A Wearable, Multi-Frequency Device to Measure Muscle Activity Combining Simultaneous Electromyography and Electrical Impedance Myography.

Chuong Ngo,Cornelius Bollheimer,Andrey Briko,Alexander Kobelev,Markus Lueken,Carlos Munoz,Steffen Leonhardt,Sergey Shchukin,Alfred Hülkenberg

doi:10.3390/s22051941

Abstract

The detection of muscle contraction and the estimation of muscle force are essential tasks in robot-assisted rehabilitation systems. The most commonly used method to investigate muscle contraction is surface electromyography (EMG), which, however, shows considerable disadvantages in predicting the muscle force, since unpredictable factors may influence the detected force but not necessarily the EMG data. Electrical impedance myography (EIM) investigates the change in electrical impedance during muscle activities and is another promising technique to investigate muscle functions. This paper introduces the design, development, and evaluation of a device that performs EMG and EIM simultaneously for more robust measurement of muscle conditions subject to artifacts. The device is light, wearable, and wireless and has a modular design, in which the EMG, EIM, micro-controller, and communication modules are stacked and interconnected through connectors. As a result, the EIM module measures the bioimpedance between 20 and 200 with an error of less than 5% at 140 SPS. The settling time during the calibration phase of this module is less than 1000 ms. The EMG module captures the spectrum of the EMG signal between 20–150 Hz at 1 kSPS with an SNR of 67 dB. The micro-controller and communication module builds an ARM-Cortex M3 micro-controller which reads and transfers the captured data every 1 ms over RF (868 Mhz) with a baud rate of 500 kbps to a receptor connected to a PC. Preliminary measurements on a volunteer during leg extension, walking, and sit-to-stand showed the potential of the system to investigate muscle function by combining simultaneous EMG and EIM.

Highlights

Robotic devices have been developed to increase the efficiency of rehabilitation therapy and reduce costs
The system developed in this work will focus on deriving the magnitude of the bioimpedance signal k ZEIM [Ω]k
The use of amplitude-modulated current at high frequency to investigate the human muscle contraction reduces the effect of motion artifacts, which are in the frequency range from 0.5 to 10 Hz [34]

Summary

Introduction

Robotic devices have been developed to increase the efficiency of rehabilitation therapy and reduce costs. Robotic devices and exoskeletons have emerged as mechanical rehabilitation tools attached to an able-bodied operator and augment the strength or endurance of movement for performing repetitive tasks [3]. To assess and control the interactive force between the robotic devices and the users in real-time, it is of importance to observe the user’s intention of motion and force [4]. One method is to apply the inverse model of the exoskeleton robot to derive the joint torques [6,7]. The parameters of the inverse models vary strongly among individuals, with time, and depending on the task, which makes robust impedance control challenging [8,9]. Alternative measurement technologies for estimation of the interactive human force/torque include sonomyography [10,11], optics [12], mechanomyography [13], magnetomyography [14], surface electromyography (EMG), and bioimpedance or electrical impedance myography (EIM)

Methods

Results

Conclusion