# An Intelligent Pressurized Thigh Band for Muscular Assistance and Multi-Mode Activity Recognition

## TL;DR

A smart thigh band was developed to assist leg muscles and recognize movements with high accuracy using pressure and deep learning.

## Contribution

The novel integration of sensing and actuation in a pressurized thigh band for muscle assistance and activity recognition.

## Key findings

- Appropriate air bladder pressure reduces quadriceps activation and metabolic cost.
- A deep learning model achieved 99.17% accuracy in recognizing six activities.
- The model was successfully deployed on an embedded platform for real-world use.

## Abstract

This study aims to develop a “sensing-actuation integrated” intelligent pressurized thigh band to assist the quadriceps, indirectly alleviate knee joint load, and achieve high-precision recognition of movement modes. The system comprises a portable integrated controller and a textile-integrated flexible pneumatic actuator. Experiments were conducted to evaluate the effects of different air bladder pressure conditions on metabolic rate and muscle activity. Simultaneously, pneumatic data corresponding to six common activities were collected, and a lightweight deep learning model was developed to enable high-precision motion classification. Finally, the model was deployed to an embedded platform to demonstrate its application potential. Results indicate that appropriate air bladder pressure significantly reduces quadriceps muscle activation and average metabolic cost. Furthermore, the deep learning model achieved 99.17% accuracy in recognizing the six activities and was successfully deployed to the embedded platform. This study validates the effectiveness of the intelligent pressurized thigh band in improving locomotor performance under static pressures and demonstrates the potential of air bladder pressure variations as a proxy indicator for movement intent for future closed-loop control.