1. A method of lie detection, comprising: receiving an input associated with heart rate variability “HRV”; and performing an HRV analysis based on the input associated with HRV to obtain a lie detection result; wherein said HRV analysis includes nonlinear HRV analysis, wherein the nonlinear HRV analysis includes the following: taking a time series with N elements, u :{u(i): 1 ≦i≦N}, wherein u(i) represents signals carried in the input associated with HRV, and for each u(i), there is a corresponding vector with m elements: 
 X ( i )=[ u ( i ), u ( i+ 1),. .. , u ( i+m− 1)]; calculating a base scale BS(i) for each vector X(i); transforming every X(i) to a m-dimensional symbol series S i ={s(i),. .. s(i+m−1)},sεA(A=0, 1, 2, 3) based on a scale of a×BS(i); calculating the probability of S i , wherein the probability of each different combination among the entire N−m+1 m-dimensional vectors is: p ⁡ ( π ) = # ⁢ ⁢ { t | ( u i , … ⁢ , u t + m - 1 ) ⁢ ⁢ has ⁢ ⁢ type ⁢ ⁢ π } N - m + 1 , wherein 1 ≦t ≦N−m+1; # is the number of states, and each possible combination π for S i represents a vibration mode for S i ; obtaining nonlinear HRV parameters or m-word distribution graph according to the probability of S i ; and obtaining a nonlinear HRV parameter PSS, which is defined as sum probabilities of all strange states calculated according to the following equation: P ⁢ ⁢ S ⁢ ⁢ S = ∑ P s ∑ i = 0 255 ⁢ P i ; wherein P i is probability of combination i, P s is probability of strange state, and ΣP s is probability sum of all strange states.