Multinode electrical impedance tomography (mnEIT) throughout whole-body electrical muscle stimulation (wbEMS) has been proposed for the simultaneous imaging of muscle compartments response. mnEIT has two characteristics, which are: 1) network hardware for synchronized measurement in multinode simultaneously and 2) nodal fast Fourier transform (FFT) for canceling time-varying noise. By mnEIT, the muscle compartments response in the upper arm and thigh of eight healthy subjects is imaged throughout wbEMS under four voltage intensity levels. According to the reconstructed images of conductivity distribution $\sigma$ in prior training and throughout wbEMS, the conductivity distribution trend of the upper arm and thigh is boosted along with the rise of wbEMS voltage intensity. As the hardware error evaluation, the normalized spatial-mean impedance error $\varepsilon _{f}$ of mnEIT is relatively higher in the increase of frequency, while the average error $\langle \varepsilon \rangle$ is 7.521%, respectively. Here, our mnEIT has the best result at $\varepsilon _{f} < \langle \varepsilon \rangle$ , which occurred at $f \le2500$ Hz that covers the frequency selection $f_{1} =500$ Hz and $f_{2} =1000$ Hz to obtain the best visualization of conductivity distribution $\sigma$ . Meanwhile, based on the Pearson correlation as the statistical evaluation, the mnEIT has a relatively high accuracy value at the upper arm $r_{\mathrm {arm}}$ = 0.9391 and thigh $r_{\mathrm {thigh}} =0.894$ .