## 1 Introduction  
Sensor-based E-Healthcare systems are a new technology developed in the field of health care in recent years. Wireless Body Area Networks (WBANs) [1] are mainly used in emergency rescue, telemedicine, home care and other occasions. Medical sensor nodes are worn on the body surface or implanted in the human body to monitor the patient's medical data, these physiological data are transferred to a sink through the WBAN, and the sink processes the data or sends the data to a medical monitoring center [2]. The nodes are mostly powered by microbatteries, the energy is very limited, so if some nodes are frequently used for data forwarding, it is likely to lead to the early depletion of these nodes, affecting the network connectivity, and eventually leading to a reduced global network lifetime [3; 4; 5]. Compared with the traditional data-centric WSN, WBANs' human-centered features make their energy requirements more demanding [6] is several aspects: (1) Faster signal transmission attenuation: the specificity of the human tissue structure and the shadow effects make the signal in the transmission process have a great path loss [7], resulting in WBANs' communication energy consumption being much higher than that of other normal networks of the same size. (2) Varying network communication link time: the network topology of WBANs is closely related to the changes in the posture of the human body (especially the activities of the human limbs). The data retransmissions caused by the frequent interruptions of the communication links and the reconstruction of the network topology can cause a waste of energy [8]. (3) Limited node energy: The network lifetime in WBANs is defined as the time interval between when the network starts working to the time when the first node dies, which leads to network partitioning in such a way that the destination cannot be reached. As battery replacement and charging is not feasible in implant medical devices, each node must use limited energy to maximize its own life. Network lifetime is of more importance in WBANs compared to WSNs. Since about 80% of the total energy is consumed only for communication purposes [9], routing algorithms play a vital role to make the communication effective and prolong the lifetime of the WBANs, and how to use the residual energy of nodes effectively to extend the network lifetime becomes the key problem of designing WBAN routing algorithms. In the survey of routing protocols in wireless sensor networks [10; 11], the path selection algorithm is based on the principle of minimizing the total energy consumption of the path, the global optimal solution is solved by using the greedy algorithm, which does not consider the protection of individual nodes with small energy, nor the energy consumption ratio of the whole path. It is easy to for some nodes to be utilized with high frequency, and if the important nodes suffer premature death, this often leads to the paralysis of the entire network [12]. Moreover, the time and spatial complexity of these algorithms will usually increase exponentially as the size of the problem grows. In the past decade, the group intelligent optimization methods have attracted more and more attention [13], as they are effective tools to address the problem of combinatorial optimization.  
In this paper, we fully consider the energy consumption of the path, the residual energy of the nodes, the importance level of the nodes and the energy ratio of the whole path, and give the definition of Optimal Path of Energy Consumption (OPEC), and by means of the idea of artificial bee colony [14; 15; 16], design Optimal Energy Consumption Artificial Bee Colony Algorithm-Based WBANs (OEABC). The simulation results show that the OEABC converges faster, and has a better ability to find the optimal solution.