Invensense, Inc.

Qualcomm Incorporated

Igor Tchertkov

Evgeni Petrovich Gousev

Russell Wayne Gruhlke

Joseph Seeger

Steven Saeed Nasiri

Martin Lim

Russel A Martin

Michael Julian Daneman

Joseph Czompo

Hasan Akyol

Kegang Huang

Evgeni Poliakov

Muhammed Ibrahim Sezan

Ilya Gurin

Goksen G Yaralioglu

Alexander Castro

Joe Seeger

Jin Qiu

Richard Li

Vidyut Naware

Shashank Narayanan

Siddika Parlak Polatkan

Hithesh Reddivari

Russel Allyn Martin

Evgeni Yurij Poliakov

A Microelectromechanical systems (MEMS) structure comprises a MEMS wafer. A MEMS wafer includes a handle wafer with cavities bonded to a device wafer through a dielectric layer disposed between the handle and device wafers. The MEMS wafer also includes a moveable portion of the device wafer suspended over a cavity in the handle wafer. Four methods are described to create two or more enclosures having multiple gas pressure or compositions on a single substrate including, each enclosure containing a moveable portion. The methods include: A. Forming a secondary sealed enclosure, B. Creating multiple ambient enclosures during wafer bonding, C. Creating and breaching an internal gas reservoir, and D. Forming and subsequently sealing a controlled leak/breach into the enclosure.

Methods for CMOS-MEMS integrated devices with multiple sealed cavities maintained at various pressures

Disclosed embodiments pertain to cardiovascular parameter (e.g. heart rate) measurements when motion is present. Biometric sensor signal measurements may be obtained based on cardiovascular parameters of a user; and motion sensor signal measurements may be obtained based on user motion. An activity type may be determined based on the motion sensor signals. For example, when non-motion related frequencies in a frequency domain representation of the biometric sensor signal are obscured by user motion, an activity type may be determined based on the motion sensor signals. Further, based on the activity type, for each cardiovascular parameter (e.g. heart rate), a corresponding likely cardiovascular parameter value (e.g. a likely heart rate) may be determined. A corresponding fundamental frequency associated with the biometric sensor signal may then be determined for each cardiovascular parameter based on the motion sensor signal measurements and the corresponding likely cardiovascular parameter value.

Cardiovascular parameter estimation in the presence of motion

Methods, systems, computer-readable media, and apparatuses for obtaining blood pressure measurements are presented. The blood pressure measurements may be obtained by determining a pulse-transit time (PTT) as a function of a photoplethysmography (PPG) measurement and electrocardiogram (ECG) measurement. A mobile device includes outer body sized to be portable for a user of the mobile device. The mobile device also includes a plurality of light emitting components distributed along at least one portion of the mobile device and a plurality of light collecting components configured to measure reflected light from the plurality of light emitting components reflected off of blood vessels within the user. The light emitting and light collecting components are distributed along the at least one portion of the mobile device. The mobile device may also include a light guide configured to direct light emitted by the at least one light emitting component toward blood vessels with the user.

System and method for obtaining blood pressure measurement

Described herein is an accelerometer that can be sensitive to acceleration, but not anchor motion due to sources other than acceleration. The accelerometer can employ a set of electrodes and/or transducers that can register motion of the proof mass and support structure and employ and output-cancelling mechanism so that the accelerometer can distinguish between acceleration and anchor motion due to sources other than acceleration. For example, the effects of anchor motion can be cancelled from an output signal of the accelerometer so that the accelerometer exhibits sensitivity to only acceleration.

Anchor-tilt cancelling accelerometer

Systems, apparatus and methods for estimating a mass of an object by a mobile device are presented. The mobile device, which may be a smartphone, vibrates the mobile device both unloaded (without an object) and loaded (with an object) while measuring the unloaded and loaded vibrations. Next, the mobile device compares the unloaded and loaded vibrations and determines the mass of the object from the comparison.

Dynamic force sensing to determine mass using a smartphone

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San Jose, CA, United States of America

Igor Tchertkov