/6898 : Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7203 : for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7214 : using signal cancellation, e.g. based on input of two identical physiological sensors spaced apart, or based on two signals derived from the same sensor, for different optical wavelengths
• CPC Class Codes: A61B 5/7225 : Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/726 : using Wavelet transforms
• CPC Class Codes: A61B 5/7267 : involving training the classification device
• CPC Class Codes: A61B 5/7271 : Specific aspects of physiological measurement analysis A61B5/316, A61B5/349 and A61B5/374 take precedence
• CPC Class Codes: A61B 5/743 : Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7435 : Displaying user selection data, e.g. icons in a graphical user interface
• CPC Class Codes: A61B 5/7455 : characterised by tactile indication, e.g. vibration or electrical stimulation
• CPC Class Codes: A61B 5/7465 : Arrangements for interactive communication between patient and care services, e.g. by using a telephone network telemetry of measured physiological signal A61B5/0002
• CPC Class Codes: A61B 5/7475 : User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61B 8/0808 : for diagnosis of the brain
• CPC Class Codes: A61B 8/56 : Details of data transmission or power supply
• CPC Class Codes: A61B 8/565 : involving data transmission via a network
• CPC Class Codes: G16H 10/60 : for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/60 : relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 30/20 : for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/63 : for local operation
• 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

Abstract

A health care monitoring system for a person includes one or more wireless nodes forming a wireless mesh network; a wearable appliance having a sound transducer coupled to the wireless transceiver; and a heart attack or stroke attack sensor coupled to the wireless mesh network to communicate patient data over the wireless mesh network to detect a heart attack or a stroke attack.

Claims

1. A heart monitoring system for a patient, comprising:

one or more wireless nodes forming a wireless mesh network; and

a wearable appliance having a wireless transceiver adapted to communicate with the one or more wireless nodes; and

an analyzer to determine heart attack or stroke attack, the analyzer coupled to the wireless transceiver to communicate patient data over the wireless mesh network, wherein the analyzer detects weakness in left half and right half of patient body;

detects walking pattern for loss of balance or coordination;

asks user to move hands/feet in a predetermined pattern and read accelerometer output in accordance with predetermined pattern;

checks whether the person experienced dizziness or headache;

displays a text image and asks the person to read back the text image one eye at a time;

or uses a speech recognizer to detect confusion, trouble speaking or understanding and asks the person if numbness is felt in the body.

2. The system of claim 1, wherein the analyzer comprises one of:

a differential amplifier, an accelerometer.

3. The system of claim 1, comprising a sound transducer coupled to the wireless transceiver to communicate audio over a plain old telephone service (POTS) network and a public switched telephone network (PSTN) network through the mesh network.

4. The system of claim 1, comprising one of:

an EMG detector, EEG detector, an EKG detector, an ECG detector, an electromagnetic detector, an ultrasonic detector, an optical detector, a Hidden Markov Model (HMM) recognizer, a dynamic time warp (DTW) recognizer, a neural network, a fuzzy logic engine, a Bayesian network.

5. The system of claim 1, wherein the appliance monitors patient movement.

6. The system of claim 1, comprising an in-door positioning system coupled to one or more mesh network appliances to provide location information.

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

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

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

12. The system of claim 1, wherein the appliance captures bioelectric impedance (BI) 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, hypoyolemia, hemorrhage, blood loss, heart attack, stroke attack.

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

14. The system of claim 1, wherein the appliance transmits and receives voice from the person over the mesh 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, 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, comprising:

one or more cameras positioned to capture three dimensional (3D) video of the patient;

a server coupled to the one or more cameras, the server executing code to detect a dangerous condition for the patient based on the 3D video and allow a remote third party to view images of the patient when the dangerous condition is detected; and

an analyzer that detects weakness in left half and right half of patient body;

detects walking pattern for loss of balance or coordination;

asks user to move hands/feet in a predetermined pattern and read accelerometer output in accordance with predetermined pattern;

checks whether the person experienced dizziness or headache;

displays a text image and asks the person to read back the text image one eye at a time;

or uses a speech recognizer to detect confusion, trouble speaking or understanding and asks the person if numbness is felt in the body.

19. A monitoring system for a person, comprising:

one or more wireless nodes;

a electromyography (EMG) sensor coupled to the person to determine a stroke attack, the EMG sensor coupled to the wireless nodes to transmit patient data; and

an analyzer that detects weakness in left half and right half of patient body;

detects walking pattern for loss of balance or coordination;

asks user to move hands/feet in a predetermined pattern and read accelerometer output in accordance with predetermined pattern;

checks whether the person experienced dizziness or headache;

displays a text image and asks the person to read back the text image one eye at a time;

or uses a speech recognizer to detect confusion, trouble speaking or understanding and asks the person if numbness is felt in the body.