Abstract: An aspect of the present invention is a state estimation device including a cardiac state time series acquisition unit that acquires a cardiac state time series that is a time series of a cardiac state quantity that is a quantity indicating a state of a heart as an estimation target, and a cardiac state estimation unit that estimates a state of the heart as the estimation target based on an occurrence time of out-of-range data, using, as the out-of-range data, a non-responsive period sample whose value is outside a threshold region of processing determined according to a distribution of the non-responsive period sample among non-responsive period samples that are non-responsive period samples among samples of the cardiac state time series acquired by the cardiac state time series acquisition unit.

Abstract: A lipid bimolecular membrane substrate 1A includes: a substrate 12 in which a microwell 20 opened on one surface is formed; a lipid bimolecular membrane 30 disposed on the substrate 12 so as to cover an opening of the microwell 20; and a sealing liquid 22 disposed between the substrate 12 and the lipid bimolecular membrane 30. The sealing liquid 22 contains an ionic liquid.

Abstract: A state estimation device includes an information acquisition unit acquiring at least one of (i) electrode acquisition information indicating an electromagnetic time series that is a time series of an electromagnetic quantity that is an electromagnetic force, field, or energy applied to an electrode from which a signal indicating a state of a heart of an estimation target is acquirable or (ii) environment information that is information on a time series of an environmental quantity that is an amount related to one or both of a state of motion of the estimation target and an environment in which the estimation target is present; and an estimation unit using at least one of the electrode acquisition information or the environment information to determine whether an electrode event, which is an abnormality in acquisition of a signal indicating the state of the heart of the estimation target by the electrode, has occurred.

Abstract: A rotation state of an object obtained from an input video of a plurality of frames in time series is estimated by using an object image obtained by excluding at least a part of a region common to the plurality of frames from an image corresponding to the object.

Abstract: A target estimation image which is an image of a target at a time point t+w·u obtained by spinning the object in an object image at a time point t obtained from an input video of a plurality of frames in time-series by w unit time on the basis of a hypothesis of spin state and an object image at the time point t+w·u obtained from the input video are used, to estimate the spin state of the object by selecting a hypothesis of spin state and w in which likelihood of the target estimation image becomes high from among a plurality of hypotheses of spin states and a plurality of w whose absolute values are two or more, wherein an absolute value of w is an integer of 2 or more and u is a unit time.

Abstract: A target estimation image which is an image of a target at a time point t+w·u obtained by spinning the object in an object image which is an image of the object at a time point t obtained from an input video in time-series by w unit time on the basis of a hypothesis of spin state and an object image at the time point t+w·u obtained from the input video are used, to estimate a spin state of the object by selecting a hypothesis of spin state and w in which likelihood of the target estimation image becomes high from among a plurality of hypotheses of spin states and a plurality of w, wherein an absolute value of W is an integer of 1 or more and u is a unit time.

Abstract: Information for displaying information representing rotation axes of balls seen from a first point side or a second point side in regard to one or more motions of the balls moving from the first point side to the second point side is output, and information for displaying information representing rotation axes of the balls seen from an outer side located in a direction that is orthogonal to a virtual straight line connecting the first point to the second point in regard to the motions is output.

Abstract: An aspect of the present invention is an electrode stack array including: a planar substrate; and a plurality of electrode stacks, each electrode stack including a sacrificial layer that is stacked on the planar substrate, a bent layer that is stacked on the sacrificial layer and is capable of bending such that a surface on a side opposite to a surface on a side of the sacrificial layer becomes an inner side, and a conductive layer that is disposed on the bent layer.

Abstract: Provided is an optical waveguide device (100) including a substrate (3) formed into a plate shape, a soft material (2) having swellability, formed into a film shape, and provided on a side of one surface of the substrate, a pair of adhesive regions (B1), formed at an interface between the substrate and the soft material, in which the substrate and the soft material are adhered to each other, a non-adhesive region (B2) formed so that the substrate and the soft material are not adhered to each other between the pair of adhesive regions, a protruding part (2B) in which a channel is formed so as to protrude in the non-adhesive region in the soft material, a liquid (W) filled into the channel and having a higher refractive index than the soft material, a pair of liquid feed tubes (8) connected to both ends of the channel, and a pair of optical fibers (9) inserted into the pair of liquid feed tubes respectively, wherein an optical waveguide is formed in the protruding part, and the optical waveguide includes a clad

Abstract: A motion evaluation method includes: a noise removal step of removing noise in time-series data related to a motion of a person; an extraction step of extracting data of an on-set section in which the motion of the person is performed from the time-series data from which the noise has been removed; a compression step of aligning a length of the extracted data of the on-set section for each on-set section and compressing the data of the on-set section through down-sampling processing; and an evaluation step of evaluating the motion of the person on the basis of the compressed data of the on-set section.

Abstract: A biological information analysis system includes a data reception unit that receives time-series data of biological information from a sensor terminal that acquires biological information, a storage unit that stores the received time-series data, a first representative value acquisition unit that acquires a first representative value based on data in a predetermined period among the received time-series data, and a second representative value acquisition unit that acquires a second representative value based on a plurality of first representative values consecutive on a time axis. In a case where an error occurs in communication between the data reception unit and the sensor terminal and a predetermined condition is satisfied, the first representative value acquisition unit uses pre-error time-series data transmitted before the error occurs and stored in the storage unit and post-error time-series data transmitted from the sensor terminal after the error occurs, to acquire the first representative value.

Abstract: An aspect of the present invention is a loss-of-consciousness estimation apparatus including: a ventricular state estimation unit configured to estimate whether or not a ventricular state of an estimation target is normal in a predetermined repetition cycle, based on a cerebral blood flow correlation amount time series, which is a time series of an amount correlated with a cerebral blood flow rate of the estimation target; a measurement reliability estimation unit configured to estimate reliability of the cerebral blood flow correlation amount time series; and a loss-of-consciousness probability acquisition unit configured to, based on the reliability, the estimation result of the ventricular state estimation unit, and elapsed time after a probability acquisition start time, which is a time at which it is first determined by the ventricular state estimation unit that the ventricular state is not normal after an estimation start time, which is a time of starting the repetition cycle, acquire a loss-of-consciou

Abstract: An aspect of the present invention is a loss-of-consciousness estimation apparatus including: an out-of-range data determination unit configured to execute out-of-range data determination processing for, using an amount correlated with a cerebral blood flow rate of an estimation target as a cerebral blood flow correlation amount, a time series of the cerebral blood flow correlation amount as a cerebral blood flow correlation amount time series, and a position in a time axis direction of data of the cerebral blood flow correlation amount time series as a time position, determining whether or not the cerebral blood flow correlation amount indicated by each piece of the data is out of range of a threshold region, which is a range corresponding to the time position of each piece of the data, based on the cerebral blood flow correlation amount time series; and a ventricular state estimation unit configured to estimate a ventricular state of the estimation target based on the determination result of the out-of-rang

Abstract: A learning-type signal separation method performed using a model formulation unit, which performs learning processing based on a training-use signal including a specific component, and a training-use signal not including the specific component, the training-use signals including a common characteristic. The learning-type signal separation method includes: generating learned data by causing the model formulation unit to perform learning processing based on the training-use signal and information indicating whether or not the specific component is included in the training-use signal, to generate a data series signal in which the specific component has been separated and removed from a data series of the training-use signal; acquiring an arbitrary signal including the common characteristic; and generating, based on the acquired arbitrary signal and the generated learned data, a data series signal in which the specific component has been separated and removed from a data series of the arbitrary signal.

Abstract: In an emotion stabilization support device including a portable vibration generator including an oscillator (36), a motion sensor (37), and a control unit (31), the control unit (31) causes the oscillator (36) to intermittently vibrate, and the control unit (31) measures a state of the portable vibration generator detected by the motion sensor (37) and determines a state of an emotion of a user.

Abstract: This cooling apparatus includes a tube (10) having an opening portion (10a) in one end portion in a longitudinal direction thereof, a cap (30) capable of opening/closing the opening portion (10a), a non-freezing drinkable coolant (20) that fills the tube (10), and a container (50) that contains the tube (10) filled with the coolant (20). The tube has a constricted portion (10d) having a reduced inner diameter.

Abstract: A kinetic motion learning device includes an information storage unit configured to associate and store in advance a pitching motion video and pitching trajectory information for a plurality of pitches actually delivered by a pitcher on a potential opponent team, and is configured to read a set of the pitching motion video and the pitching trajectory information stored in the information storage unit, output the pitching motion video being read to a projector, output the pitching trajectory information being read to a pitching machine, and control motion timings of the projector and the pitching machine so that a time of ball release of the pitcher in the pitching motion video displayed on a screen and a time of the pitching machine launching the ball with the pitching trajectory information match. The projector is configured to project the pitching motion video onto the screen so that the pitching motion video is displayed on the screen at a motion timing controlled by the kinetic motion learning device.

Abstract: A time-series-data feature extraction device includes: a data processing unit that processes a received unevenly spaced time-series-data group into an evenly spaced time-series-data group including omissions and an omission information group indicating presence or absence of omissions, based on a received input time-series data length and a received minimum observation interval; a model learning unit that learns a weight vector of each layer of a model with a difference between an element not missing in a matrix of the evenly spaced time-series-data group including omissions and an element of an output result of an output layer of the model being taken as an error, and stores the weight vector as a model parameter in a storage unit, the difference being; and a feature extraction unit that receives time-series data of a feature extraction target, calculates a value of the intermediate layer of the model with use of the model parameter stored in the storage unit by inputting the received time-series data of the

Abstract: A learning-type signal separation method performed using a model formulation unit, which performs learning processing based on a training-use signal including a specific component, and a training-use signal not including the specific component, the training-use signals including a common characteristic. The learning-type signal separation method includes: generating learned data by causing the model formulation unit to perform learning processing based on the training-use signal and information indicating whether or not the specific component is included in the training-use signal, to generate a data series signal in which the specific component has been separated and removed from a data series of the training-use signal; acquiring an arbitrary signal including the common characteristic; and generating, based on the acquired arbitrary signal and the generated learned data, a data series signal in which the specific component has been separated and removed from a data series of the arbitrary signal.

Abstract: A time-series-data feature extraction device includes: a data processing unit that processes a received unevenly spaced time-series-data group into an evenly spaced time-series-data group including omissions and an omission information group indicating presence or absence of omissions, based on a received input time-series data length and a received minimum observation interval; a model learning unit that learns a weight vector of each layer of a model with a difference between an element not missing in a matrix of the evenly spaced time-series-data group including omissions and an element of an output result of an output layer of the model being taken as an error, and stores the weight vector as a model parameter in a storage unit, the difference being; and a feature extraction unit that receives time-series data of a feature extraction target, calculates a value of the intermediate layer of the model with use of the model parameter stored in the storage unit by inputting the received time-series data of the