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US 2019/0056422 A1Published application
Systems and methods for human body motion capture
AssigneeBigMotion Technologies Inc.
InventorsJung Wook PARK, Shaghayegh ZIHAJEHZADEH
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Abstract
The present disclosure provides substantially magnetometer-free systems and methods for motion capture of a subject including 3-D localization and posture tracking by fusing inertial sensors with a localization system and a biomechanical model of the subject. Using the novel Kalman filter based fusion techniques disclosed herein, the localization data aided with the biomechanical model can eliminate the drift in inertial yaw angle estimation.
Claims10
A system for capturing lower body motion of a subject, the system comprising:
- an inertial measurement unit (IMU) mounted on each of a left foot, a right foot, a left shank, a right shank, a left thigh, a right thigh and a pelvis of the subject, each IMU unit comprising an accelerometer and a gyroscope and configured to output rate of turn signals and acceleration signals;
- a localization tag mounted on each of a left mid foot, a right mid foot and a waist of the subject;
- a localization sensor system configured to detect each localization tag and to output position signals for each localization tag;
- and,
- a processing system in communication with each IMU and with the localization sensor system to receive the rate of turn, acceleration, and position signals, and to derive velocity signals for each localization tag from the position signals, the processing system comprising:
- a tilt Kalman filter configured to process the rate of turn and acceleration signals from each IMU to generate a pitch angle and a roll angle for each of the left foot, right foot, left shank, right shank, left thigh, right thigh and pelvis;
- a localization Kalman filter configured to process the rate of turn and acceleration signals, the position signals and the velocity signals for each localization tag, and the pitch angle and the roll angle for each of the left foot, right foot and pelvis from the tilt Kalman filter to generate a position vector for each of the left mid foot, right mid foot and waist and a rotation matrix for each of the left foot, right foot and pelvis;
- a yaw Kalman filter configured to process the pitch angle and the roll angle for each of the left shank, right shank, left thigh and right thigh from the tilt Kalman filter and the position vector for each of the left mid foot, right mid foot and waist and the rotation matrix for each of the left foot, right foot and pelvis from the localization Kalman filter to generate a yaw angle for each of the left shank, right shank, left thigh and right thigh;
- and
- a motion reconstruction block configured to reconstruct full three-dimensional motion of the subject's lower body based on the pitch angle and the roll angle for each of the left shank, right shank, left thigh and right thigh from the tilt Kalman filter, the position vector for each of the left mid foot, right mid foot and waist and the rotation matrix for each of the left foot, right foot and pelvis from the localization Kalman filter, and the yaw angle for each of the left shank, right shank, left thigh and right thigh from the yaw Kalman filter.
7 more elements
A method for capturing motion of a subject, the method comprising:
- mounting a plurality of inertial measurement units (IMUs) on the subject, each IMU mounted on one of a plurality of body segments of the subject, the plurality or body segments comprising one or more kinematic chains, each kinematic chain having a root segment and an end segment, each IMU configured to generate acceleration signals and rate of turn signals for a respective body segment;
- mounting a plurality of localization tags on the subject, with one localization tag mounted at a localization point on each root segment and each end segment of the plurality of body segments of the subject;
- detecting the localization tags to generate position signals and velocity signals for each of the localization tags;
- processing the acceleration signals and the rate of turns signals for the plurality of IMUs in a tilt Kalman filter to generate a pitch angle and a roll angle for each of the plurality of body segments;
- processing the rate of turn and acceleration signals from the IMUs mounted on the root and end segments of the plurality of body segments, the position signals and the velocity signals for each of the localization tags from the localization sensor system, and the pitch angle and the roll angle for each of the root and end segments of the plurality of body segments from the tilt Kalman filter in a localization Kalman filter to generate a position vector for each localization point and a rotation matrix for each of the root and end segments of the plurality of body segments;
- processing the pitch angle and the roll angle for each of the plurality of body segments other than the root and end segments from the tilt Kalman filter and the position vector for each localization point and the rotation matrix for each of the root and end segments of the plurality of body segments from the localization Kalman filter in a yaw Kalman filter to generate a yaw angle for each of the plurality of body segments other than the root and end segments;
- and
- reconstructing full three-dimensional motion of the plurality of body segments based on the pitch angle and the roll angle for each of the plurality of body segments other than the root and end segments from the tilt Kalman filter, the position vector for each localization point on each end segment and the rotation matrix for each end segment and each root segment from the localization Kalman filter, and the yaw angle for each of the plurality of body segments other than the root and end segments from the yaw Kalman filter.
5 more elements
Dependencies are inferred from the claim text.