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Instrumented insoles for assessment of gait in patients with vestibular schwannoma

Published online by Cambridge University Press:  10 May 2023

Stephen Leong
Affiliation:
Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, NY, USA
Bing M. Teh
Affiliation:
Department of Otolaryngology—Head & Neck Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA Department of Otolaryngology—Head & Neck Surgery, Monash Health; Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VC, Australia
Ton Duong
Affiliation:
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ, USA
Diane Hu
Affiliation:
Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, NY, USA
Alexander Chui
Affiliation:
Department of Biological Sciences, Columbia University, New York, NY, USA
Jocelyn S. Chen
Affiliation:
Department of Biomedical Engineering, Columbia University, New York, NY, USA
Michael B. Sisti
Affiliation:
Department of Otolaryngology—Head & Neck Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA Department of Neurological Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA Department of Radiation Oncology, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA
Tony J.C. Wang
Affiliation:
Department of Neurological Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA Department of Radiation Oncology, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA
Damiano Zanotto
Affiliation:
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ, USA
Anil K. Lalwani*
Affiliation:
Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, NY, USA Department of Otolaryngology—Head & Neck Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA Department of Mechanical Engineering, Columbia University, New York, NY, USA
*
Corresponding author: Anil K. Lalwani; Email: akl2144@cumc.columbia.edu

Abstract

Background

Imbalance and gait disturbances are common in patients with vestibular schwannoma (VS) and can result in significant morbidity. Current methods for quantitative gait analysis are cumbersome and difficult to implement. Here, we use custom-engineered instrumented insoles to evaluate the gait of patients diagnosed with VS.

Methods

Twenty patients with VS were recruited from otology, neurosurgery, and radiation oncology clinics at a tertiary referral center. Functional gait assessment (FGA), 2-minute walk test (2MWT), and uneven surface walk test (USWT) were performed. Custom-engineered instrumented insoles, equipped with an 8-cell force sensitive resistor (FSR) and a 9-degree-of-freedom inertial measurement unit (IMU), were used to collect stride-by-stride spatiotemporal gait parameters, from which mean values and coefficients of variation (CV) were determined for each patient.

Results

FGA scores were significantly correlated with gait metrics obtained from the 2MWT and USWT, including stride length, stride velocity, normalized stride length, normalized stride velocity, stride length CV, and stride velocity CV. Tumor diameter was negatively associated with stride time and swing time on the 2MWT; no such association existed between tumor diameter and FGA or DHI.

Conclusions

Instrumented insoles may unveil associations between VS tumor size and gait dysfunction that cannot be captured by standardized clinical assessments and self-reported questionnaires.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press
Figure 0

Figure 1. Components of the instrumented insole system, including (a) an 8-cell force sensitive resistor (FSR) and 9-degree-of-freedom inertial measurement unit (IMU), (b) a smartphone control application, and (c) the fully assembled insole and logic unit.

Figure 1

Table 1. Demographics and characteristics of the study population

Figure 2

Figure 2. Pearson correlation analyses for FGA versus selected gait parameters obtained from the 2MWT. All selected parameters are significantly correlated with FGA, and include stride length (a), stride velocity (b), normalized stride length (c), normalized stride velocity (d), stride length CV (e), and stride velocity CV (f). Correlation coefficients and corresponding p-values are displayed.

Figure 3

Figure 3. Pearson correlation analyses for FGA versus selected gait parameters obtained from the USWT. All selected parameters are significantly correlated with FGA, and include stride length (a), stride velocity (b), normalized stride length (c), normalized stride velocity (d), stride length CV (e), and stride velocity CV (f). Correlation coefficients and corresponding p-values are displayed.

Figure 4

Figure 4. Linear regression analyses for tumor diameter versus FGA (a) and DHI (b) scores. Neither FGA nor DHI are significantly associated with tumor size. R2 values and corresponding p-values are displayed.

Figure 5

Figure 5. Linear regression analyses for tumor diameter versus 2MWT metrics: stride time (a) and swing time (b), and USWT metrics: stride time (c) and swing time (d). Neither FGA nor DHI are significantly associated with tumor size. R2 values and corresponding p-values are displayed.

Supplementary material: File

Leong et al. supplementary material

Table S1

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Leong et al. supplementary material

Table S2

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Leong et al. supplementary material

Table S3

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