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

Förster, 2011 - Google Patents

Adaptation of activity recognition systems

Förster, 2011

View PDF
Document ID
14075207165589392218
Author
Förster K
Publication year

External Links

Snippet

Advances in mobile computer systems, signal processing and sensing technology enable new computing applications to support the user anywhere and anytime. One such application is activity aware computing where the user's activities are taken into account to …
Continue reading at www.research-collection.ethz.ch (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • 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
    • G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116—Determining posture transitions

Similar Documents

Publication Publication Date Title
Górriz et al. Computational approaches to explainable artificial intelligence: advances in theory, applications and trends
US10970374B2 (en) User identification and authentication with neuromuscular signatures
CN112970056A (en) Human-computer interface using high speed and accurate user interaction tracking
US11179066B2 (en) Real-time spike detection and identification
Saa et al. Discriminative methods for classification of asynchronous imaginary motor tasks from EEG data
Malešević et al. Vector autoregressive hierarchical hidden Markov models for extracting finger movements using multichannel surface EMG signals
EP1032872A1 (en) User interface
Xu et al. Accelerating reinforcement learning using eeg-based implicit human feedback
Nguyen et al. Adaptive multi-degree of freedom Brain Computer Interface using online feedback: Towards novel methods and metrics of mutual adaptation between humans and machines for BCI
Quinton et al. The cat is on the mat. Or is it a dog? Dynamic competition in perceptual decision making
Kramer et al. Reconstructing nonlinear dynamical systems from multi-modal time series
Pereira-Montiel et al. Automatic sign language recognition based on accelerometry and surface electromyography signals: A study for Colombian sign language
WO2023003979A2 (en) Optimal data-driven decision-making in multi-agent systems
Hsiao et al. The role of eye movement consistency in learning to recognise faces: Computational and experimental examinations.
Ramadoss et al. Computer Vision for Human‐Computer Interaction Using Noninvasive Technology
Abbaspourazad et al. Dynamical flexible inference of nonlinear latent structures in neural population activity
Silva et al. Applications of human-computer interaction and robotics based on artificial intelligence
Förster Adaptation of activity recognition systems
Severin et al. Head Gesture Recognition based on 6DOF Inertial sensor using Artificial Neural Network
de Sa An interactive control strategy is more robust to non-optimal classification boundaries
Papakostas From body to brain: Using artificial intelligence to identify user skills & intentions in interactive scenarios
Bishop Combining Neural Population Recordings: Theory and Application.
de Faria Patient classification for intelligent wheelchair adaptation
Chandra et al. Eyeball Movement Cursor Control Using OpenCV
Kim et al. Enhancement of sEMG-based gesture classification using mahanobis distance metric