A human motion capture system based on inertial sensing and a complementary filter

Kan Kanjanapas, Yizhou Wang, Wenlong Zhang, Lauren Whittingham, Masayoshi Tomizuka

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

3 Scopus citations

Abstract

A human motion capture system is becoming one of the most useful tools in rehabilitation application because it can record and reconstruct a patient's motion accurately for motion analysis. In this paper, a human motion capture system is proposed based on inertial sensing. A microprocessor is implemented onboard to obtain raw sensing data from the inertial measurement unit (IMU), and transmit the raw data to the central processing unit. To reject noise in the accelerometer, drift in the gyroscope, and magnetic distortion in the magnetometer, a time varying complementary filter (TVCF) is implemented in the central processing unit to provide accurate attitude estimation. A forward kinematic model of the human arm is developed to create an animation for patients and physical therapists. Performance of the hardware and filtering algorithm is verified by experimental results.

Original languageEnglish (US)
Title of host publicationNonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing;
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Print)9780791856147
DOIs
StatePublished - Jan 1 2013
Externally publishedYes
EventASME 2013 Dynamic Systems and Control Conference, DSCC 2013 - Palo Alto, CA, United States
Duration: Oct 21 2013Oct 23 2013

Publication series

NameASME 2013 Dynamic Systems and Control Conference, DSCC 2013
Volume3

Other

OtherASME 2013 Dynamic Systems and Control Conference, DSCC 2013
CountryUnited States
CityPalo Alto, CA
Period10/21/1310/23/13

ASJC Scopus subject areas

  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'A human motion capture system based on inertial sensing and a complementary filter'. Together they form a unique fingerprint.

Cite this