Abstract: In one aspect, a computerized process useful for movement classification using a motion capture suit includes the step of providing the motion capture suit worn by a user. The motion capture suit comprises a set of position sensors and a Wi-Fi system configured to communicate a set of position sensor data to a computing system. The process includes the step of providing the computing system to: receive a set of position data from the motion capture suit for a specified time window of data comprising X, Y and Z axis positions and a joints-angle data for each position sensor of the set of position sensors, transforming each joints-angle data to a corresponding frequency domain using a fast Fourier transformation to remove any time dependency value, after the fast Fourier data transformation, train a support vector machine using the X, Y and Z axis positions data and the frequency domain data as input, using the support vector machine to predict a set of body positions and movements.

Abstract: In one aspect, a computerized process useful for movement classification using a motion capture suit includes the step of providing the motion capture suit worn by a user. The motion capture suit comprises a set of position sensors and a Wi-Fi system configured to communicate a set of position sensor data to a computing system. The process includes the step of providing the computing system to: receive a set of position data from the motion capture suit for a specified time window of data comprising X, Y and Z axis positions and a joints-angle data for each position sensor of the set of position sensors, transforming each joints-angle data to a corresponding frequency domain using a fast Fourier transformation to remove any time dependency value, after the fast Fourier data transformation, train a support vector machine using the X, Y and Z axis positions data and the frequency domain data as input, using the support vector machine to predict a set of body positions and movements.

Abstract: In one aspect, a computerized method useful for hand movement classification using a motion capture glove includes the step of providing a motion capture glove comprises one or multiple sensors connected to a back of the motion capture glove and one or multiple sensors connected to each finger of the motion capture glove. The method includes the step of, with the one or multiple sensors, measuring a set of physical quantities that describe a motion and a pose of a hand wearing the motion capture glove.

Abstract: In one aspect, a computerized process useful for movement classification using a motion capture suit includes the step of providing the motion capture suit worn by a user. The motion capture suit comprises a set of position sensors and a Wi-Fi system configured to communicate a set of position sensor data to a computing system. The process includes the step of providing the computing system to: receive a set of position data from the motion capture suit for a specified time window of data comprising X, Y and Z axis positions and a joints-angle data for each position sensor of the set of position sensors, transforming each joints-angle data to a corresponding frequency domain using a fast Fourier transformation to remove any time dependency value, after the fast Fourier data transformation, train a support vector machine using the X, Y and Z axis positions data and the frequency domain data as input, using the support vector machine to predict a set of body positions and movements.

Abstract: In one aspect, a computerized process useful for movement classification using a motion capture suit includes the step of providing the motion capture suit worn by a user. The motion capture suit comprises a set of position sensors and a Wi-Fi system configured to communicate a set of position sensor data to a computing system. The process includes the step of providing the computing system to: receive a set of position data from the motion capture suit for a specified time window of data comprising X, Y and Z axis positions and a joints-angle data for each position sensor of the set of position sensors, transforming each joints-angle data to a corresponding frequency domain using a fast Fourier transformation to remove any time dependency value, after the fast Fourier data transformation, train a support vector machine using the X, Y and Z axis positions data and the frequency domain data as input, using the support vector machine to predict a set of body positions and movements.

Abstract: The invention relates to a laryngeal mask (1) comprising at least one airway tube (2) and a mask portion (3), which mask portion (3) comprises a top face (4) and a bottom face (5), said bottom face (5) comprising a lumen (6) that communicates with the tube (2) interior (7), and said top face (4) comprising a closed transition face (8), and said mask portion (3) being at least on the bottom face in the periphery delimited by an inflatable cuff (9), and said mask portion (3) comprising a joint throughout the entire internal circumference of the cuff (9), facing towards the lumen (6) and for providing a closed cuff. Hereby a product is provided which is formed integrally with regard to mask portion and airway tube portion thereby eliminating the risk that the two parts are separated in use.

Abstract: The invention relates to a laryngeal mask (1) comprising at least one airway tube (2) and a mask portion (3), which mask portion (3) comprises a top face (4) and a bottom face (5), said bottom face (5) comprising a lumen (6) that communicates with the tube (2) interior (7), and said top face (4) comprising a closed transition face (8), and said mask portion (3) being at least on the bottom face in the periphery delimited by an inflatable cuff (9), and said mask portion (3) comprising a joint throughout the entire internal circumference of the cuff (9), facing towards the lumen (6) and for providing a closed cuff. Hereby a product is provided which is formed integrally with regard to mask portion and airway tube portion thereby eliminating the risk that the two parts are separated in use.

Abstract: A training apparatus (10) for the practice of puncturing blood vessels includes a model arm and an air-tight, liquid-tight compressible liquid container (19) and a two-way pressure threshold valve for transferring liquid between the container and the model arm. The model arm includes a core (14) of a solid material, a tight-fitting cover (32) of a penetrable material and at least one penetrable tube (31) provided between the core (14) and the cover (32), one end of the tube being connected to the liquid container (19) and the other end being sealed. The liquid container (19) is integrated into the model arm and disposed in such a manner so as to allow it to be compressed by establishing a pressure on a part of the surface of the model arm.