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Authentication ensures the privacy of patients by enabling access control within wireless medical sensor networks. However, many schemes do not consider the resource-constrained environments, making those protocols unusable. Meanwhile, sensitive patient information continues to be stored and accessed in a central location, increasing the risk of “single points of failure.” To solve this problem, the researchers designed a lightweight anonymous authentication protocol based on blockchain technology and fuzzy extraction. First, they created a multiround session key negotiation mechanism. Then, they utilized the fuzzy extraction function to extract and recover multimodal biometric features. Decentralization was achieved through blockchain and smart contracts. Simultaneously, the researchers also provided a formal security proof by Burrows-Abadi-Needham logic. Finally, experiments using the Java Pairing-Based Cryptography Library show that this scheme outperforms the comparison schemes in terms of computational overhead and communication overhead.