NDLI: Pedestrian positioning with physical activity classification for indoors

Content Provider	IEEE Xplore Digital Library
Author	Xi Chen Sheng Hu Zhenzhou Shao Jindong Tan
Copyright Year	2011
Description	Author affiliation: Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, 49931, USA (Xi Chen; Sheng Hu; Zhenzhou Shao; Jindong Tan)
Abstract	This paper presents a wearable Inertial Measurement Unit pedestrian positioning system for indoors. Hidden Markov Model (HMM) is introduced to pre-process the sensor data and classify common activities. HMM also complements local minimum angular rate value for capturing the onset/end of each step. ZUPT algorithm are implemented to correct the walking velocity at step stance phase when errors existed. A novel acceleration-based approach combined with gyroscope data is developed to achieve a better heading estimation. Proposed method is able to reduce drift errors from gyroscopes and avoid electromagnetic perturbance to magnetometers when estimate subject's position. Experiment results show the positioning system achieves approximately 99% accuracy.
Starting Page	1311
Ending Page	1316
File Size	614727
Page Count	6
File Format	PDF
ISBN	9781612843865
ISSN	10504729
e-ISBN	9781612843858
DOI	10.1109/ICRA.2011.5980236
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Legged locomotion Gyroscopes Acceleration Magnetometers Estimation Accelerometers
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Chest-mounted inertial measurement unit for pedestrian motion classification using continuous hidden Markov model

Hidden Markov models applied onto gait classification

Human activity recognition using inertial sensors with invariance to sensor orientation

Low cost infrastructure free form of indoor positioning

Nonlinear pitch and roll estimation for walking robots

Indoor positioning system using walking pattern classification

Pedestrian navigation system with fall detection and energy expenditure calculation

Walking speed estimation using shank-mounted accelerometers

Human activity recognition using smartphone sensors with two-stage continuous hidden Markov models

Pedestrian positioning with physical activity classification for indoors

Similar Documents

Chest-mounted inertial measurement unit for pedestrian motion classification using continuous hidden Markov model

Hidden Markov models applied onto gait classification

Human activity recognition using inertial sensors with invariance to sensor orientation

Low cost infrastructure free form of indoor positioning

Nonlinear pitch and roll estimation for walking robots

Indoor positioning system using walking pattern classification

Pedestrian navigation system with fall detection and energy expenditure calculation

Walking speed estimation using shank-mounted accelerometers

Human activity recognition using smartphone sensors with two-stage continuous hidden Markov models

Pedestrian positioning with physical activity classification for indoors