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

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 Ω 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.

System Performance and User Feedback Regarding Wearable Bioimpedance System for Multi-Site Knee Tissue Monitoring: Free-Living Pilot Study With Healthy Adults

“…These data provide insights regarding the reliability of data (i.e., quantity of artifact free data) and limitations of this design in unsupervised free-living environments. While the system in this effort is not the first wearable BIS system, with a range of wearable BIS systems presented in the literature ( Hersek et al, 2016 ; Rossi et al, 2017 ; Teague et al, 2020 ; Ngo et al, 2022 ; Sanchez-Perez et al, 2022 ), it does advance the use BIS wearables beyond controlled laboratory or clinical settings. For a comprehensive comparison of existing BIS wearables to this system, details of existing systems electrode placements, on-body locations, length of data collection, location of use, number of participants, and processing methods applied to collected BIS data are provided in Table 5 .…”

Electrical impedance myography combined with quantitative assessment techniques in paretic muscle of stroke survivors: Insights and challenges

“…Both active and passive muscle properties were assessed at the same time, which could advance the understanding of muscle dysfunction. Ngo et al (2022) proposed a novel device that can combine EIM and EMG measurements simultaneously, offering a more robust method for muscle status assessment even in the presence of artifacts.…”

“…• EIM is a promising biomarker in assessment of muscle function in neuromuscular diseases and its relationships with other electrophysiological measures have been well-established in various neuromuscular diseases. Hu et al, 2021a;Ngo et al, 2022 • Applying EIM and EMG simultaneously could provide more comprehensive information of the inherent properties and muscle activation alteration.…”

A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications

“…Tractor manipulation via EMG-based human–machine interface [ 113 ]. Combining synchronized EMG and EIT to measure muscle activity [ 114 ]. A disabled assistive robotic glove using optical fiber force myography sensor [ 47 ].…”

“…Tractor manipulation via EMG-based human-machine interface [113]. Combining synchronized EMG and EIT to measure muscle activity [114]. A disabled [109].…”