Attitude estimation of a wearable motion sensor

Chi Zhang, Amirhossein Taghvaei, Prashant G. Mehta

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper is concerned with the problem of attitude estimation for a wrist-worn motion sensor equipped with a 3-axis gyroscope and a 3-axis accelerometer. In the absence of motion and the with the arm in its natural resting state, the attitude is unobservable because the accelerometer's measurement of the gravity vector alone can not distinguish between configurations of the motion sensor obtained by rotating the sensor around the wrist. In the presence of motion, considered here to be the swinging motion of the arm, the observability is shown to improve. The estimation task is mathematically formulated as a continuous-time filtering problem on the product Lie group SO(3)×SO(2). The feedback particle filter (FPF) algorithm is explicitly constructed in this setting, using both the rotation matrix and the quaternion. Experimental results with real sensor data are provided to illustrate the tracking performance of the proposed filter.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509059928
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2017 American Control Conference, ACC 2017
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


Dive into the research topics of 'Attitude estimation of a wearable motion sensor'. Together they form a unique fingerprint.

Cite this