IPC분류정보
국가/구분 |
United States(US) Patent
등록
|
국제특허분류(IPC7판) |
|
출원번호 |
US-0770553
(2010-04-29)
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등록번호 |
US-8525673
(2013-09-03)
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발명자
/ 주소 |
|
출원인 / 주소 |
|
대리인 / 주소 |
|
인용정보 |
피인용 횟수 :
20 인용 특허 :
187 |
초록
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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 tra
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.
대표청구항
▼
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; anda processor analyzing accelerometer data and coupled t
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; anda 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; andrequesting 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 todistinguish between falls and other types of normal body movement; andrequesting assistance if the person's current activity varies from the pattern or if a dangerous condition is detected; anddetecting 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.
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