Biological signal measurement system based on wireless sensor network is a combination of traditional medical monitor and modern communication technology. It is of great significance for clinical application and the development of medical instruments, especially in family medical treatment. The application of intelligent bionic algorithm in wireless sensor network node location has become a hot topic in academic research. Traditional particle swarm optimization (PSO), as a common method to solve optimization problems, has great advantages in finding the optimal solution iteratively. However, the convergence speed of PSO cannot be adjusted dynamically according to the operation degree of the algorithm, therefore it is easy to go into the situation of finding the local optimal solution. To solve these above problems, this paper proposes a DV-Hop localization algorithm based on particle swarm bionic optimization, which improves the performance of traditional PSO algorithm from three aspects: population selection, inertia weight and learning factor. The simulation results show that, the algorithm can adjust the convergence speed dynamically, and jump out of the local optimal dilemma to the maximum extent, which improves the iterative accuracy of the algorithm for the biologic signal measuring system.