A wearable inertial device human gait information acquisition and calculation method

Abstract

The invention provides a wearable inertial device human body gait information acquisition and calculation method, and relates to the field of exoskeleton gait rule information acquisition. The methodincludes the following steps that (1), four accelerometers and two IMUs are installed on one leg of the human body; (2), a first knee joint angle is calculated according to a thigh pitch angle and a shank pitch angle; (3), a second knee joint angle is calculated according to a thigh inclination angle and a shank inclination angle; (4), a first human body thigh IMU coordinate system and a second shank IMU coordinate system are established; (5), a relation equation of the first knee joint angle and the second knee joint angle is established; (6), Kalman filtering calculation is carried out, anda knee joint angle error and a knee joint angle obtained after compensation are obtained. Real-time non-contact measurement of human body gait information is achieved, accurate knee joint angle information is acquired, and in combination with basic human body information acquired at the beginning, information such as the step length, the step frequency and the leg lifting height in the human bodywalking process is calculated.

Description

technical field [0001] The invention relates to the field of exoskeleton gait rule information collection, in particular to a wearable inertial device human body gait information collection and calculation method. Background technique [0002] Rehabilitation training exoskeletons, disabled walking exoskeletons, weight-bearing exoskeletons and other exoskeleton equipment require a coordinated gait pattern between the human body and the exoskeleton equipment, but there are indelible differences between the two, so the wearers of the above exoskeleton equipment Acquisition of gait information and analysis of gait data classification, tracking and prediction are required in order to realize gait tracking and control of lower extremity exoskeleton and improve its dynamic stability. In addition, nursing homes for the elderly or athletes need to collect and detect human body posture and physical fitness information, so as to facilitate the evaluation of the elderly's exercise abili...

AI Technical Summary

Problems solved by technology

[0005] Image sequence analysis: real-time detection of gait data is costly, data processing is large, and delay is serious

[0006] EMG signal detection: The sensors and supporting devices used are expensive, and signal recognition and classification are difficult, and EMG signal detection is affected by the detection position, sweat, temperature, etc., and is easily interfered by signals, and the repeatability is not high

[0007] Angle / angular velocity detection: Due to the use of the integral algorithm, the error continues to accumulate, making the joint angle error gradually increase

[0008] Accelerometer detection method: only applicable to static calculation, not extended to dynamic joint angle calculation

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