Patent ID: 11966836
Assignee: KABUSHIKI KAISHA TOSHIBA
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 8:
9. A detection method, comprising:
acquiring first data of a time series, the first data being based on an action of a first body part in a work task of a first worker having a first proficiency;
acquiring second data of a time series, the second data being based on an action of the first body part in the work task of a second worker having a second proficiency that is different than the first proficiency such that the first worker completes the work task in a shorter time than it takes for the second worker to complete the work task, wherein the first data, second data and third data was acquired by mounting an accelerometer to the right wrist of each of the first worker, the second worker, and the third worker, the first data is acceleration information of the first body part in the work task of the first worker, the second data is acceleration information of the first body part in the work task of the second worker, and the third data is acceleration information of the first body part in the work task of the third worker;
training a recurrent neural network including a first output layer by inputting the first data to the recurrent neural network, the first output layer including a first neuron and a second neuron, a first value corresponding to the action of the first body part of the first proficiency being set as teacher data in the first neuron;
training the recurrent neural network by inputting the second data to the recurrent neural network, a second value corresponding to the action of the first body part of the second proficiency being set as teacher data in the second neuron;
acquiring third data of a time series, the third data being based on an action of the first body part in the work task of a third worker;
inputting the third data, as a waveform of acceleration in an X-axis direction and a waveform of acceleration data in the Y-axis direction over a total time it takes for the third worker to complete the work task, to the trained recurrent neural network; and
detecting that at least part of the action of the third worker, during a particular time period within the total time it takes for the third worker to complete the work task, corresponds to the first proficiency when an absolute value of a first activity of the first neuron is larger than a threshold in response to the input of the waveform of acceleration in an X-axis direction and the waveform of acceleration data in the Y-axis direction, and detecting that at least part of the action of the third worker, during a particular time period within the total time it takes for the third worker to complete the work task, corresponds to the second proficiency when an absolute value of a second activity of the second neuron is larger than the threshold in response to the input of the wavefoirii of acceleration in an X-axis direction and the waveform of acceleration data in the Y-axis direction, thereby detecting, as a detection result, that said part of the action of the third worker corresponding to the second proficiency needs improvement, and
outputting a display of the detection result on a display device the displayed detection result including a part of the third data for which the first neuron or the second neuron responded, and the part of the third data is displayed to be discriminable from another part of the third data.