Wireless human body sensor networks are widely used, but because of hardware and environmental constraints, their nodes have problems such as unsustainable energy and weak computing capabilities. To further improve the efficiency of data aggregation for health monitoring, a fuzzy clustering based data aggregation algorithm is presented. Based on the fuzzy clustering algorithm of distributed wireless sensors, this work analyzes the processing mechanism of distributed data and introduces an optimal weighted weighting algorithm, thereby obtaining the optimal weight distribution coefficient of each sensor, results of node variance evaluation, and corresponding data aggregation through distributed data processing. The proposed algorithm is of great significance to improve the accuracy of data collection and reduce the overall energy consumption of the network.