[go: up one dir, main page]

Wu et al., 2016 - Google Patents

Analysis and classification of stride patterns associated with children development using gait signal dynamics parameters and ensemble learning algorithms

Wu et al., 2016

View PDF @Full View
Document ID
15213197935754883455
Author
Wu M
Liao L
Luo X
Ye X
Yao Y
Chen P
Shi L
Huang H
Wu Y
Publication year
Publication venue
BioMed research international

External Links

Snippet

Measuring stride variability and dynamics in children is useful for the quantitative study of gait maturation and neuromotor development in childhood and adolescence. In this paper, we computed the sample entropy (SampEn) and average stride interval (ASI) parameters to …
Continue reading at onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1121Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116Determining posture transitions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-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
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/45For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4528Joints
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813Specially adapted to be attached to a specific body part
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802Sensor mounted on worn items
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/0002Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/05Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
    • A61B5/053Measuring electrical impedance or conductance of a portion of the body
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/165Evaluating the state of mind, e.g. depression, anxiety

Similar Documents

Publication Publication Date Title
Sehle et al. Objective assessment of motor fatigue in multiple sclerosis: the Fatigue index Kliniken Schmieder (FKS)
Kim et al. Children with cerebral palsy have greater stride-to-stride variability of muscle synergies during gait than typically developing children: implications for motor control complexity
Pinto-Bernal et al. A data-driven approach to physical fatigue management using wearable sensors to classify four diagnostic fatigue states
DeBerardinis et al. A comparison of two techniques for center of pressure measurements
De Brabandere et al. Data fusion of body-worn accelerometers and heart rate to predict VO2max during submaximal running
Gall et al. A comparison of wrist-versus hip-worn actigraph sensors for assessing physical activity in adults: a systematic review
Kluge et al. Real-world gait detection using a wrist-worn inertial sensor: validation study
Ahmadi et al. Laboratory-based and free-living algorithms for energy expenditure estimation in preschool children: a free-living evaluation
Montes et al. Gait assessment with solesound instrumented footwear in spinal muscular atrophy
DeShaw et al. Methods for activity monitor validation studies: an example with the Fitbit charge
Ponciano et al. Sensors are capable to help in the measurement of the results of the timed-up and go test? a systematic review
Cosoli et al. Methods for the metrological characterization of wearable devices for the measurement of physiological signals: state of the art and future challenges
Czech et al. The impact of reducing the number of wearable devices on measuring gait in parkinson disease: Noninterventional exploratory study
Wiles et al. NONAN GaitPrint: An IMU gait database of healthy young adults
Zhong et al. Gait Assessment of Younger and Older Adults with Portable Motion‐Sensing Methods: A User Study
McAloon et al. Validation of the activPAL activity monitor in children with hemiplegic gait patterns resultant from cerebral palsy
Wu et al. Analysis and classification of stride patterns associated with children development using gait signal dynamics parameters and ensemble learning algorithms
Wu et al. Human gait-labeling uncertainty and a hybrid model for gait segmentation
Zignoli et al. Indoor running temporal variability for different running speeds, treadmill inclinations, and three different estimation strategies
Dini et al. Digital remote monitoring of people with multiple sclerosis
Liu et al. The Multivariate Largest Lyapunov Exponent as an Age‐Related Metric of Quiet Standing Balance
Li et al. Internet of things-based smart wearable system to monitor sports person health
Wipperman et al. Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning
Lendt et al. Assessing the accuracy of activity classification using thigh-worn accelerometry: A validation study of ActiPASS in school-aged children
Knowlden Measure of Physical Activity for Health Promotion and Education Research