Maxell, Ltd.

Hitachi, Ltd.

Hitachi Consumer Electronics Co., Ltd.

Hitachi Maxell, Limited

Fujifilm Healthcare Corporation

Hitachi Computer Peripherals Co., Ltd.

Yuko Sano

Akihiko Kandori

Mitsunobu Watanabe

Tsuyoshi Miyashita

Mitsuo Okimoto

Shigemitsu Ando

Tomohiko Mizuguchi

Yuhua Zhang

Kenji Takeda

Ryuzo Kawabata

Toshio Tsuji

Yuuji Nagashima

Ying Yin

Mitsuru Onuma

Kuniomi Ogata

Kanako Esaki

Takako Mizoguchi

Keisuke Shima

Taichi Nomura

Kenichirou Beppu

Hiroshi Shimizu

Atsushi Ninomiya

Kenji Katsumata

Yusuke Seki

Kazuhiro Kaizaki

Takumi Okamura

Toshinori Miyoshi

Tomochika Yamashita

Nobutaka Abe

Tamotsu Nagabayashi

Norihiko Adachi

Kouichi Ishizuka

Yasushi Saito

Saburo Sakoda

Masaru Yokoe

Yasuhiro Tamura

Takafumi Shimamoto

Harutoyo Hirano

Toshiroh Shibata

Toshihiro Aita

Akitoshi Doi

Shinya Katsuki

Katsuya Morohoshi

The abnormal data processing system is provided with: a storage unit for holding a multiple-subject DB in which data on multiple subjects are accumulated and individual-subject DB in which data on individual subjects are accumulated; an individual-subject DB divergence-degree calculation unit for calculating an individual-subject DB divergence degree which is the degree of divergence of the new data from the individual-subject DB; a multiple-subject DB divergence degree calculation unit for calculating a multiple-subject DB divergence degree which is the degree of divergence of the new data from the multiple-subject DB; and a composite divergence degree calculation unit for determining a composite divergence by compositing the individual-subject DB divergence degree and the multiple-subject DB divergence degree using the number of data instances in the individual-subject DB. The abnormal data processing system determines whether or not the new data is abnormal on the basis of the composite divergence degree.

Abnormal data processing system and abnormal data processing method

A technique for evaluating human cognitive and motor functions by a plurality of hand movement tasks is disclosed. A task execution method determines the execution order of a plurality of tasks which a test subject is caused to execute to acquire a characteristic quantity. A test subject group task database includes scores given in advance and characteristic quantities obtained from a plurality of tasks stored as past data corresponding to each of a plurality of test subjects. In a storage device, (1) a differentiation precision database for a case in which test subjects are divided into two groups by predetermined threshold value scores differentiated by the characteristic quantities, or (2) an estimation precision database for a case in which a score is estimated using the characteristic quantity for a predetermined score value is prepared for each of the tasks on the basis of the test subject group task database.

Task execution order determination system and task execution method

A system for evaluating a degree of brain dysfunction of a subject, such as a decline in cognitive function, calculates a difference in movement functions between both hands in a coordination movement. The system includes a storage device for storing time-series data on a finger movement task of each of both hands of a test subject acquired by a movement sensor; a data processing device for analyzing the time-series data stored in the storage device; and a display device for displaying an analysis result analyzed by the data processing device. The data processing device includes a movement waveform generation unit for generating a movement waveform corresponding to the time-series data stored in the storage device; and a difference-between-hands feature quantity generation unit for generating a difference-between-hands feature quantity which represents a difference in respective finger movement tasks between both hands, based on the respective movement waveforms of both hands.

Brain dysfunction evaluation system, brain dysfunction evaluation method, and program

The objective of the present invention is to provide a hardness meter which estimates hardness in a stable manner regardless of a compression strength. A hardness meter includes: a movable portion which is continuously pressed against an object to be measured; a sensor which outputs an output signal reflecting a reaction force at a part of the object to be measured; a motive force mechanism that causes the movable portion to perform a piston motion; a hardness estimating portion which estimates the hardness of the object on the basis of an alternating current component of the output signal, generated by the piston motion; a position estimating portion which estimates a measurement position information by shooting with a camera; and a hardness map display portion which maps and displays the hardness on a schematic diagram of the surface of a living body based on the measurement position information.

Hardness meter and hardness measuring method for estimating target object having hardness estimation portion that estimates hardness of measurement object based

An object of the present invention is to provide a durometer enabling a contact portion in contact with an object to perform smooth piston motion. The durometer includes a main body unit including a movable unit pressed continuously against an object to be measured, a first sensor outputting acceleration information corresponding to an acceleration of movement of a contact part of the object to be measured in contact with the movable unit in a pressing direction, a second sensor outputting reactive force information corresponding to a reactive force at the contact part of the object to be measured in contact with the movable unit, a motor, a crank mechanism driven by the motor and causing the main body unit and the movable unit to perform piston motion, and at least one buffering member disposed on a periphery of the main body unit.

Durometer

A training apparatus is capable of generating and presenting a suitable training menu for finger exercise to maintain or improve a cognitive function and/or an exercise function of a human and supporting training of the human. The training apparatus includes a measuring apparatus and a terminal device. Analysis evaluating data based on measurement of the finger exercise including finger tapping is obtained, and the analysis evaluating data contains an evaluation value of an index item related to an exercise function of a user. A training menu for the user is generated based on the analysis evaluating data and contains a training item for the finger exercise. The index item includes at least one of an amount of exercise, endurance, rhythmicity, cooperativeness of both sides, or marker trackability. The training item includes an exercise to carry out the finger tapping in accordance with teaching information, stimulation, or a marker.

Finger exercise training menu generating system, method thereof, and program thereof

The accuracy of an intervention site in surgery is predicted and the predicted intervention site is presented to a surgeon. A surgery support apparatus includes a prediction data generation unit that generates prediction data predicting an intervention site based on data before an intervention using an artificial intelligence algorithm. The artificial intelligence algorithm is an artificial intelligence algorithm learning an intervention site by analyzing data before the intervention and intervention site data for an object, and outputs coordinates, a region, or a shape of one point of the intervention site as prediction data. Data before the intervention used for learning of the artificial intelligence algorithm and input data input to the artificial intelligence algorithm to generate prediction data correspond to image data, a segment image, a feature point, etc. The prediction data is displayed on a display apparatus together with an image of a patient acquired in advance.

Surgery support apparatus and surgical navigation system

The objective of the present invention is to provide a hardness meter which estimates hardness in a stable manner regardless of a compression strength. Disclosed is a hardness meter characterized in being provided with: a movable portion which is continuously pressed against an object to be measured; a sensor which outputs an output signal reflecting a reaction force at a part of the object to be measured that is in contact with the movable portion; a motive force mechanism that causes the movable portion to perform a piston motion; and a hardness estimating portion which estimates the hardness of the object to be measured on the basis of an alternating current component of the output signal, generated by the piston motion of the movable portion.

Hardness meter and method having hardness estimation portion that estimates hardness of measurement object based on alternating current component

The present invention addresses the problem of limiting power consumption and radio wave interference when assessing the movements of multiple sites of a living body. The present invention is a movement function assessment system provided with: a movement function measurement apparatus for calculating movement data on the basis of the relative distances of pairs of transmission coils and reception coils attached to movable portions of a living body; and an assessment apparatus for assessing the movement function of the living body on the basis of the movement data received from the movement function measurement apparatus. A control unit of the movement function measurement apparatus performs the switching of the multiple transmission coils by a switching unit (1) and the switching of the multiple reception coils by a switching unit (2) so that the paired transmission coils and reception coils are operated sequentially.

Movement function assessment system and movement function measurement apparatus

A system for evaluating the degree of brain dysfunction of a subject, such as a decline in cognitive function, calculates a difference in movement functions between both hands in a coordination movement. The system includes a storage device for storing time-series data on a finger movement task of each of both hands of a test subject acquired by a movement sensor; a data processing device for analyzing the time-series data stored in the storage device; and a display device for displaying an analysis result analyzed by the data processing device. The data processing device includes a movement waveform generation unit for generating a movement waveform corresponding to the time-series data stored in the storage device; and a difference-between-hands feature quantity generation unit for generating a difference-between-hands feature quantity which represents a difference in respective finger movement tasks between both hands, based on the respective movement waveforms of both hands.

The present invention solves a problem that there may be a case that an estimated value of regression cannot be calculated depending on a discrimination result when a regression method is applied after a discrimination method, and has a purpose to obtain an estimating equation with high accuracy even when the number of sample groups to which the regression method is applied is small. An estimating equation that satisfies the regression and discrimination at the same time can be obtained by combining a discrimination evaluation function that evaluates discrimination accuracy and a regression evaluation function that evaluates regression accuracy, calculating a combination evaluation function, and optimizing the combination evaluation function.

Regression analysis system and regression analysis method that perform discrimination and regression simultaneously

The present invention provides a sphygmomanometer system, including a measurement device pressed against a predetermined part to be measured so that the part to be measured is held down, and a blood pressure measurement device to measure blood pressure based on information from the measurement device. The measurement device includes an average blood pressure detection unit to obtain information on pressure applied to the measurement device, and a blood pressure change amount detection unit to detect a minute change of the part to be measured when the blood pressure change amount detection unit contacts with the part to be measured. The processor of the blood pressure measurement device calculates the average blood pressure, the highest blood pressure, and the lowest blood pressure based on information on pressure obtained from the blood pressure change amount detection unit and the average blood pressure detection unit.

Sphygmomanometer system

Growing community of inventors

Tokyo, Japan

Yuko Sano