
Trusted Blockchain-Based Clinical Decision and Medication Management System for Movement Disorders
Author(s) -
Behnaz Behara,
Mehdi Delrobaei,
Nima Afraz
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3596693
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Centralized healthcare information systems face significant challenges related to security, interoperability, and real-time monitoring, particularly in the management of movement disorders. This paper proposes a novel blockchain-based framework that integrates wearable inertial measurement units (IMUs), AI-driven analytics, and the Hyperledger Fabric blockchain to enable secure, decentralized decision-making in the management of movement disorders. The system employs a voting-based consensus mechanism, where medication dosage recommendations proposed by an AI model are validated by clinicians, ensuring transparency and accountability in treatment decisions. Experimental evaluations demonstrate the framework’s scalability, achieving a throughput of 185 transactions per second (TPS) and reducing latency to 0.285 seconds under a 300 TPS load, using an 8-core CPU configuration. The proposed architecture guarantees 100% auditability and tamper-evident records, significantly improving the security and efficiency of clinical workflows. Notably, the system achieves a 96.3% reduction in latency and shows promising performance in both medication safety and treatment response times. The integration of blockchain and AI-based dosage recommendations offers a scalable and low-latency solution for remote patient monitoring and personalized healthcare management in patients with movement disorders. This work provides a practical solution to the challenges of decentralized decision-making and real-time data integration, offering a pathway to more resilient and secure healthcare systems.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom