Using body sensor networks (BodyNets) to monitoring the human health is increasingly emerging as a dominant application framework for the evolving sensor network technology. In this paper, we explore how to promote such network work in cold region. Different to the ordinary region, sensors not only need to collect sensory data of human characteristic but also accurately monitor the surround environment of the target human. Specially, the monitoring objectives are affected by the combined effects of many parameters, such as the movement of target human and uncertainty of nature. These parameters are featured in vague and many-to-many association etc, which make the monitoring process in high complexity. We analyze the requirement of Bodynets during the process of monitoring health condition, and design an adaptable system model. Moreover, we use distributed Bayesian estimation to eliminate the inaccuracy of sensory information with the consideration of time and spatial distribution effects on monitoring process. The experiment result show that our design can efficiently guarantee the information accuracy of monitoring objective.