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Device Technologies and Biomedical Robotics

Device Technologies and Biomedical Robotics - Poster Session A

Poster I10 - A Graphical User Interface to Improve Stimulation-Based Programming Efficiency and Usability

Thursday, October 24, 2024

10:00 AM - 11:00 AM EST

Location: Exhibit Hall E, F & G

Presenting Author(s)

Mahika Krishnamoorthi

Student
Advanced Platform Technology Center
Dublin, California, United States

Co-Author(s)

GL

Gabrielle Labrozzi

Graduate Student
Advanced Platform Technology Center, United States
KF

Kevin Foglyano

Senior Engineer
Advanced Platform Technology Center, United States

Primary Investigator(s)

RT

Ronald Triolo

Prof Biomedical Eng CWRU; Executive Dir. VA APTC;VA Senior Research Career Scientist; PI at ReLLiNC
Case Western Reserve University, VA Center for Advanced Platform Technology (APTC), United States

Introduction: Individuals with a spinal cord injury (SCI) often have limited standing and walking ability due to paralysis of their lower extremities (1). Researchers restore walking after a SCI via neuromuscular stimulation (NS), a process in which an electrical current is delivered to nerves to activate the otherwise paralyzed muscles and initiate steps. Current approaches adjust stimulation parameters via an off-line method. However, this method is neither inefficient nor clinician friendly, as changing a value requires editing code in MATLAB (Natick, MA), which cannot be done within a walk, only during rest breaks. Previous work has demonstrated that graphical user interfaces (GUI) can be developed to work in conjunction with a Speedgoat (Bern, SZ) real-time processor to solve similar issues. Therefore, developing a user-friendly GUI that allows for changes in real-time, could be a solution to improve usability and efficiency for neural stimulation programs. Thus, this work examined the compatibility and accuracy of a custom-built GUI for electrically stimulated walking patterns in a real-time study with clinicians and researchers who would use the application on a regular basis.

Materials and

Methods: Interviews were conducted with clinicians and researchers to ensure proper user interface/user experience (UI/UX). The main design parameters were identified as maximizing efficiency and usability of the app for clinicians conducting research. The GUI was designed using the MATLAB App Designer interface. In the design, a graphical representation of the stimulation patterns was incorporated to visualize the parameter (pulse width, amplitude, and on/off timings) changes. Parameters were organized per muscle channel to make it intuitive for users. The output of surface stimulation was confirmed by testing via LED monitor boards, which plug into a custom 12-channel, external control unit (ECU). The test checked for the correct timing and intensity via the brightness of the lights. Additionally, more rigorous testing was conducted with an oscilloscope, that displayed stimulation waveforms, to ensure the GUI outputted accurate pulse width and amplitudes. Various values across the 0-100 milliamps and 0-255 microseconds range were tested by comparing the inputs to the outputs. The various modes and conditions of the GUI were also tested to ensure it would perform as intended with all values and patterns. Next, an experiment was conducted with a clinician and individual with SCI to confirm the GUI’s usability in real-time. In addition, a survey based on the Questionnaire for User Interface Satisfaction (2) was provided to one clinician and three engineers (who used the GUI with the user manual) to collect quantitative data of the progress. Lastly, three timed trials were conducted for each method to determine the GUI’s efficiency.

Results, Conclusions, and Discussions: The GUI improves efficiency for clinicians and researchers and allows for modulating stimulation walking parameters for individuals with SCI in real-time. Most changes in the GUI occur instantly, except for changing the timing, which has a slight delay. In terms of usability and efficiency, the survey indicated that the GUI improved overall experience compared to the current method with values of 8.5 and 9 (out of 10) respectively. Clinicians and researchers specified that the GUI had significantly better speed with values of 4 and 7.5 (out of 10) for the existing and proposed methods respectively. This corresponds to the timed test where the existing method took on average 5 minutes, 40 seconds to make a few stimulation changes, while the GUI version took 1 minute, 2 seconds on average. For future iterations, the code can be optimized to minimize the delay when changing the stimulation timing, which can increase the efficiency. Users scored the helpfulness of the user manual 8.75 out of 10 and highly appreciated the error/help messages in the GUI, scoring them 10 out of 10. Furthermore, the clinicians successfully operated the GUI independently; thus, showing improvements in usability. Overall, the GUI method outperforms the current method. The GUI enables participants to complete more walking trials in a single session and improve steps quicker. Similar GUIs can be made in the future to optimize changing NS values for other applications like rowing or biking, and for other participant groups like individuals with hemiparesis.

Acknowledgements (Optional): 1) Lisa M. Lombardo, Stephanie N. Bailey, Kevin M. Foglyano, Michael E. Miller,
Gilles Pinault & Ronald J. Triolo (2015) A preliminary comparison of myoelectric and cyclic
control of an implanted neuroprosthesis to modulate gait speed in incomplete SCI, The Journal
of Spinal Cord Medicine, 38:1, 115-122, DOI: 10.1179/2045772314Y.0000000262
2) Chin, J. P., Diehl, V. A., Norman, K. L. (1988). Development of an instrument measuring user satisfaction of the human-computer interface. In CHI 88 Conference Proceedings: Human Factors in Computing Systems (New York, 1988), ACM Press, pp. 213-218