This paper presents a method for pedestrian motionclassification based on MEMS inertial measurement unit (IMU)mounted on the chest. The choice of mounting the IMU on thechest provides the potential application of the current study incamera-aided inertial navigation for positioning and personalassistance. In the present work, five categories of the pedestrianmotion including standing, walking, running, going upstairs,and going down the stairs are considered in the classificationprocedure. As the classification method, the continuous hiddenMarkov model (HMM) is used in which the output densityfunctions are assumed to be Gaussian mixture models (GMMs).The correct recognition rates based on the experimental resultsare about 95%.© 2012 IEEE. Per...
This research presents a novel approach to human gait analysis using wearable Inertial Measurement U...
Novel features for joint classification of gait and device modes are proposed and multiple machine l...
The advent of miniaturized sensing technology (MEMS: Micro-Electro-Mechanical Systems) gave the poss...
In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemente...
This paper presents a wearable Inertial Measurement Unit pedestrian positioning system for indoors. ...
This paper presents multi-category human motion recognition methods based on MEMS inertial sensing d...
This paper presents a new method of human motion recognition based on MEMS inertial sensors data. A ...
This paper presents a new method of human motion recognition based on MEMS inertial sensors data. A ...
This paper presents multi-category human motion recognition methods based on MEMS inertial sensing d...
International audienceThis paper presents a pedestrian navigation algorithm based on a foot-mounted ...
Pedestrian navigation in body-worn devices is usually based on global navigation satellite systems (...
Knowledge about the current motion related activity of a person is information that is required or ...
This paper describes a novel approach for human motion recognition via motion feature vectors collec...
In this paper we present a PDR (Pedestrian Dead Reckoning) algorithm which uses characteristic featu...
In this paper, an algorithm to estimate the position of a pedestrian in a 3-dimensional space is int...
This research presents a novel approach to human gait analysis using wearable Inertial Measurement U...
Novel features for joint classification of gait and device modes are proposed and multiple machine l...
The advent of miniaturized sensing technology (MEMS: Micro-Electro-Mechanical Systems) gave the poss...
In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemente...
This paper presents a wearable Inertial Measurement Unit pedestrian positioning system for indoors. ...
This paper presents multi-category human motion recognition methods based on MEMS inertial sensing d...
This paper presents a new method of human motion recognition based on MEMS inertial sensors data. A ...
This paper presents a new method of human motion recognition based on MEMS inertial sensors data. A ...
This paper presents multi-category human motion recognition methods based on MEMS inertial sensing d...
International audienceThis paper presents a pedestrian navigation algorithm based on a foot-mounted ...
Pedestrian navigation in body-worn devices is usually based on global navigation satellite systems (...
Knowledge about the current motion related activity of a person is information that is required or ...
This paper describes a novel approach for human motion recognition via motion feature vectors collec...
In this paper we present a PDR (Pedestrian Dead Reckoning) algorithm which uses characteristic featu...
In this paper, an algorithm to estimate the position of a pedestrian in a 3-dimensional space is int...
This research presents a novel approach to human gait analysis using wearable Inertial Measurement U...
Novel features for joint classification of gait and device modes are proposed and multiple machine l...
The advent of miniaturized sensing technology (MEMS: Micro-Electro-Mechanical Systems) gave the poss...