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

Sethi et al., 2024 - Google Patents

Multi‐feature gait analysis approach using deep learning in constraint‐free environment

Sethi et al., 2024

Document ID
2004182681199274013
Author
Sethi D
Prakash C
Bharti S
Publication year
Publication venue
Expert Systems

External Links

Snippet

A quantitative gait assessment system is crucial for clinical analysis and decision‐making. Such rigorous evaluation involves costly clinical setups and domain experts for observation and analysis. To circumvent such constraints, the proposed work is conducted in a …
Continue reading at onlinelibrary.wiley.com (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
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • 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
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • 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
    • G06K9/00362—Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
    • G06K9/00369—Recognition of whole body, e.g. static pedestrian or occupant recognition
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • 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
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Cicirelli et al. Human gait analysis in neurodegenerative diseases: a review
Liao et al. A review of computational approaches for evaluation of rehabilitation exercises
Harris et al. A survey of human gait-based artificial intelligence applications
Sabo et al. Estimating parkinsonism severity in natural gait videos of older adults with dementia
Lu et al. Vision-based estimation of MDS-UPDRS gait scores for assessing Parkinson’s disease motor severity
Alvarez et al. Behavior analysis through multimodal sensing for care of Parkinson’s and Alzheimer’s patients
Hellsten et al. The potential of computer vision-based marker-less human motion analysis for rehabilitation
Zhao et al. Multimodal gait recognition for neurodegenerative diseases
Kour et al. Computer-vision based diagnosis of Parkinson’s disease via gait: A survey
Chaaraoui et al. Abnormal gait detection with RGB-D devices using joint motion history features
Rocha et al. System for automatic gait analysis based on a single RGB-D camera
Guo et al. Sparse adaptive graph convolutional network for leg agility assessment in Parkinson’s disease
WO2021186655A1 (en) Fall risk evaluation system
Kaur et al. A vision-based framework for predicting multiple sclerosis and Parkinson's disease gait dysfunctions—A deep learning approach
Rani et al. Human gait recognition: A systematic review
Wu et al. Robust fall detection in video surveillance based on weakly supervised learning
US20240070854A1 (en) Tracking, analysing and assessment of huamn body movements using a subject-specific digital twin model of the human body
Sethi et al. Multi‐feature gait analysis approach using deep learning in constraint‐free environment
Romeo et al. Video based mobility monitoring of elderly people using deep learning models
Zhen et al. Hybrid Deep‐Learning Framework Based on Gaussian Fusion of Multiple Spatiotemporal Networks for Walking Gait Phase Recognition
Rana et al. Markerless gait classification employing 3D IR-UWB physiological motion sensing
Rahman et al. Auto-gait: Automatic ataxia risk assessment with computer vision from gait task videos
Gaud et al. Human gait analysis and activity recognition: A review
Lin et al. A Feasible Fall Evaluation System via Artificial Intelligence Gesture Detection of Gait and Balance for Sub-Healthy Community-Dwelling Older Adults in Taiwan
Wang et al. Fall detection with a non-intrusive and first-person vision approach