Wu et al., 2016 - Google Patents
Analysis and classification of stride patterns associated with children development using gait signal dynamics parameters and ensemble learning algorithmsWu et al., 2016
View PDF- 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 …
- 230000005021 gait 0 title abstract description 63
Classifications
-
- 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
- A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
- A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories
-
- 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
-
- 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
-
- 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
- A61B5/48—Other medical applications
-
- 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
- A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
- A61B5/4528—Joints
-
- 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
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements 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
- A61B5/6813—Specially adapted to be attached to a specific body part
-
- 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
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements 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
- A61B5/6802—Sensor mounted on worn items
-
- 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
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
-
- 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
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
- A61B5/053—Measuring electrical impedance or conductance of a portion of the body
-
- 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
- A61B5/02—Detecting, 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
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
-
- 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
- A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
- A61B5/165—Evaluating 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 |