WO2016095875A1 - Intelligent sensor network and a method of automatic classification of physical activity of the user of the intelligent sensor network - Google Patents

Intelligent sensor network and a method of automatic classification of physical activity of the user of the intelligent sensor network Download PDF

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Publication number
WO2016095875A1
WO2016095875A1 PCT/CZ2014/000161 CZ2014000161W WO2016095875A1 WO 2016095875 A1 WO2016095875 A1 WO 2016095875A1 CZ 2014000161 W CZ2014000161 W CZ 2014000161W WO 2016095875 A1 WO2016095875 A1 WO 2016095875A1
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WO
WIPO (PCT)
Prior art keywords
user
sensor network
intelligent sensor
block
peripheral
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Application number
PCT/CZ2014/000161
Other languages
French (fr)
Inventor
Jan Kaspar
Karel Hana
Jan Muzik
Pavel Smrcka
Miroslav MUZNY
David GILLAR
Adam BOHUNCAK
Original Assignee
Univerzita Karlova V Praze
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
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Priority to PCT/CZ2014/000161 priority Critical patent/WO2016095875A1/en
Publication of WO2016095875A1 publication Critical patent/WO2016095875A1/en

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Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation

Definitions

  • Intelligent sensor network and a method of automatic classification of physical activity of the user of the intelligent sensor network
  • the invention relates to an intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user, comprising a set of sensors and at least one user's peripheral while the sensors are interconnected with the central server via the user's peripheral, the server being equipped with a block for sending feedback.
  • the invention further relates to a method of automatic classification of physical activity of the user of such an intelligent sensor network.
  • Remote health condition monitoring sometimes referred to as telemedicine, is commonly well-known, including relatively complex and expensive systems for such monitoring.
  • Such systems are described e.g. by the patents US5375604, US5441047 or the published application US2002115916.
  • Well-known commercially available systems for remote monitoring of the health condition of individual users generally consist of a single-purpose device for monitoring one or a few values, e.g. the pulse, blood pressure etc. These known systems are not suitable for comprehensive monitoring of the health condition and do not have comprehensive feedback that would make it possible to send comprehensive recommendations to the user based on the set of established values.
  • the Czech utility model no. 25375 discloses a health condition remote monitoring system that comprises a set of sensing devices connected to the central server with transmission channels, the server being fitted with a block for processing the measured values while at least one user's peripheral device is connected to the central server.
  • a health condition remote monitoring system that comprises a set of sensing devices connected to the central server with transmission channels, the server being fitted with a block for processing the measured values while at least one user's peripheral device is connected to the central server.
  • an interface is installed for the connection of a set of sensing devices with a different design while the block for processing the measured values is connected to a database of limit values and algorithms and a block for user communication connected to the user's peripheral with transmission channels is connected to the block for processing the measured values.
  • sports-testers which can measure the speed, distances and pulse during jogging, cycling, swimming etc.
  • the data of some devices can be loaded to a computer where the user can keep a training logbook.
  • the goal of the invention is to design such equipment that would be able to automatically recognize the type of the conducted activity.
  • an intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user comprising a set of sensors and at least one user's peripheral while the sensors are interconnected, via the user's peripheral, with a central server that is equipped with a block for sending feedback according to the invention the principle of which is that the central server is interconnected with a social network server and the central server is equipped with a block for automatic monitoring of the user's electronic communication.
  • the central server is further equipped with a block for automatic classification of the user's physical activity based on the output of the block for automatic monitoring of the user's electronic communication.
  • An advantage of the automatic sensor network in accordance with the invention is that it makes it possible to automatically classify the currently conducted physical activity of the user (jogging, cycling, skiing, swimming etc.) based on characteristic information of the user's place and/or time of stay and/or activity obtained through monitoring of the user's electronic communication on social network servers.
  • the block for automatic monitoring of the user's electronic communication is interconnected with the user's peripheral so characteristic information about the user's place and/or time of stay and/or activity is obtained not only by monitoring of the user's electronic communication on social network servers, but also the other electronic communication of the user (SMS, MMS, e-mail, etc.)
  • the sensors comprise a sphygmomanometer and/or pedometer and/or bio-impedance scale and/or glucose meter and/or accelerometer and/or gyroscope and/or GPS sensor and/or NFC sensor.
  • the sensors may be attached to the user's body and/or to the user's clothing and/or installed in the user's place of residence.
  • the block for sending feedback is interconnected with the user's peripheral and/or with a physician's peripheral and/or with a fitness coach's peripheral and or a nutrition consultant's peripheral.
  • this electronic communication is used to obtain characteristic information about the place and/or time of stay and/or activity of the user and the automatic classification of the user's physical activity is done by assignment of the obtained characteristic information to the output of the sensors of the intelligent sensor network.
  • the intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user will be described in a more detailed way using a particular embodiment example, shown schematically in fig. 1.
  • the example of an embodiment of the intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user is intended for a diabetic and comprises three sensors 1 , which are a DEXCOM G4 glucose meter for continuous measurement of the blood sugar level, a "smart" Flex-fitbit wristband where a pedometer, accelerometer and gyroscope for monitoring the physical activity and energy output of the user are integrated and a "smart" watch for entering more user data, especially data about the energy value of consumed food.
  • the intelligent sensor network further comprises the user's peripheral 2, which is a LG Nexus 5 smartphone in the described embodiment example.
  • the user's peripheral 2 fulfils the function of a data collection and transmission device among other things.
  • the sensors 1 are interconnected with the central server 3 via the user's peripheral 2 by means of a GSM or WiFi interface, the server 3 being represented by an Intel NUC mini-computer with an integrated CPU, RAM, data storage and communication interface in this particular case.
  • the central server 3 is equipped with a block 4 for sending feedback, which is in this particular embodiment example a programmable block in the Intel NUC minicomputer, which contains an input interface (LAN Ethernet Internet interface, wireless LAN WiFi) and an output interface (LAN Ethernet internet interface, wireless LAN WiFi GSM gate for sending SMS and MMS) and which processes input data (MMS, SMS, e-mail, social network messages) and output data (MMS, SMS, e-mail, social network messages).
  • the central server 3 is interconnected with a social network server 6 consisting of a cloud server.
  • a social network server 6 consisting of a cloud server.
  • fig. 1 shows one social network server 6, but the intelligent sensor network is actually interconnected with any number of known servers of social networks as Facebook, Twitter, instagram etc.
  • the central server 3 is equipped with a block 7 for automatic monitoring of the user's electronic communication through the social network server 6 and the user's peripheral 2.
  • the user's electronic communication refers to any electronic communication of the user through the social network server 6 and the user's peripheral 2(MMS, SMS, e-mail, social network messages).
  • the block 7 for automatic monitoring of the user's electronic communication consists of a programmable block in the Intel NUC minicomputer, which contains an input interface (LAN Ethernet Internet interface, wireless LAN WiFi, a GSM gate for receiving SMS and MMS) and an output interface (LAN Ethernet Internet interface, wireless LAN WiFi GSM gate for sending SMS and MMS) and which processes input data (MMS, SMS, e-mail, social network messages) and output data (MMS, SMS, e-mail, social network messages).
  • the central server 3 is further equipped with a block 5 for automatic classification of the user's physical activity based on the output of the block 7 for automatic monitoring of the user's electronic communication.
  • the block 5 for classification of the user's physical activity consists of a programmable block in the Intel NUC mini-computer, which contains an input interface (LAN Ethernet Internet interface, wireless LAN WiFi), an output interface (LAN Ethernet Internet interface, wireless LAN WiFi) and which processes input data (event type, place and character, data from sensors) and the output data are classifications of the user's activity (character, duration, frequency, place and time of the activity) and the correlation with the user's activity.
  • the intelligent sensor network according to the embodiment of fig. 1 has been described with three sensors 1 for diabetics. Experts will find it obvious that for a different disease type or different goal (e.g. weight reduction, training with the aim to increase performance etc.) any other known sensors can be used, e.g. a sphygmomanometer, bio-impedance scape, GPS sensor, NFC sensor etc.
  • the sensors 1 may be attached to the user's body, but also to the user's clothing, installed in the user's place of residence etc. Depending on the disease type or the goal the user wants to achieve the block 4 for sending feedback may be interconnected not only with the user's peripheral 2, but also with a physician's, fitness coach's, nutrition consultant's etc. peripheral as well.
  • the intelligent sensor network schematically shown in fig. 1 , works as follows.
  • the outputs of the sensors 1 are sent by means of the user's peripheral 2 via a GSM or WiFi interface to the central server 3.
  • the automatic classification of the user's physical activity is done by the intelligent sensor network in such a way that the block 7 for automatic monitoring of the user's electronic communication automatically continuously monitors the electronic communication conducted by the user of the intelligent sensor network through the social network servers 6 (social network messages), as well as outside these networks (MMS, SMS, e-mail).
  • the data relating to the user's electronic communication are used to obtain characteristic information about the user's current place and/or time of stay and/or activity and the automatic classification of the user's physical activity is done in block 5 for automatic classification of the user's physical activity by assignment of the obtained characteristic information to the outputs of the sensors 1 of the intelligent sensor network.
  • the block 4 for sending feedback sends feedback to the user's peripheral 2 in the form of an SMS, e-mail or another similar electronic message and this feedback contains information about the classification of the user's physical activity (walking, jogging, swimming, skiing etc.), the duration, frequency, place and time of the activity.

Abstract

An intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user, comprising a set of sensors (1) and at least one user's peripheral (2). The sensors (1) are interconnected, via a user's peripheral (2), with a central server (3). The central server (3) is equipped with a block (4) for sending feedback. The central server (3) is interconnected with a social network server (6). The central server (3) is equipped with a block (7) for automatic monitoring of the user's electronic communication. The central server (3) is further equipped with a block (5) for automatic classification of the user's physical activity based on the output from the block (7) for automatic monitoring of the user's electronic communication.

Description

Intelligent sensor network and a method of automatic classification of physical activity of the user of the intelligent sensor network
Technical Field
The invention relates to an intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user, comprising a set of sensors and at least one user's peripheral while the sensors are interconnected with the central server via the user's peripheral, the server being equipped with a block for sending feedback. The invention further relates to a method of automatic classification of physical activity of the user of such an intelligent sensor network.
Prior Art
Remote health condition monitoring, sometimes referred to as telemedicine, is commonly well-known, including relatively complex and expensive systems for such monitoring. Such systems are described e.g. by the patents US5375604, US5441047 or the published application US2002115916.
Well-known commercially available systems for remote monitoring of the health condition of individual users generally consist of a single-purpose device for monitoring one or a few values, e.g. the pulse, blood pressure etc. These known systems are not suitable for comprehensive monitoring of the health condition and do not have comprehensive feedback that would make it possible to send comprehensive recommendations to the user based on the set of established values.
The Czech utility model no. 25375 discloses a health condition remote monitoring system that comprises a set of sensing devices connected to the central server with transmission channels, the server being fitted with a block for processing the measured values while at least one user's peripheral device is connected to the central server. At the input of the central server an interface is installed for the connection of a set of sensing devices with a different design while the block for processing the measured values is connected to a database of limit values and algorithms and a block for user communication connected to the user's peripheral with transmission channels is connected to the block for processing the measured values.
In addition, there are "sport-testers", which can measure the speed, distances and pulse during jogging, cycling, swimming etc. The data of some devices can be loaded to a computer where the user can keep a training logbook.
However, none of the known systems is able to automatically distinguish the type of the conducted activity (jogging, cycling, skiing, swimming etc.). Thus, the user must subsequently classify individual activities by manually adding the type of the conducted activity (jogging, cycling, skiing, swimming etc.) to the recorded data.
The goal of the invention is to design such equipment that would be able to automatically recognize the type of the conducted activity.
Disclosure of the Invention
The above mentioned goal is achieved with an intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user, comprising a set of sensors and at least one user's peripheral while the sensors are interconnected, via the user's peripheral, with a central server that is equipped with a block for sending feedback according to the invention the principle of which is that the central server is interconnected with a social network server and the central server is equipped with a block for automatic monitoring of the user's electronic communication. The central server is further equipped with a block for automatic classification of the user's physical activity based on the output of the block for automatic monitoring of the user's electronic communication. An advantage of the automatic sensor network in accordance with the invention is that it makes it possible to automatically classify the currently conducted physical activity of the user (jogging, cycling, skiing, swimming etc.) based on characteristic information of the user's place and/or time of stay and/or activity obtained through monitoring of the user's electronic communication on social network servers.
In an advantageous embodiment the block for automatic monitoring of the user's electronic communication is interconnected with the user's peripheral so characteristic information about the user's place and/or time of stay and/or activity is obtained not only by monitoring of the user's electronic communication on social network servers, but also the other electronic communication of the user (SMS, MMS, e-mail, etc.)
In a convenient embodiment the sensors comprise a sphygmomanometer and/or pedometer and/or bio-impedance scale and/or glucose meter and/or accelerometer and/or gyroscope and/or GPS sensor and/or NFC sensor.
The sensors may be attached to the user's body and/or to the user's clothing and/or installed in the user's place of residence. in a convenient embodiment the block for sending feedback is interconnected with the user's peripheral and/or with a physician's peripheral and/or with a fitness coach's peripheral and or a nutrition consultant's peripheral. The above mentioned goal is also achieved using a method of automatic classification of physical activity of the user of the intelligent sensor network in accordance with the invention the principle of which is that
the electronic communication of the user of the intelligent sensor network is automatically continuously monitored,
this electronic communication is used to obtain characteristic information about the place and/or time of stay and/or activity of the user and the automatic classification of the user's physical activity is done by assignment of the obtained characteristic information to the output of the sensors of the intelligent sensor network. Brief Description of Drawings
The intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user will be described in a more detailed way using a particular embodiment example, shown schematically in fig. 1.
Description of preferred embodiments
The example of an embodiment of the intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user, shown schematically in fig. 1 , is intended for a diabetic and comprises three sensors 1 , which are a DEXCOM G4 glucose meter for continuous measurement of the blood sugar level, a "smart" Flex-fitbit wristband where a pedometer, accelerometer and gyroscope for monitoring the physical activity and energy output of the user are integrated and a "smart" watch for entering more user data, especially data about the energy value of consumed food.
The intelligent sensor network further comprises the user's peripheral 2, which is a LG Nexus 5 smartphone in the described embodiment example. The user's peripheral 2 fulfils the function of a data collection and transmission device among other things.
The sensors 1 are interconnected with the central server 3 via the user's peripheral 2 by means of a GSM or WiFi interface, the server 3 being represented by an Intel NUC mini-computer with an integrated CPU, RAM, data storage and communication interface in this particular case. The central server 3 is equipped with a block 4 for sending feedback, which is in this particular embodiment example a programmable block in the Intel NUC minicomputer, which contains an input interface (LAN Ethernet Internet interface, wireless LAN WiFi) and an output interface (LAN Ethernet internet interface, wireless LAN WiFi GSM gate for sending SMS and MMS) and which processes input data (MMS, SMS, e-mail, social network messages) and output data (MMS, SMS, e-mail, social network messages).
The central server 3 is interconnected with a social network server 6 consisting of a cloud server. For clarity, fig. 1 shows one social network server 6, but the intelligent sensor network is actually interconnected with any number of known servers of social networks as Facebook, Twitter, instagram etc.
The central server 3 is equipped with a block 7 for automatic monitoring of the user's electronic communication through the social network server 6 and the user's peripheral 2. In this document, the user's electronic communication refers to any electronic communication of the user through the social network server 6 and the user's peripheral 2(MMS, SMS, e-mail, social network messages). In this particular embodiment example the block 7 for automatic monitoring of the user's electronic communication consists of a programmable block in the Intel NUC minicomputer, which contains an input interface (LAN Ethernet Internet interface, wireless LAN WiFi, a GSM gate for receiving SMS and MMS) and an output interface (LAN Ethernet Internet interface, wireless LAN WiFi GSM gate for sending SMS and MMS) and which processes input data (MMS, SMS, e-mail, social network messages) and output data (MMS, SMS, e-mail, social network messages).
The central server 3 is further equipped with a block 5 for automatic classification of the user's physical activity based on the output of the block 7 for automatic monitoring of the user's electronic communication. In this particular embodiment example the block 5 for classification of the user's physical activity consists of a programmable block in the Intel NUC mini-computer, which contains an input interface (LAN Ethernet Internet interface, wireless LAN WiFi), an output interface (LAN Ethernet Internet interface, wireless LAN WiFi) and which processes input data (event type, place and character, data from sensors) and the output data are classifications of the user's activity (character, duration, frequency, place and time of the activity) and the correlation with the user's activity.
The intelligent sensor network according to the embodiment of fig. 1 has been described with three sensors 1 for diabetics. Experts will find it obvious that for a different disease type or different goal (e.g. weight reduction, training with the aim to increase performance etc.) any other known sensors can be used, e.g. a sphygmomanometer, bio-impedance scape, GPS sensor, NFC sensor etc.
The sensors 1 may be attached to the user's body, but also to the user's clothing, installed in the user's place of residence etc. Depending on the disease type or the goal the user wants to achieve the block 4 for sending feedback may be interconnected not only with the user's peripheral 2, but also with a physician's, fitness coach's, nutrition consultant's etc. peripheral as well. The intelligent sensor network, schematically shown in fig. 1 , works as follows.
The outputs of the sensors 1 are sent by means of the user's peripheral 2 via a GSM or WiFi interface to the central server 3. The automatic classification of the user's physical activity is done by the intelligent sensor network in such a way that the block 7 for automatic monitoring of the user's electronic communication automatically continuously monitors the electronic communication conducted by the user of the intelligent sensor network through the social network servers 6 (social network messages), as well as outside these networks (MMS, SMS, e-mail).
In the block 7 for automatic monitoring of the user's electronic communication the data relating to the user's electronic communication are used to obtain characteristic information about the user's current place and/or time of stay and/or activity and the automatic classification of the user's physical activity is done in block 5 for automatic classification of the user's physical activity by assignment of the obtained characteristic information to the outputs of the sensors 1 of the intelligent sensor network.
Then, the block 4 for sending feedback sends feedback to the user's peripheral 2 in the form of an SMS, e-mail or another similar electronic message and this feedback contains information about the classification of the user's physical activity (walking, jogging, swimming, skiing etc.), the duration, frequency, place and time of the activity.

Claims

1. An intelligent sensor network for automatic collection and administration of data characterizing the physiological functions and physical activity of the user, comprising a set of sensors (1) and at least one user's peripheral (2) while the sensors (1) are interconnected, via a user's peripheral (2), with a central server (3) that is equipped with a block (4) for sending feedback, characterized in that the central server (3) is interconnected with a social network server (6) and the central server (3) is equipped with a block (7) for automatic monitoring of the user's electronic communication while the central server (3) is further equipped with a block (5) for automatic classification of the user's physical activity based on the output from the block (7) for automatic monitoring of the user's electronic communication.
2. The intelligent sensor network in accordance with claim 1 , characterized in that the block (7) for automatic monitoring of the user's electronic communication is interconnected with the user's peripheral (2).
3. The intelligent sensor network in accordance with claim 1 or 2, characterized in that the sensors (1) comprise a sphygmomanometer and/or pedometer and/or bio-impedance scale and/or glucose meter and/or accelerometer and/or gyroscope and/or GPS sensor and/or NFC sensor.
4. The intelligent sensor network in accordance with claim 1 , 2 or 3, characterized in that the sensors (1) are attached to the user's body and/or the user's clothing and/or installed in the user's place of residence.
5. The intelligent sensor network in accordance with any of the previous claims, characterized in that the block (4) for sending feedback is interconnected with the user's peripheral (2) and/or with a physician's and/or fitness coach's and/or nutrition consultant's peripheral.
6. A method of automatic classification of physical activity of the user of the intelligent sensor network in accordance with any of claims 1 - 5, characterized in that the electronic communication of the user of the intelligent sensor network is automatically continuously monitored,
this electronic communication is used to obtain characteristic information about the place and/or time of stay and/or activity of the user and
the automatic classification of the user's physical activity is done by assignment of the obtained characteristic information to the output of the sensors of the intelligent sensor network.
PCT/CZ2014/000161 2014-12-19 2014-12-19 Intelligent sensor network and a method of automatic classification of physical activity of the user of the intelligent sensor network WO2016095875A1 (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106650243A (en) * 2016-12-06 2017-05-10 北京体育大学 Relaxation activity system of preventing injury to athlete muscle

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5375604A (en) 1992-12-11 1994-12-27 Siemens Medical Electronics, Inc. Transportable modular patient monitor
US5441047A (en) 1992-03-25 1995-08-15 David; Daniel Ambulatory patient health monitoring techniques utilizing interactive visual communication
US20020115916A1 (en) 1996-09-19 2002-08-22 Ortivus Ab Portable telemedicin device
GB2393356A (en) * 2002-09-18 2004-03-24 E San Ltd Remote patient monitoring system
CZ25375U1 (en) 2013-04-02 2013-05-13 Sherlog Evito, A.S. System for remote monitoring of health condition
US20130151343A1 (en) * 2011-12-09 2013-06-13 Samsung Electronics Co., Ltd. Displaying mobile advertising based on determining user's physical activity from mobile device sensor data
US20130190004A1 (en) * 2012-01-20 2013-07-25 Matthew Nicholas Papakipos Statistics for Continuous Location Tracking
US20140125481A1 (en) * 2012-11-06 2014-05-08 Aliphcom General health and wellness management method and apparatus for a wellness application using data associated with a data-capable band
US20140129260A1 (en) * 2011-07-14 2014-05-08 Korea University Research And Business Foundation Method and device for providing application service using health classification information
US20140206327A1 (en) * 2013-01-18 2014-07-24 Apple Inc. Method and Apparatus For Automatically Adjusting the Operation of Notifications Based on Changes in Physical Activity Level
US20140350349A1 (en) * 2011-12-16 2014-11-27 Koninklijke Philips. N.V. History log of users activities and associated emotional states

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5441047A (en) 1992-03-25 1995-08-15 David; Daniel Ambulatory patient health monitoring techniques utilizing interactive visual communication
US5375604A (en) 1992-12-11 1994-12-27 Siemens Medical Electronics, Inc. Transportable modular patient monitor
US20020115916A1 (en) 1996-09-19 2002-08-22 Ortivus Ab Portable telemedicin device
GB2393356A (en) * 2002-09-18 2004-03-24 E San Ltd Remote patient monitoring system
US20140129260A1 (en) * 2011-07-14 2014-05-08 Korea University Research And Business Foundation Method and device for providing application service using health classification information
US20130151343A1 (en) * 2011-12-09 2013-06-13 Samsung Electronics Co., Ltd. Displaying mobile advertising based on determining user's physical activity from mobile device sensor data
US20140350349A1 (en) * 2011-12-16 2014-11-27 Koninklijke Philips. N.V. History log of users activities and associated emotional states
US20130190004A1 (en) * 2012-01-20 2013-07-25 Matthew Nicholas Papakipos Statistics for Continuous Location Tracking
US20140125481A1 (en) * 2012-11-06 2014-05-08 Aliphcom General health and wellness management method and apparatus for a wellness application using data associated with a data-capable band
US20140206327A1 (en) * 2013-01-18 2014-07-24 Apple Inc. Method and Apparatus For Automatically Adjusting the Operation of Notifications Based on Changes in Physical Activity Level
CZ25375U1 (en) 2013-04-02 2013-05-13 Sherlog Evito, A.S. System for remote monitoring of health condition

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106650243A (en) * 2016-12-06 2017-05-10 北京体育大学 Relaxation activity system of preventing injury to athlete muscle

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