# EMG-Controlled Soft Robotic Bicep Enhancement

## TL;DR

This paper presents a wearable soft robotic arm device that uses EMG signals to help industrial workers reduce muscle strain during repetitive lifting tasks.

## Contribution

The novel contribution is a wearable EMG-controlled soft robotic bicep enhancement prototype with a hybrid control algorithm for industrial use.

## Key findings

- A soft robotic muscle based on the McKibben design was successfully integrated into a wearable arm device.
- A hybrid control algorithm combining PID and model-based methods improved the device's responsiveness to EMG signals.
- Feasibility testing suggests the device can enhance worker endurance during repetitive lifting tasks.

## Abstract

Industrial workers often engage in repetitive lifting tasks. This type of continual loading on their arms throughout the workday can lead to muscle or tendon injuries. A non-intrusive system designed to assist a worker’s arms would help alleviate strain on their muscles, thereby preventing injury and minimizing productivity losses. The goal of this project is to develop a wearable soft robotic arm enhancement device that supports a worker’s muscles by sharing the load during lifting tasks, thereby increasing their lifting capacity, reducing fatigue, and improving their endurance to help prevent injury. The device should be easy to use and wear, functioning in relative harmony with the user’s own muscles. It should not restrict the user’s range of motion or flexibility. The human arm consists of numerous muscles that work together to enable its movement. However, as a proof of concept, this project focuses on developing a prototype to enhance the biceps brachii muscle, the primary muscle involved in pulling movements during lifting. Key components of the prototype include a soft robotic muscle or actuator analogous to the biceps, a control system for the pneumatic muscle actuator, and a method for securing the soft muscle to the user’s arm. The McKibben-inspired pneumatic muscle was chosen as the soft actuator for the prototype. A hybrid control algorithm, incorporating PID and model-based control methods, was developed. Electromyography (EMG) and pressure sensors were utilized as inputs for the control algorithms. This paper discusses the design strategies for the device and the preliminary results of the feasibility testing. Based on the results, a wearable EMG-controlled soft robotic arm augmentation could effectively enhance the endurance of industrial workers engaged in repetitive lifting tasks.