# US 2024/0201793 A1 · Training a gesture recognition model > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2024/0201793 A1 - Document ID: US20240201793A1 - Status: Published application - Kind: A1 - Application number: 18/542,263 - Filed: 2023-12-15 - Published: 2024-06-20 - Earliest claimed: 2022-12-16 - Assignees: TDK Corporation - Applicants: TDK Corporation - Inventors: Rémi Louis Clément PONÇOT; Juan S Mejia SANTAMARIA; Abbas ATAYA; Etienne De FORAS; Bruno FLAMENT - Web page: https://patentgrep.com/patent/US20240201793A1 ## CPC - G06F 3/017: {Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883)} - G01C 21/16: by integrating acceleration or speed, i.e. inertial navigation - G06F 3/011: {Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00)} - G06F 3/0346: with detection of the device orientation or free movement in a three-dimensional [3D] space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) ## Abstract In a method for training a gesture recognition model, gesture data is collected from an inertial measurement unit (IMU) positioned on one side of a user, wherein the IMU is capable of collecting data when positioned on either side of the user. A transformation is applied to the gesture data, wherein the transformation generates transformed gesture data that is independent of either side of the user. A gesture recognition model is trained using the transformed gesture data. ## Claims ### Claim 1 A method for training a gesture recognition model, the method comprising: collecting gesture data from an inertial measurement unit (IMU) positioned on one side of a user, wherein the IMU is capable of collecting data when positioned on either side of the user; applying a transformation to the gesture data, wherein the transformation generates transformed gesture data that is independent of either side of the user; and training a gesture recognition model using the transformed gesture data. ### Claim 2 (depends on 1) The method of claim 1, wherein the transformation comprises a symmetric transformation of accelerometer data of the gesture data and a rotation transformation of gyroscope data of the gesture data. ### Claim 3 (depends on 1) The method of claim 1, wherein the transformation comprises a symmetric transformation of the gesture data for a Y-Z plane of a frame of reference of the IMU and a rotation of 180 degrees of the gesture data around an X-axis of the frame of reference of the IMU. ### Claim 4 (depends on 1) The method of claim 1, further comprising: determining which side of the user on which the IMU is positioned, wherein the transformation is configured to be applied to one side of the user; and provided the IMU is not positioned on the side of the user on which the transformation is configured to be applied, training the gesture recognition model using the gesture data. ### Claim 5 (depends on 4) The method of claim 4, wherein the method is performed for a plurality of IMUs positioned on a plurality of users, such that the gesture recognition model is trained using the gesture data for at least one user and the transformed gesture data for at least one user. ### Claim 6 (depends on 1) The method of claim 1, wherein the transformation comprises an absolute value transformation. ### Claim 7 (depends on 6) The method of claim 6, wherein the transformation comprises an absolute value symmetric transformation of accelerometer data of the gesture data and an absolute value rotation transformation of gyroscope data of the gesture data. ### Claim 8 (depends on 6) The method of claim 6, wherein the transformation comprises an absolute value symmetric transformation of the gesture data for a Y-Z plane of a frame of reference of the IMU and an absolute value rotation transformation of 180 degrees of the gesture data around an X-axis of the frame of reference of the IMU. ### Claim 9 (depends on 1) The method of claim 1, further comprising: deploying the gesture recognition model to a user device. ### Claim 10 A wearable system utilizing gesture recognition, the system comprising: an inertial measurement unit (IMU) positioned on one side of a user for collecting gesture data based on movement of the IMU; a gesture recognition model trained on one side of the user; and a processing unit for performing gesture recognition using the gesture data, the processing unit configured to: determine a side of the user on which the IMU is positioned; provided the IMU is positioned on an opposite side of the user on which the gesture recognition is trained, applying a transformation to the gesture data, wherein the transformation transforms the gesture data such that transformed gesture data is transformed to a side of the user on which the gesture recognition model is trained; and performing gesture recognition using the transformed gesture data. ### Claim 11 (depends on 10) The system of claim 10, wherein the transformation comprises a symmetric transformation of accelerometer data of the gesture data and a rotation transformation of gyroscope data of the gesture data. ### Claim 12 (depends on 10) The system of claim 10, wherein the transformation comprises a symmetric transformation of the gesture data for a Y-Z plane of a frame of reference of the IMU and a rotation of 180 degrees of the gesture data around an X-axis of the frame of reference of the IMU. ### Claim 13 A wearable system utilizing gesture recognition, the system comprising: an inertial measurement unit (IMU) positioned on one side of a user for collecting gesture data based on movement of the IMU; a gesture recognition model that is trained independent of which side of the user the IMU is positioned; and a processing unit for performing gesture recognition using the gesture data, the processing unit configured to: applying a transformation to the gesture data, wherein the transformation is an absolute value transformation that transforms the gesture data such that transformed gesture data is independent of which side of the user the IMU is positioned; and performing gesture recognition using the transformed gesture data. ### Claim 14 (depends on 13) The system of claim 13, wherein the transformation comprises an absolute value transformation. ### Claim 15 (depends on 14) The system of claim 14, wherein the transformation comprises an absolute value symmetric transformation of accelerometer data of the gesture data and an absolute value rotation transformation of gyroscope data of the gesture data. ### Claim 16 (depends on 14) The system of claim 14, wherein the transformation comprises an absolute value symmetric transformation of the gesture data for a Y-Z plane of a frame of reference of the IMU and an absolute value rotation transformation of 180 degrees of the gesture data around an X-axis of the frame of reference of the IMU. ### Claim 17 A non-transitory computer readable storage medium having computer readable program code stored thereon of a method for training a gesture recognition model, the method comprising: collecting gesture data from inertial measurement units (IMUs) positioned on one side of a plurality of users, wherein the IMUs are capable of collecting data when positioned on either side of the plurality of users; determining which side of the user on which the IMU is positioned, wherein a transformation is configured to be applied to a first side of the user; and provided the IMU is positioned on the first side of the user on which the transformation is configured to be applied, applying a transformation to the gesture data, wherein the transformation transforms the gesture data such that transformed gesture data is representative of data collected from an IMU positioned on a second side of the user; and training a gesture recognition model using the gesture data received from an IMU positioned on the second side of the user and the transformed gesture data for the gesture data received from an IMU positioned on the first side of the user. ### Claim 18 (depends on 17) The computer readable storage medium of claim 17, wherein the transformation comprises a symmetric transformation of accelerometer data of the gesture data and a rotation transformation of gyroscope data of the gesture data. ### Claim 19 (depends on 17) The computer readable storage medium of claim 17, wherein the transformation comprises a symmetric transformation of the gesture data for a Y-Z plane of a frame of reference of the IMU and a rotation of 180 degrees of the gesture data around an X-axis of the frame of reference of the IMU. ### Claim 20 (depends on 17) The computer readable storage medium of claim 17, the method further comprising: deploying the gesture recognition model to a user device.