Technologies disclosed herein are directed to enforcing blocking functionality on a mobile device (e.g., a mobile device within a vehicle). The mobile device receives a request to disable a blocking of a user interaction with one or more functions of the mobile device. The mobile device prompts a capture of an image by a camera of the mobile device. The mobile device determines whether the image is captured from a passenger space in the vehicle. Once so determined, the mobile device disables the blocking of the user interaction with the one or more functions of the mobile device.

The technical solution relates to control systems, more particularly to systems and methods of generating control commands based on operator's bioelectrical data. One more technical result of the present technical solution is the increase of identification accuracy of the Operator's actions. One more technical result of the present technical solution is the improvement of identification of the Operator's actions due to the elimination of artefacts from the Operator's bioelectrical data.

The invention described provides a way to use video image to estimate the human artery blood pressure reducing or completely eliminating the need for human contact (non invasive). Since video images can be stored and transmitted, the estimation of the blood pressure can be performed locally, remotely and in real time or offline.

User interaction concepts, principles and algorithms for gestures involving facial expressions, mental activity, and other body actions are disclosed. User interaction concepts, principles and algorithms for enabling hands-free and voice-free interaction with electronic devices are disclosed. Apparatuses, systems, computer implementable methods, and non-transient computer storage media storing instructions, implementing the disclosed concepts, principles and algorithms are disclosed. Gestures for systems using eye gaze and head tracking that can be used with augmented, mixed or virtual reality, mobile or desktop computing are disclosed. Use of periods of limited activity and consecutive body actions in orthogonal axes is disclosed.

The present disclosure provides a system and method for PET image reconstruction. The method may include processes for obtaining physiological information and/or rigid motion information. The image reconstruction may be performed based on the physiological information and/or rigid motion information.

A motion measurement apparatus according to an embodiment of the present technology includes a controller unit. The controller unit extracts, from an acceleration in each direction of three axes that includes a dynamic acceleration component and a static acceleration component of a detection target that moves within a space, the dynamic acceleration component of the detection target, and generates, as a control signal, a change in kinematic physical quantity of a posture of the detection target from the dynamic acceleration component.

A method for operating a data processing system to find peaks in a mass spectrum that includes an ordered set of measurements of the abundances of species as a function of the mass/charge ratio of the species is disclosed. The method includes selecting a candidate blob that has a plurality of blob peaks from the mass spectrum. The data processing system selects a candidate blob peak for characterization. The candidate blob peak is approximated by a first species peak using a species peak model having a plurality of parameters by fitting the species peak model to a portion of the blob that has values that are substantially free of contributions from other species peaks that overlap with the first species peak and that are not represented by the species peak model. The first species peak is then subtracted from the candidate blob.

A first observation window in a first time series is identified. The first observation window is preceded by a first portion of the first time series. A neural network is trained using the first portion of the first time series and the first observation window, and weights are extracted from the middle layers of the neural network. A first feature vector is generated based on the weights. A second observation window in a second time series is identified, where the second observation window is preceded by a first portion of the second time series. A second feature vector associated with the second observation window is determined. The second feature vector is based at least in part on the first set of weights. A similarity between the first and second observation windows is determined based on comparing the first feature vector and the second feature vector.

A fingerprint identification module includes a substrate, a fingerprint sensor die, a covering adhesive layer, a cover plate and a mold compound layer. The fingerprint sensor die is attached on the substrate for sensing a fingerprint image. The covering adhesive layer is formed on a top surface of the fingerprint sensor die. The cover plate is attached on the covering adhesive layer. The mold compound layer is formed over the substrate. The fingerprint sensor die, the covering adhesive layer and the cover plate over the substrate are molded together through the mold compound layer, and the cover plate is exposed. The fingerprint identification module has small thickness and enhanced sensing accuracy.

A method and associated apparatus combine a calculation of chaos of a quantifiable cardiac characteristic associated with a patient with a measurement of a non-increasing parasympathetic activity of the patient to detect a physiological abnormality of the patient.