Activity recognition using a single accelerometer placed at the wrist or ankle - Wikidata - wikimedia - TriplyDB

Activity recognition using a single accelerometer placed at the wrist or ankle

Activity recognition using a single accelerometer placed at the wrist or ankle

http://www.wikidata.org/entity/Q37227824

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The Elderly's Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development.Movement prediction using accelerometers in a human population.Estimating physical activity in youth using a wrist accelerometer.MEMS sensor technologies for human centred applications in healthcare, physical activities, safety and environmental sensing: a review on research activities in Italy.Evaluation of prompted annotation of activity data recorded from a smart phone Exercise Performance Measurement with Smartphone Embedded Sensor for Well-Being Management.Sit-to-Stand Transition Reveals Acute Fall Risk in Activities of Daily Living.Better than counting seconds: Identifying fallers among healthy elderly using fusion of accelerometer features and dual-task Timed Up and Go.Dealing with the effects of sensor displacement in wearable activity recognition Predicting human movement with multiple accelerometers using movelets Objectively measured physical activity in two-year-old children - levels, patterns and correlates A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers.Assessment of physical activity and energy expenditure: an overview of objective measures.mDurance: A Novel Mobile Health System to Support Trunk Endurance Assessment.Reliability and validity of ten consumer activity trackers.Accelerometry-based Recognition of the Placement Sites of a Wearable Sensor Methods to estimate aspects of physical activity and sedentary behavior from high-frequency wrist accelerometer measurements.Characterizing Pain Flares From the Perspective of Individuals With Symptomatic Knee Osteoarthritis.Innovations in the Use of Interactive Technology to Support Weight Management.A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients.Ngram time series model to predict activity type and energy cost from wrist, hip and ankle accelerometers: implications of age.Comparison of physical activity assessed using hip- and wrist-worn accelerometers.Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification.Performance of Activity Classification Algorithms in Free-Living Older Adults How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls?Impact of imposed exercise on energy intake in children at risk for overweight.Hierarchical Activity Recognition Using Smart Watches and RGB-Depth Cameras A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition.The Role of Heart-Rate Variability Parameters in Activity Recognition and Energy-Expenditure Estimation Using Wearable Sensors.Occupational physical activity assessment for chronic disease prevention and management: A review of methods for both occupational health practitioners and researchers.Performance Evaluation of State of the Art Systems for Physical Activity Classification of Older Subjects Using Inertial Sensors in a Real Life Scenario: A Benchmark Study.Activity Recognition in Youth Using Single Accelerometer Placed at Wrist or Ankle.Window size impact in human activity recognition.Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.Physical activity using wrist-worn accelerometers: comparison of dominant and non-dominant wrist.A cluster randomised controlled trial to evaluate the effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among adolescents aged 13-14 years.Profiling Movement and Gait Quality Characteristics in Pre-School Children.Can energy expenditure be accurately assessed using accelerometry-based wearable motion detectors for physical activity monitoring in post-stroke patients in the subacute phase?A wrist sensor and algorithm to determine instantaneous walking cadence and speed in daily life walking.A More Efficient Transportable and Scalable System for Real-Time Activities and Exercises Recognition.

P2860

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P2860

Activity recognition using a single accelerometer placed at the wrist or ankle

http://www.wikidata.org/entity/Q37227824

description

2013 nî lūn-bûn

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2013年の論文

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2013年学术文章

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2013年学术文章

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2013年学术文章

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2013年学术文章

@zh-my

2013年学术文章

@zh-sg

2013年學術文章

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2013年學術文章

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2013年學術文章

@zh-hant

name

Activity recognition using a single accelerometer placed at the wrist or ankle

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Activity recognition using a single accelerometer placed at the wrist or ankle.

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type

label

Activity recognition using a single accelerometer placed at the wrist or ankle

@en

Activity recognition using a single accelerometer placed at the wrist or ankle.

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prefLabel

Activity recognition using a single accelerometer placed at the wrist or ankle

@en

Activity recognition using a single accelerometer placed at the wrist or ankle.

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Medicine and Science in Sports and Exercise

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Activity recognition using a single accelerometer placed at the wrist or ankle

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P2093

Angelo M Sabatini

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Mary Rosenberger

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Stephen S Intille

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William Haskell

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P2860

Physical activity in the United States measured by accelerometer

Physical activity assessment with accelerometers: an evaluation against doubly labeled water.

Avoiding non-independence in fMRI data analysis: leave one subject out

Gait phase detection and discrimination between walking-jogging activities using hidden Markov models applied to foot motion data from a gyroscope.

Body acceleration distribution and O2 uptake in humans during running and jumping.

Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement.

Estimating activity and sedentary behavior from an accelerometer on the hip or wrist

Methods for gait event detection and analysis in ambulatory systems.

Design of a wearable physical activity monitoring system using mobile phones and accelerometers.

Physical activity classification using the GENEA wrist-worn accelerometer.

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2193-2203

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