1. The purpose of the experiment
Deepen the understanding and mastery of theoretical knowledge through actual data collection and processing, and improve students' practical ability.
2. Experimental principle
- Zero drift processing, noise reduction
- Spectrum Analysis
- Filter
3. Experimental content and results
3.1 Data collection
Download MATLAB APP or other mobile phone applications, and 速度传感器collect personal walking gait data based on the built-in mobile phone . Requirements are as follows:
- First determine the best placement of the mobile phone to ensure that the data can be saved and read through MATLAB;
- The experimental collection is divided into 4 groups, namely normal walking at a constant speed, walking at a constant speed with the heel off the ground, running at a normal constant speed, and switching between normal walking and normal running, and the pace is self-determined;
- The sampling frequency is set to 100 Hz, the single sampling time is 30 s, and each group of experiments is collected no less than 5 times;
Note : The acceleration sensor must be checked when collecting , otherwise the required data will not be collected.
3.2 Denoising of gait data
Zero drift and noise are common forms of interference in measured signals. They are low-frequency processes and stationary random processes, respectively. In order to ensure the reliability of the gait feature analysis results, the measured signal must be filtered and denoised. Combined with the knowledge learned in the course, the requirements are as follows:
3.2.1 FFT spectrum analysis
First, perform Fast Fourier Transform (FFT) on the measured signal, and determine the bandpass frequency of the filter through the spectrum graph; read the data, there are three dimensions of X, Y, Z, and draw the time-domain waveform diagram as follows.
(1) The experimental results of the time-domain waveform diagram of the collected data are as follows: