Multi-part limb movement capturing method based on electrical impedance

Abstract

The invention discloses a multi-part limb motion capture method based on electrical impedance, which belongs to the field of motion capture, and specifically comprises the following steps: firstly, connecting a limb motion capture device, attaching an electrode girdle by a user, and connecting a channel control module; after power-on, the single-chip microcomputer controlling the level change of the pin to sequentially select a channel and the impedance measurement module to form a data stream and send the data stream to the upper computer; manually carrying out initialization control on the GUI, adjusting calibration parameters and setting a to-be-identified action label; the data processing module inputs and reads an electrical impedance data stream of a to-be-identified action in real time, divides the electrical impedance data stream into groups and stores the groups into excel; the data modeling module using the stored data as a training set to generate a training model; a to-be-detected part of a user making various actions with input data again, the lower computer collecting the actions, wherein the actions are segmented and extracted by the data processing module and then input into the training model, and an action recognition result is directly output. The multi-channel bioelectrical impedance signals are used as an information source of action recognition, and the recognition rate is high.

Description

technical field [0001] The invention belongs to the field of motion capture, relates to motion capture of multiple body parts, in particular to a method for capturing motion of multiple body parts based on electrical impedance. Background technique [0002] With the development of information technology, body movements have attracted much attention as an ideal choice of human-computer interaction. Numerous corporate research investments and the use of a large number of mature technologies in the field of motion capture have enabled the application of body movements in many aspects of production and life: For example, Noitom has launched a high-precision full-body motion capture technology based on precision optical sensors and inertial sensors , can be applied to film game production and VR games; as another example, the Spark series drones launched by DJI can realize gesture-controlled drone flight and gesture-controlled camera and video through onboard cameras and machine ...

AI Technical Summary

Problems solved by technology

However, the data collected by these two technologies are relatively complex, and the processing process is also very cumbersome.

This leads to higher learning costs for ordinary users

[0011] In addition, inertial sensors have different installation requirements on different parts of the body. In order to achieve measurement of different parts, different sensor installation kits are required; the installation parts of surface electromyography sensors are limited, and it is also difficult to realize the transplantation and installation of different parts of a set of equipment

Therefore, the existing two types of equipment are specific. If the user has motion capture needs for different body parts, it is often necessary to purchase multiple sets of equipment, and the budget is difficult to reduce.

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