A MATLAB application for automated H-Reflex measurements and analyses. (April 2021)

• Record Type: Journal Article
• Authors: Moukarzel, George; Lemay, Michel A.; Spence, Andrew J.
• Is Part Of: Biomedical signal processing and control. Volume 66(2021)
• Publication Date: 2021-04
• Subjects: H-Reflex -- Software -- Data analysis -- Automated measurements -- MATLAB -- EMG -- Hoffman reflex -- Spinal cord -- Afferent; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102448
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Automated H-Reflex measurements can conduct faster, standardized measurements with automated saving of metadata. Automated equipment is expensive and not always extensible by the user. We developed an app that can perform automated H-Reflex measurements and analyze the record immediately. Our app is an open source platform that can be widely used and expanded, and works with inexpensive equipment. Abstract: Objective: H-Reflex is a test that is carried out to measure the relative excitability of reflex pathways. Although reliable, conventional methods consist of performing many small steps, which requires a high level of attentiveness, and thus can carry an elevated risk of human error, despite proper training. Equipment that is available to perform those tests with different levels of automation are typically proprietary, inextensible by the user, and expensive. Here we present a novel MATLAB application that can accurately and reliably perform automated H-Reflex measurements, test the stimulating electrodes, and carry out typical subsequent analyses. Methods: This application is a Graphical User Interface that works with inexpensive equipment and offers many important features such as measuring electrode impedance in-situ, automating lengthy measurements like recruitment curves and frequency response trials, standardizing electric stimulation properties, automatic exporting of digital data and metadata, and immediately analyzing acquired data with single-click events. Results: Our new method was validated against conventional H-Reflex measurement methods with 2 anesthetized rats. The difference between acquired data using both methods was negligible (mean difference=0.0038; std=0.0121). Our app also detected electrode impedance with high accuracy (94%). Conclusion: The method presented here allows reliable and efficient automated H-reflex measurements and can accurately analyze the collected data. Significance: The features provided by our app can speed up data collection and reduce human error, and unlike conventional methods, allow the user to analyze data immediately after the record. This can result in higher research quality and give broader access to the technique.