Recognizing human activities from smartphone sensors using hierarchical continuous hidden Markov models

Investigating Inter-Subject and Inter-Activity Variations in Activity Recognition Using Wearable Motion Sensors

(2015) Billur Barshan et al.   COMPUTER JOURNAL

A tutorial on human activity recognition using body-worn inertial sensors

(2014) Andreas Bulling et al.   ACM COMPUTING SURVEYS

Feature Selection and Activity Recognition System Using a Single Triaxial Accelerometer

(2014) Piyush Gupta et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems

(2014) Lei Gao et al.   MEDICAL ENGINEERING & PHYSICS

An Unsupervised Approach for Automatic Activity Recognition Based on Hidden Markov Model Regression

(2013) Dorra Trabelsi et al.   IEEE Transactions on Automation Science and Engineering

Human Behavior Cognition Using Smartphone Sensors

(2013) Ling Pei et al.   SENSORS

Optimal Placement of Accelerometers for the Detection of Everyday Activities

(2013) Ian Cleland et al.   SENSORS

A Survey on Human Activity Recognition using Wearable Sensors

(2012) Oscar D. Lara et al.   IEEE Communications Surveys and Tutorials

Sensor-Based Activity Recognition

(2012) Liming Chen et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE

A Triaxial Accelerometer-Based Physical-Activity Recognition via Augmented-Signal Features and a Hierarchical Recognizer

(2010) A M Khan et al.   IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE

Comparative study on classifying human activities with miniature inertial and magnetic sensors

(2010) Kerem Altun et al.   PATTERN RECOGNITION

Variable selection using random forests

(2010) Robin Genuer et al.   PATTERN RECOGNITION LETTERS

Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers

(2010) Andrea Mannini et al.   SENSORS

Empirical characterization of random forest variable importance measures

(2007) Kellie J. Archer et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS