# US 10,441,848 B1 · System for automatic evaluation of martial arts moves > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,441,848 B1 - Document ID: US10441848B1 - Status: Granted - Kind: B1 - Application number: 16/168,959 - Filed: 2018-10-24 - Granted: 2019-10-15 - Earliest claimed: 2018-10-24 - Applicants: Anna Skhisov; Eduard Skhisov; Daniel Skhisov - Inventors: Anna Skhisov; Eduard Skhisov; Daniel Skhisov - Web page: https://patentgrep.com/patent/US10441848B1 ## CPC - A63B 24/0006: {Computerised comparison for qualitative assessment of motion sequences or the course of a movement} - 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 - A63B 24/0062: {Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance} - A63B 69/32: with indicating devices - G01P 3/68: using optical means, i.e. using infrared, visible, or ultraviolet light (G01P3/80 takes precedence {; by reflection of waves G01S17/58}) - 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)} - G06F 3/0304: {Detection arrangements using opto-electronic means (constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042)} - G06N 20/00: Machine learning - A63B 2024/0012: {Comparing movements or motion sequences with a registered reference} - A63B 2024/0065: {Evaluating the fitness, e.g. fitness level or fitness index} - A63B 2024/0071: {Distinction between different activities, movements, or kind of sports performed} - A63B 2244/10: Combat sports - A63B 2244/106: Karate - G01P 7/00: Measuring speed by integrating acceleration (measuring travelled distance by double integration of acceleration G01C21/16) - G01P 15/18: in two or more dimensions - A63B: APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT (apparatus for passive exercising, massage A61H) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G01P: MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT (measuring or recording blood flow A61B5/02, A61B8/06; monitoring speed or deceleration of electrically-propelled vehicles B60L3/00; vehicle lighting systems adapted to indicate speed B60Q1/54; determining position or course in navigation, measuring ground distance in geodesy or surveying G01C; combined measuring devices for measuring two or more variables of movement G01C23/00; measuring velocity of sound G01H; measuring velocity of light G01J7/00; measuring direction or velocity of solid objects by reception or emission of radiowaves or other waves and based on propagation effects, e.g. Doppler effect, propagation time, direction of propagation, G01S; measuring speed of nuclear radiation G01T; measuring acceleration of gravity G01V; {measuring or recording the speed of trains B61L23/00; speed indicators incorporated in motor vehicles B60K35/00; measuring frequency or phase G01R; traffic control G08G}) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Methods, systems, and devices for automatically evaluating a martial arts move are described. The method may include identifying a distance between a target and a sensor coupled with a user and receiving motion data from the sensor. The motion data may include linear acceleration data and rotation data. The method may further include calculating, based on the distance and the linear acceleration data, an end point in three-dimensional space of the martial arts move and determining whether the user made contact with the target based on a comparison between the end point and a three-dimensional representant of the target. The method may further include determining a rotational characteristic of the move and comparing the rotational characteristic with a stored model of the move. The method may further include evaluating the move based on whether the user made contact with the target and the comparison of the rotational characteristic. ## Claims ### Claim 1 A method of evaluating a martial arts move, comprising: identifying a distance between a target and a nine degree of freedom (DOF) sensor coupled with a user; receiving motion data from the nine DOF sensor, wherein the motion data comprises three-dimensional linear acceleration data as a function of time and three-dimensional rotation data as a function of time; calculating, based at least in part on the distance and the three-dimensional linear acceleration data, an end point in three-dimensional space of the martial arts move; determining whether the user made contact with the target based at least in part on a comparison between the end point and a three-dimensional representation of the target; calculating, based at least in part on the three-dimensional rotation data, a rotational characteristic of the martial arts move; comparing the rotational characteristic of the martial arts move to a stored model gesture corresponding to the martial arts move; evaluating the martial arts move based at least in part on whether the user made contact with the target and the comparison of the rotational characteristic; and transmitting an indication of the evaluation of the martial arts move to a user device. ### Claim 2 (depends on 1) The method of claim 1, further comprising: receiving training motion data from a second nine DOF sensor coupled with an authorized user, wherein the training motion data comprises training three-dimensional linear acceleration data as a function of time and training three-dimensional rotation data as a function of time; storing a plurality of sets of training motion data received from the authorized user; analyzing the training three-dimensional rotation data from the plurality of sets of training motion data using a machine learning model; and determining the stored model gesture corresponding to the martial arts move based at least in part on the analysis of the training three-dimensional rotation data. ### Claim 3 (depends on 1) The method of claim 1, further comprising: determining a contact location on the target based at least in part on the end point and the three-dimensional representation of the target. ### Claim 4 (depends on 3) The method of claim 3, wherein evaluating the martial arts move is further based at least in part on the contact location on the target. ### Claim 5 (depends on 3) The method of claim 3, further comprising: calculating a force exerted on the target at the contact location based at least in part on the three-dimensional linear acceleration data. ### Claim 6 (depends on 5) The method of claim 5, wherein evaluating the martial arts move is further based at least in part on the force. ### Claim 7 (depends on 1) The method of claim 1, wherein identifying the distance between the target and the nine DOF sensor comprises: receiving a video signal of the user and the target; and calculating the distance based at least in part on an image analysis of the video signal. ### Claim 8 (depends on 7) The method of claim 7, wherein the target is a second user, and wherein the image analysis is based at least in part on a color recognition of clothing worn by the user and the second user. ### Claim 9 (depends on 1) The method of claim 1, further comprising: retrieving the three-dimensional representation of the target from a surface library. ### Claim 10 (depends on 1) The method of claim 1, further comprising: retrieving the stored model gesture from a gesture library. ### Claim 11 (depends on 1) The method of claim 1, wherein the motion data is received via a wireless data connection. ### Claim 12 (depends on 1) The method of claim 1, wherein the three-dimensional rotation data comprises quaternion data. ### Claim 13 (depends on 1) The method of claim 1, wherein the rotational characteristic of the martial arts move comprises an indication of a rotational orientation of a hand of the user as a function of time. ### Claim 14 (depends on 1) The method of claim 1, wherein the martial arts move comprises a punch, a kick, or a combination thereof. ### Claim 15 (depends on 1) The method of claim 1, wherein the indication of the evaluation of the martial arts move comprises a score. ### Claim 16 (depends on 1) The method of claim 1, further comprising: receiving an identification of the user, an identification of the nine DOF sensor, a timestamp, or a combination thereof. ### Claim 17 (depends on 1) The method of claim 1, wherein the determining whether the user made contact with the target comprises a point in polyhedron calculation. ### Claim 18 (depends on 1) The method of claim 1, further comprising: identifying a starting point in three-dimensional space of the martial arts move.