Due to the fast development of mobile communication networks, more and more wearable devices access the network through mobile terminals and produce massive data. These aggregated medical data have significant statistical analysis and decision making value. Nevertheless, there are emerge security and privacy issues (e.g., as transmission interruption, information leakage, and data tampering) in medical data transmission and aggregation process. To address those security issues and ensure accurate medical data aggregation and analysis, an efficient verifiable fault-tolerant medical data aggregation scheme is proposed based on mobile edge service computing. The scheme exploits a modified BGN homomorphic encryption algorithm, integrates Shamir secret sharing mechanism to ensure medical data confidentiality, fault tolerance of encrypted aggregated data, simultaneously. The concept of mobile edge-assisted service computing in wireless body area networks is proposed in the scheme. Combined with the advantages of mobile edge computing and cloud computing, the real-time big data processing and statistical analysis of massive medical big data could be conducted. Through edge-level aggregation and cloud-level aggregation, the aggregation efficiency is improved and the communication overhead is reduced. Besides, the scheme designs an aggregate signature algorithm to conduct batch verification on medical encrypted data, and guarantee the integrity during transmission and storage process. The comprehensive performance evaluation demonstrates that the proposed scheme has outstanding advantages in terms of computational costs and communication overhead.