Shang Chih Su Lin

US Patent:

20110178707, Jul 21, 2011

Filed:

Jan 21, 2010

Appl. No.:

12/691710

Inventors:

David Sachs - Sunnyvale CA, US
Shang Hung Lin - San Jose CA, US

Assignee:

INVENSENSE, INC. - Sunnyvale CA

International Classification:

G01C 25/00
G01C 21/16
G01C 17/38
G01P 15/00
G01C 19/00
G06F 17/30

US Classification:

701216, 73 176, 73 177, 702141, 702151, 707802, 707E17044

Abstract:

Novel techniques for estimating compass and gyroscope biases for handheld devices are disclosed. The handheld devices can include wireless phones, navigational devices and video gaming systems. The compass bias can be determined by causing a small movement of the handheld device and comparing the data obtained from the compass with the data obtained from the gyroscope. The gyroscope bias can be determined by obtaining a quaternion based angular velocity term of the handheld device when the accelerometer and compass data are reliable, and then comparing the angular velocity term to with the gyro data estimate the gyro bias. When the compass and/or the accelerometer data are unreliable, a previously determined quaternion angular velocity term is used, which was determined when the compass and the accelerometer were providing reliable data. The gyroscope bias can also be determined by measuring gyroscope biases at various temperatures in a non-factory setting, and storing that data in a memory, and using the data to estimate gyro biases when the accelerometer and/or the compass data are unreliable.

US Patent:

20160051167, Feb 25, 2016

Filed:

Aug 21, 2014

Appl. No.:

14/464999

Inventors:

- San Jose CA, US
Hemabh Shekar - San Jose CA, US
Shang Hung Lin - San Jose CA, US
Chih-Chieh Geoff Chang - Mountain View CA, US

International Classification:

A61B 5/11

Abstract:

A system and method for efficiently and accurately classifying user activity. In a non-limiting example, accelerometer signals and/or gyroscope sensor signals may be analyzed to classify user activity, for example, that of a user of a handheld and/or wearable device. Information from additional sources and sensors (e.g., other inertial sensors, non-inertial sensors, passive sensors, etc.) may also be utilized.