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Mageswaran P, Dufour J, Aurand A, Knapik G, Hani H, Blakaj DM, Khan S, Hussain N, Tiwari M, Vallabh J, Weaver T, Marras WS. Wearable motion-based platform for functional spine health assessment. Reg Anesth Pain Med 2024; 49:518-527. [PMID: 37813527 DOI: 10.1136/rapm-2023-104840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 09/22/2023] [Indexed: 10/17/2023]
Abstract
INTRODUCTION Low back pain is a significant burden to society and the lack of reliable outcome measures, combined with a prevailing inability to quantify the biopsychosocial elements implicated in the disease, impedes clinical decision-making and distorts treatment efficacy. This paper aims to validate the utility of a biopsychosocial spine platform to provide standardized wearable sensor-derived functional motion assessments to assess spine function and differentiate between healthy controls and patients. Secondarily, we explored the correlation between these motion features and subjective biopsychosocial measures. METHODS An observational study was conducted on healthy controls (n=50) and patients with low back pain (n=50) to validate platform utility. The platform was used to conduct functional assessments along with patient-reported outcome assessments to holistically document cohort differences. Our primary outcomes were motion features; and our secondary outcomes were biopsychosocial measures (pain, function, etc). RESULTS Our results demonstrated statistically significant differences in motion features between healthy and patient cohorts across anatomical planes. Importantly, we found velocity and acceleration in the axial plane showed the largest difference, with healthy controls having 49.7% and 55.7% higher values, respectively, than patients. In addition, we found significant correlations between motion features and biopsychosocial measures for pain, physical function and social role only. CONCLUSIONS Our study validated the use of wearable sensor-derived functional motion metrics in differentiating healthy controls and patients. Collectively, this technology has the potential to facilitate holistic biopsychosocial evaluations to enhance spine care and improve patient outcomes. TRIAL REGISTRATION NUMBER NCT05776771.
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Affiliation(s)
- Prasath Mageswaran
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Jonathan Dufour
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Alexander Aurand
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Gregory Knapik
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Hamed Hani
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Dukagjin M Blakaj
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
- Comprehensive Cancer Center, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Safdar Khan
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
- Orthopedics, Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Nasir Hussain
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
- Anesthesiology, Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Maneesh Tiwari
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Jayesh Vallabh
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
- Physical Medicine & Rehabilitation, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Tristan Weaver
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
- Anesthesiology, Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - William S Marras
- Spine Research Institute, The Ohio State University, Columbus, Ohio, USA
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