Instrumented assessment of lower and upper motor neuron signs in amyotrophic lateral sclerosis using robotic manipulation

an explorative study

Journal Article (2024)
Author(s)

D. J.L. Stikvoort García (University Medical Center Utrecht)

B. T.H.M. Sleutjes (University Medical Center Utrecht)

W. Mugge (TU Delft - Biomechatronics & Human-Machine Control)

J. J. Plouvier (Student TU Delft)

H. S. Goedee (University Medical Center Utrecht)

AC Schouten (TU Delft - Biomechanical Engineering)

Frans Van Der Helm (TU Delft - Biomechatronics & Human-Machine Control)

L. H. van den Berg (University Medical Center Utrecht)

Research Group
Biomechatronics & Human-Machine Control
DOI related publication
https://doi.org/10.1186/s12984-024-01485-9
More Info
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Publication Year
2024
Language
English
Research Group
Biomechatronics & Human-Machine Control
Issue number
1
Volume number
21
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Abstract

Background: Amyotrophic lateral sclerosis (ALS) is a lethal progressive neurodegenerative disease characterized by upper motor neuron (UMN) and lower motor neuron (LMN) involvement. Their varying degree of involvement results in a clinical heterogenous picture, making clinical assessments of UMN signs in patients with ALS often challenging. We therefore explored whether instrumented assessment using robotic manipulation could potentially be a valuable tool to study signs of UMN involvement. Methods: We examined the dynamics of the wrist joint of 15 patients with ALS and 15 healthy controls using a Wristalyzer single-axis robotic manipulator and electromyography (EMG) recordings in the flexor and extensor muscles in the forearm. Multi-sinusoidal torque perturbations were applied, during which participants were asked to either relax, comply or resist. A neuromuscular model was used to study muscle viscoelasticity, e.g. stiffness (k) and viscosity (b), and reflexive properties, such as velocity, position and force feedback gains (kv, kp and kf, respectively) that dominated the responses. We further obtained clinical signs of LMN (muscle strength) and UMN (e.g. reflexes, spasticity) dysfunction, and evaluated their relation with the estimated neuromuscular model parameters. Results: Only force feedback gains (kf) were elevated in patients (p = 0.033) compared to controls. Higher kf, as well as the resulting reflexive torque (Tref), were both associated with more severe UMN dysfunction in the examined arm (p = 0.040 and p < 0.001). Patients with UMN symptoms in the examined arm had increased kf and Tref compared to controls (both p = 0.037). Neither of these measures was related to muscle strength, but muscle stiffness (k) was lower in weaker patients (p = 0.012). All these findings were obtained from the relaxed test. No differences were observed during the instructions comply and resist. Conclusions: This findings are proof-of-concept that instrumented assessment using robotic manipulation is a feasible technique in ALS, which may provide quantitative, operator-independent measures relating to UMN symptoms. Elevated force feedback gains, driving larger reflexive muscle torques, appear to be particularly indicative of clinically established levels of UMN dysfunction in the examined arm.