Nothing Special   »   [go: up one dir, main page]

Tian et al., 2009 - Google Patents

Wearable activity recognition for automatic microblog updates

Tian et al., 2009

Document ID
16078495275819713281
Author
Tian H
Lei P
Xingjuan L
Shusong X
Publication year
Publication venue
2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

External Links

Snippet

Activity recognition system based on MEMS sensors and wearable computer can produce updates on microblog automatically and frequently. Miniature sensors like the accelerometers made with MEMS technologies can measure body movements continuously …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
JP6777201B2 (en) Information processing equipment, information processing methods and programs
Laput et al. Sensing fine-grained hand activity with smartwatches
US9641991B2 (en) Systems and methods for determining a user context by correlating acceleration data from multiple devices
Wang et al. Friendbook: a semantic-based friend recommendation system for social networks
Lim et al. Fall‐Detection Algorithm Using 3‐Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model
Hoseini-Tabatabaei et al. A survey on smartphone-based systems for opportunistic user context recognition
Jian et al. A portable fall detection and alerting system based on k-NN algorithm and remote medicine
Hung et al. Activity recognition with sensors on mobile devices
Wu et al. We hear your activities through Wi-Fi signals
Bouton-Bessac et al. Your Day in Your Pocket: Complex Activity Recognition from Smartphone Accelerometers
Tian et al. Wearable activity recognition for automatic microblog updates
Wang et al. Recognizing transportation mode on mobile phone using probability fusion of extreme learning machines
Guo et al. Multimode pedestrian dead reckoning gait detection algorithm based on identification of pedestrian phone carrying position
Pascoal et al. Activity recognition in outdoor sports environments: smart data for end-users involving mobile pervasive augmented reality systems
He et al. A wearable method for autonomous fall detection based on kalman filter and k-nn algorithm
Choujaa et al. Activity recognition from mobile phone data: State of the art, prospects and open problems
Lee et al. Enabling human activity recognition with smartphone sensors in a mobile environment
Sun et al. Context awareness-based accident prevention during mobile phone use
Faye et al. Toward a characterization of human activities using smart devices: A micro/macro approach
Brahim et al. A New Semantic-based Multi-Level Classification Approach for Activity Recognition Using Smartphones
Hnoohom et al. Recognizing Stationary and Locomotion Activities using LSTM-XGB with Smartphone Sensors
Pei et al. Cognitive phone for sensing human behavior
Gil et al. Comparing features extraction techniques using j48 for activity recognition on mobile phones
Burda Authenticating users based on how they pick up smartphones
Ahn et al. Physical training gesture recognition using wristwatch wearable devices