Can AI analyze gait to detect muscle disorders?
Cloud and IoT based Smart Agent-driven Simulation of Human Gait for Detecting Muscles Disorder
September 24, 2024
https://arxiv.org/pdf/2409.14561This paper introduces a system for analyzing human gait to detect muscle disorders. It uses a smartphone's motion sensors to capture gait data and employs a biomechanical model with muscle and joint agents to simulate movement and calculate muscle forces. This data is then fed into an ensemble of neural networks to differentiate between healthy and unhealthy muscle activity, aiding in diagnosis.
Key points relevant to LLM-based multi-agent systems:
- Agent-based modeling allows for simulating complex biological systems like muscle groups.
- Each muscle and joint is represented as an independent agent, enhancing the system's interpretability and reflecting the parallel nature of biological processes.
- This approach can be extended to model other complex systems using LLMs as agents, where each agent can represent a different component or process.
- The ensemble neural network approach for analysis can inspire similar architectures in LLM-based systems for improved reliability and interpretability.