Microsoft Technology Licensing, LLC

Nadav Linenberg

Matan Slassi

Gilad Pundak

Dmitry Birenberg

Arie Yehuda Gur

Lior Zagiel

Idan Palmor

Uri Ron

Netanel Hadad

Assaf Cohen

Amir Zyskind

Eran Arbel

Yael Livne

Andrew Pyon Mittereder

Ilan Geller

Eran Chencinski

Tal Aviv

On Haran

Vadim Mishalov

Oren Istrin

Anton Gorbanev

Adam Hakim

Hanan Grinberg

Roy Gan Maiberger

Hadas Ruas

Shai Levi

Examples are disclosed relating to noise compensation ratios in a spatial noise model to compensate for noise in a frame of touch sensor data. One example provides a computing device comprising a display, a touch sensor, a logic machine, and a storage machine comprising instructions. The instructions are executable by the logic machine to receive a noise level for each sensor antenna of a set of sensor antennas of the touch sensor. The instructions are further executable to, for each pair of sensor antennas of the set of sensor antennas, determine a noise compensation ratio comprising a noise level of a first antenna of the pair of sensor antennas compared to a noise level of a second antenna of the pair of sensor antennas, and store the noise compensation ratio in a spatial noise model.

Noise compensation using a spatial noise model

Examples are disclosed herein relating to simulating force-sensing functionality for a touch interface using a machine-learning model that is trained based at least on training data generated by a training touch interface including a plurality of force sensors. In one example, a computing system includes a touch interface configured to output a touch heatmap based at least on touch input detected by a plurality of touch sensors of the touch interface. The computing system is configured to execute a machine-learning model that is configured to receive the touch heatmap, output a force estimation of the touch input based at least on analyzing the touch heatmap, and execute a computing operation based at least on the force estimation. The machine-learning model is trained based at least on training data generated by a training touch interface including a plurality of force sensors.

Touch input force estimation using machine learning

Examples are disclosed relating to computing devices and methods for performing touch detection within a virtual trackpad area of a touch screen display. In one example, a non-trackpad touch input signal is received from outside the virtual trackpad area and processed with at least a jitter restrictor algorithm that applies a non-trackpad distance between reported touch locations. A virtual trackpad touch input signal is received from within the virtual trackpad area. On condition of determining that the virtual trackpad touch input signal is received from within the virtual trackpad area, the virtual trackpad touch input signal is processed with the jitter restrictor algorithm that applies a virtual trackpad distance between reported touch locations that is smaller than the non-trackpad distance between reported touch locations.

Touch screen display with virtual trackpad

A base noise level of a touchscreen interface for a computing device is actively and adaptively calibrated. Antenna traces forming a digitizer of the touchscreen interface are allocated into antenna regions. Antenna regions with high energy signal levels and antenna regions with low energy signal levels are identified. Signal level information from high energy antenna regions is discarded. A noise level, caused by electrical components of the computing device, is determined within signals generated in the antenna traces based at least in part upon the low energy antenna regions. The digitizer is calibrated by reducing energy levels of signals carried by the antenna traces in all antenna regions by the noise level.

Touchscreen sensor calibration using adaptive noise classification

A capacitive touch-sensor system comprises an electrode array coupled to an electromagnetic-noise source, a hardware interface, and associated output logic. The electrode array acquires sensory signal. The hardware interface exposes a touch-position output of the capacitive touch sensor. The output logic determines that an anomalous sensory electrode of the electrode array is proximate to a touchpoint, the anomalous sensory electrode providing an anomalous response to noise from the electromagnetic-noise source. Pursuant to determining that the anomalous sensory electrode is proximate to the touchpoint, the output logic identifies a non-anomalous sensory electrode of the electrode array which is usable to detect the noise. If an amplitude of the sensory signal from the non-anomalous sensory electrode exceeds a predetermined threshold, then the output logic invalidates the sensory signal for touchpoint resolution. If the sensory signal is not invalidated, the output logic computes the touch-position output based in part on the sensory signal.

Touch-sensor accuracy in noisy environments

A method for electronic device identifier assignment at a host computing device includes receiving a current local identifier of a separate electronic device and a full unique identifier of the separate electronic device. A host-specific identifier is assigned to the separate electronic device by, based at least in part on determining that the current local identifier of the separate electronic device is included in a set of local identifier values available for assignment, assigning the host-specific identifier to the separate electronic device with a same local identifier value as the current local identifier. Based at least in part on determining that the current local identifier of the separate electronic device is already assigned by the host computing device to a different separate electronic device, the host-specific local identifier is selected from the set of local identifier values available for assignment and assigned to the separate electronic device.

Assigning device identifiers by host identifier availability

A computing device is provided comprising a processor, a first display device having a first capacitive touch sensor, a second display device having a second capacitive touch sensor, and a hinge positioned between and coupled to each of the first display device and the second display device, the first display device and second display device being rotatable about the hinge and separated by a hinge angle. The processor is configured to detect the hinge angle at a first point in time, determine that the hinge angle at the first point in time is outside a first predetermined range, and upon at least determining that the hinge angle is outside the first predetermined range, perform run-time calibration of at least a plurality of rows of the capacitive touch sensor of the first display device and of the capacitive touch sensor of the second display device.

Hinged dual display computing device

An electronic device samples radiofrequency signals measured by multiple antennas positioned across the digitizer, wherein the radiofrequency signals include noise components. The electronic device selects an orthogonal frequency outside the defined bandwidth of the working frequency and removes at least some of the noise components from the radiofrequency signals measured by each antenna based at least on a sense signal measured at the orthogonal frequency by the each antenna.

Frequency-based noise removal

Examples are disclosed relating to using a spatial noise model to compensate for noise in a frame of touch sensor data. One example provides, on a computing device, a method comprising receiving a noise level for each sensor antenna of a set of sensor antennas of a touch sensor; for each pair of sensor antennas, determining a noise compensation ratio comprising a noise level of a first antenna compared to a noise level of a second antenna; and storing the noise compensation ratio in a spatial noise model.

A method for electronic accessory pairing includes capturing an image of an external environment via a camera communicatively coupled to a host computing device. The image of the external environment is analyzed to detect presence of an imaged electronic accessory. After determining that the host computing device is not presently paired with the imaged electronic accessory, a pairing is established between the host computing device and the imaged electronic accessory.

Accessory pairing based on captured image

A computing device comprises a logic subsystem and a storage subsystem holding instructions executable by the logic subsystem to transmit a first identifier of the computing device to a separate electronic device, the first identifier being transmitted during one time frame of a plurality of sequential time frames. A second identifier of the computing device is transmitted to the electronic device, the second identifier including more data than the first identifier, the second identifier being transmitted over two or more time frames of the plurality of sequential time frames. An electronic pairing is established between the computing device and the electronic device based at least in part on one or both of the first and second identifiers, the electronic pairing enabling receiving of control inputs from the electronic device at the computing device.

Electronic device pairing

The disclosure herein describes changing a mode of operation of a computing device using signals from a pen device. The pen device obtains gesture input data from at least one sensor of the pen device and the obtained gesture input data is compared to at least one gesture pattern. Based on the gesture input data matching the at least one gesture pattern, the pen device transitions to an active state. The pen device detects, via an electrostatic communication channel, an uplink signal from the computing device and sends a signal to change a mode of operation of the computing device by at least one of a network interface or a communication channel, other than the electrostatic communication channel. Changing modes of operation of a computing device provides a flexible, stream-lined way to enhance the user experience of using a computing device with a pen device (e.g., performing an initial pairing process).

Changing a mode of operation of a computing device by a pen device

Examples are disclosed relating to computing devices and methods for performing touch detection within a virtual trackpad area of a touch screen display. In one example, a non-trackpad touch input signal is received from outside the virtual trackpad area and processed with at least one touch detection algorithm applying a non-trackpad threshold value. A virtual trackpad touch input signal is determined to be received from within the virtual trackpad area. On condition of determining that the virtual trackpad touch input signal is received from within the virtual trackpad area, the virtual trackpad touch input signal is processed with the touch detection algorithm applying a virtual trackpad threshold value different from the non-trackpad threshold value.

A touch-screen system comprises adjacent first and second touch-screen sensors, first and second digitizers, and synchronization and return logic. Each of the first and second digitizers is coupled electronically to the respective touch-screen sensor and configured to provide a pen signal responsive to action of a pen on the touch-screen sensor. The synchronization logic is configured to synchronize the pen to the first and second digitizers and to enable pen tracking by any of the first and second digitizers conditionally, based at least partly on the first and second pen signals. The return logic is configured to expose a result of the pen tracking to an operating system of the touch-screen system.

Growing community of inventors

Even Yehuda, Israel

Nadav Linenberg