Nokia Technologies Oy

Harri Lindholm

Mikko Johannes Honkala

Kim Blomqvist

Satu Rajala

Tapio Taipalus

Michael Woldegebriel

Akos Vetek

Leo Karkkainen

Alessandra Sala

Alice Marascu

Kiti Müller

Leo Karkkaien

The application relates to apparatus, methods and computer programs for determining pulse wave velocity, The apparatus includes circuitry configured for: receiving a first ballistocardiograph signal indicative of a pulse wave travelling in a first direction at a first time, the pulse wave having a pulse velocity and receiving a second ballistocardiograph signal indicative of the pulse wave travelling in a second direction at a second time, wherein the second direction is, at least partially, perpendicular to the first direction. The circuitry is also configured for determining the pulse wave velocity based one the first ballistocardiograph signal and the second ballistocardiograph signal.

Apparatus, methods and computer programs for determining pulse wave velocity

A method of detection of a recurrent feature of interest within a signal including: obtaining evidence, based on a signal, the evidence including a probability density function for each of a plurality of parameters for parameterizing the signal, including at least one probability density function for a parameter, of the plurality of parameters, that positions a feature of interest within signal data of the signal; parameterizing a portion of the signal data from the signal based upon a hypothesis that a point of interest in the signal data is a position of the feature of interest; determining a posterior probability of the hypothesis being true given the portion of the signal data by combining a prior probability of the hypothesis and a conditional probability of observing the portion of the signal data given the hypothesis.

Determining whether a hypothesis concerning a signal is true

An apparatus and a method are described in which a signal is received from a gyroscope sensor mounted on a subject. The gyroscope sensor is configured to measure rotational movement of the subject's heart, the signal being indicative of a left ventricular twist of the subject's heart. A change in the left ventricular twist of the subject's heart caused by occlusion of blood flow by an arterial occlusion device configured to selectively occlude blood flow of the subject is determined.

Apparatus and method for determining a change in left ventricular twist of a subject's heart

An apparatus, method and computer program is described comprising: receiving interaction information via at least one user device, wherein the interaction information is related to at least one user using at least one user device in relation to a first content creation task; receiving sensor data relating to the at least one user from one or more sensors; and determining data, using a first model, the data comprising content creation performance data and user state data, wherein: the content creation performance data indicates performance of the at least one user in relation to the first content creation task, based, at least in part, on the interaction information and a first content created when the at least one user performs the first content creation task; and the user state data is based, at least in part, on the received sensor data in relation to the first content creation task.

User interaction

An apparatus including circuitry configured to determine a probability by combining at least: a probability that an event is present within a current feature of interest given a first set of previous features of interest, and a probability that the event is present within the current feature of interest given a second set of previous features of interest, different to the first set of previous features of interest; circuitry configured to detect the event based on the determined probability; and circuitry configured to control, in dependence on the detection of the event, performance of an action.

Probability-based detector and controller apparatus, method, computer program

A method, apparatus and computer program, the method comprising: receiving a first biopotential signal obtained by a first capacitive sensor; receiving a second biopotential signal obtained by a second capacitive sensor, the first capacitive sensor and the second capacitive sensor being positioned at different locations on a subject; synchronising biopotential signals obtained by the first capacitive sensor and the second capacitive sensor by applying a time adjustment to biopotential signals obtained by at least one of the first capacitive sensor or the second capacitive sensor; wherein features in at least one of the first biopotential signal and the second biopotential signal are used to synchronise the biopotential signals obtained by the first capacitive sensor and the second capacitive sensor.

Method, apparatus and computer program for synchronizing biopotential signals

An approach is provided for synchronizing an impedance cardiography ('ICG') measurement period with an electrocardiography ('ECG') signal to reduce patient () auxiliary current. The approach involves measuring an ECG signal of a patient via an ECG device (). The approach also involves processing the ECG signal to cause, at least in part, a detection of one or more ECG features of the signal. The approach further involves synchronizing a start, a stop, or a combination thereof of a measurement of an ICG signal of the patient via an ICG device () based, at least in part, on the detection of the one or more ECG features. The measurement of the ICG signal includes injecting an electrical current into the patient () for a duration of the measurement.

Method and apparatus for synchronizing impedance cardiography with electrocardiography to lower patient auxiliary current

An apparatus configured to generate an output quality error estimate using a machine-learning error estimation model to compare an output meeting a predetermined quality threshold with an output image reconstructed from a plurality of images, and provide the output quality error estimate for use in estimating if a second subsequent image is required, in addition to a first subsequent image to obtain a cumulative output having an output quality error meeting a predetermined error threshold. Also an apparatus configured, using a received output quality error estimate generated using a machine-learning error estimation model as above, to estimate if a second subsequent image is required, in addition to a first subsequent image, to obtain a cumulative output having an output quality error meeting a predetermined error threshold.

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Helsinki, Finland

Harri Lindholm