How to extract gait information? Challenge:signal reflections of different body parts are mixed together in the wave form. Insight:different body parts move at different speeds Signal reflections of different parts have differentfrequencies. CSI fluctuations of differentfrequencies are separable in the frequency domain. How:convert waveforms into time-frequency domain - Use Short-Time Fourier Transform(STFT)to convert each slice of waveforms to a spectrogram. Spectrogram 3 dimensions:time,frequency,and FFT amplitude Window size:tradeoff between frequency and time resolutions Larger:higher frequency resolution,low time resolution Smaller:low frequency solution,high time resolution Our choice:FFT size=1024 samples,window size=32 samples Frequency resolution=2.44Hz,time resolution=12.8ms 10/9610/96 How to extract gait information? § Challenge: signal reflections of different body parts are mixed together in the wave form. § Insight: different body parts move at different speeds – Signal reflections of different parts have different frequencies. – CSI fluctuations of different frequencies are separable in the frequency domain. § How: convert waveforms into time-frequency domain – Use Short-Time Fourier Transform (STFT) to convert each slice of waveforms to a spectrogram. – Spectrogram 3 dimensions: time, frequency, and FFT amplitude – Window size: tradeoff between frequency and time resolutions • Larger: higher frequency resolution, low time resolution • Smaller: low frequency solution, high time resolution – Our choice: FFT size=1024 samples, window size=32 samples • Frequency resolution=2.44Hz, time resolution=12.8ms