Patent ID: 11944427
Assignee: TOYOTA JIDOSHA KABUSHIKI KAISHA
Field: Medical technology (Instruments)
Classification: CPC A  B  G | IPC A  B  G

Claim 0:
1. A learning system comprising:
a data acquisition unit configured to acquire rehabilitation data from a walking training system comprising a plurality of actuators configured to assist a walking motion of a trainee, a treadmill on which the trainee walks, a plurality of sensors configured to detect data regarding the walking motion assisted by the plurality of actuators, and a control unit configured to control the plurality of actuators and treadmill in accordance with a plurality of setting parameters;
a data generation unit configured to generate learning data based on the rehabilitation data; and
a learning unit configured to perform machine learning using the learning data, wherein
the plurality of actuators includes a front pulling unit configured to apply pulling force to a leg of the trainee from front side and a rear pulling unit configured to apply pulling force to the leg of the trainee from a rear side for assisting a swing motion of the leg;
the plurality of sensors are provided to detect a plurality of motion amounts in the walking motion of the trainee,
the plurality of the setting parameters includes a speed of the treadmill, the pulling forces of the front pulling unit, a ratio between the pulling forces of the front and rear pulling units,
it is evaluated that, for each walking cycle of the walking motion, when at least one of the motion amounts matches one of predetermined abnormal walking criteria,
the motion amounts include distances along a walking direction from a hip joint to a foot joint of the trainee at a time of swinging of the leg and at a time of landing of the leg;
the data generation unit generates each of the pieces of rehabilitation data in a walking cycle before and after a change in results of evaluation of abnormal walking pattern as learning data,
the learning unit sequentially inputs each of the pieces of rehabilitation data in the walking cycle before and after the change in the results of the evaluation as one data set, thereby performing machine learning by a supervised machine learning with using the setting parameter as a correct-answer label,
the one data set includes the plurality of setting parameters, an evaluation result of the abnormal walking pattern, and
the learning unit constructs a learning model that receives the abnormal walking pattern and outputs the setting parameter,
the learning model is configured to output one or more setting parameter for improving the evaluation result of the abnormal walking pattern.