Cirrus Logic Inc.

Luke Lapointe

Tejasvi Das

Siddharth Maru

Zhong You

Anthony Stephen Doy

Drew Kinney

Eric Jerome King

Matthew Beardsworth

Srdjan Marijanovic

Johann Guy Gaboriau

Emmanuel A Marchais

Srdjan Marjianovic

A system may include a plurality of sensors, a measurement circuit communicatively coupled to the plurality of sensors and configured to measure one or more physical quantities associated with the plurality of sensors, and a predictive optimization subsystem configured to detect an event associated with a first sensor of the plurality of sensors and responsive to the event, execute a predictive action with respect to one or more of the other sensors of the plurality of sensors.

Predictive sensor tracking optimization in multi-sensor sensing applications

A system may include a sensor configured to output a sensor signal indicative of a distance between the sensor and a mechanical member associated with the sensor, a measurement circuit communicatively coupled to the sensor and configured to determine a physical force interaction with the mechanical member based on the sensor signal, and a compensator configured to monitor the sensor signal and to apply a compensation factor to the sensor signal to compensate for changes to properties of the sensor based on at least one of changes in a distance between the sensor and the mechanical member and changes in a temperature associated with the sensor.

Compensation for air gap changes and temperature changes in a resonant phase detector

A system may include a resistive-inductive-capacitive sensor, a measurement circuit communicatively coupled to the resistive-inductive-capacitive sensor and configured to measure phase information associated with the resistive-inductive-capacitive sensor and based on the phase information, determine a displacement of a mechanical member relative to the resistive-inductive-capacitive sensor. The system may also include a Q factor enhancer communicatively coupled to the resistive-inductive-capacitive sensor and configured to control a Q factor of the resistive-inductive-capacitive sensor.

Q-factor enhancement in resonant phase sensing of resistive-inductive-capacitive sensors

A system may include a resistive-inductive-capacitive sensor, a measurement circuit communicatively coupled to the resistive-inductive-capacitive sensor and configured to at a plurality of periodic intervals, measure phase information associated with the resistive-inductive-capacitive sensor and based on the phase information, determine a displacement of a mechanical member relative to the resistive-inductive-capacitive sensor. The system may also include a driver configured to drive the resistive-inductive-capacitive sensor at a driving frequency and a driving amplitude, wherein at least one of the driving frequency and the driving amplitude varies among the plurality of periodic intervals.

False triggering prevention in a resonant phase sensing system

A method may include receiving an input signal from a force sensor configured to sense a force associated with a human interaction with a virtual button, comparing the input signal to at least one behavioral model, the at least one behavioral model comprising one or more parameters associated with a valid human interaction with the virtual button, and determining whether a valid human interaction with the virtual button occurred based on the comparing.

Virtual button characterization engine

A system may include a tactile actuator for providing tactile feedback and a resonant phase sensing system. The resonant phase sensing system may include a resistive-inductive-capacitive sensor and a measurement circuit communicatively coupled to the resistive-inductive-capacitive sensor and the tactile actuator. The resistive-inductive-capacitive sensor may be configured to measure phase information associated with the resistive-inductive-capacitive sensor, based on the phase information, detect an indication of human interaction with the system proximate to the resistive-inductive-capacitive sensor, and trigger the tactile actuator to generate tactile feedback responsive to detecting the indication of human interaction.

Efficient detection of human machine interface interaction using a resonant phase sensing system

A system may include a first resistive-inductive-capacitive sensor, a second resistive-inductive-capacitive sensor, and a measurement circuit communicatively coupled to the first resistive-inductive-capacitive sensor and the second resistive-inductive-capacitive sensor and configured to measure first phase information associated with the first resistive-inductive-capacitive sensor, measure second phase information associated with the second resistive-inductive-capacitive sensor, and based on the first phase information and the second phase information, determine a displacement of a mechanical member relative to the first resistive-inductive-capacitive sensor.

Use of reference sensor in resonant phase sensing system

A system may include a resistive-inductive-capacitive sensor, a driver configured to drive the resistive-inductive-capacitive sensor at a driving frequency, and a measurement circuit communicatively coupled to the resistive-inductive-capacitive sensor and configured to measure phase information associated with the resistive-inductive-capacitive sensor and based on the phase information, determine a displacement of a mechanical member relative to the resistive-inductive-capacitive sensor, wherein the displacement of the mechanical member causes a change in an impedance of the resistive-inductive-capacitive sensor.

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Austin, TX, United States of America

Luke Lapointe