(D-152) 3D force vector characterization of tendon indentation to quantify stretch reflex

Introduction
• Hyperactive tendon stretch reflexes are the hallmark of spasticity [1] in chronic stroke survivors. Clinically, to assess spasticity, the Modified Ashworth Test is performed. However, the test has limited resolution and suffers from inter/intra-rater variability.
• To accurately quantify the stretch reflex threshold, we developed a highly precise framework utilizing a position-controlled tendon tapper with a load cell attached to the tapper head [2]. One of the limitations of this method is to ensure the orthogonality between the tap axis and the muscle axis.
• In order to assess whether the tapper is located on the tendon in a consistent position, continuous monitoring of the force sensor and subject movement is necessary. In this study, we propose a novel approach that overcomes the above-mentioned limitation by studying three-dimensional force data from the sensor.
• Our ultimate goal is to develop a portable version of our device that may also be used in clinical settings for more precise quantification of spasticity.

Materials & Methods
Participants: 2 male, 1 female; Age Range: 28-35; Dominant Hand: Right.
Experimental Setup: The device consisted of a position-controlled linear actuator (Linmot S.A., Spreitenbach, Switzerland) with a load cell (ATI Multi- Axis force-torque sensor, Series Nano 17, NC, USA) attached at the end of the actuator (Figure 1b). The subject’s arm and system were set up in a fixed position, and the indentation protocol was followed on the biceps brachii tendon, with the tapper position orthogonal to the long axis of the tendon (Figure 1a). Details about the experimental setup can be found in [1]. Recorded signals (Figure 2) include X, Y, and Z axes of the load cell.

Results
In figure 3 and 4, force data for X, Y, and Z axis is plotted by varying the indentation angle (10°) at each depth with respect to the long axis to the biceps tendon. We considered the stretch reflex after getting a minimum of 3 reflexes out of 5 tapping. We were able to get a reflex response for 2 subjects.
To analyze the position stability of the load cell required to elicit a reflex, we plotted the three-dimensional force variation data in figure 5.

Discussion
• In all cases, the force data shows a nonlinear pattern with respect to the indentation depth (2nd order polynomial) in all axis potentially due to the tissue overlying the tendon. Once the tendon is reached, reflex responses were present and a linear trend was observed.
• The rate of change in force value is higher in the Z axis compared to the X and Y axes. For all the subjects tendon indentation profile has specific curvature for Y and Z axis.
• The results (figure 5) indicate that for a stable position, the data points lie within a small, well-defined area. Conversely, to examine the force variation in an unstable scenario, the force sensor was deliberately moved 200 millimeters away from the tendon. The grid pattern appears much smoother for stable positioning, whereas the grid plot seems more crumpled in the case of an unstable positioning.

Conclusion
• In this study, we have analyzed three-dimensional force data obtained from the linmot system to assess the stretch reflex.
• By analyzing the data in three dimensions, we can achieve a more precise quantification of the reflex and its pattern of variation, leading to better accuracy in determining the threshold.
• Currently, efforts are ongoing to make the device portable, and the insights gained from the 3D analysis are pivotal.
• Portable version of the linmot system would significantly enhance the accessibility and usability, benefiting both patients and healthcare providers by simplifying the testing process and enabling assessments in more flexible environments.

Limitations: For this study, we specifically recruited healthy young subjects. However, to obtain more comprehensive insights, it is necessary to conduct tests on a wider age range. In future research, we intend to explore broader ranges of variables, including tapping depth, hand positions etc. which were kept fixed in this study.
Acknowledgments: We thank all the participants of this study. Also, we want to show our gratitude to Alexander Barry, Leah OShea and Fandi Shi for all the technical support during the experiment.

References:
1. Lance JW. The control of muscle tone, reflexes, and movement: Robert Wartenberg Lecture. Neurology. 1980;30(12):1303-1313. doi:10.1212/wnl.30.12.1303
2. Chardon MK, Rymer WZ, Suresh NL. Quantifying the deep tendon reflex using varying tendon indentation depths: applications to spasticity. IEEE Trans Neural Syst Rehabil Eng. 2014 Mar;22(2):280-9. doi: 10.1109/TNSRE.2014.2299753. PMID: 24621852.
3. Afzal, T., Chardon, M.K., Rymer, W.Z. et al. Stretch reflex excitability in contralateral limbs of stroke survivors is higher than in matched controls. J NeuroEngineering Rehabil 16, 154 (2019). https://doi.org/10.1186/s12984-019-0623-8