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Feier CH, Brown SHM. The effect of visual cues at different heights on sit-to-stand movements in people with and without low back pain. Musculoskelet Sci Pract 2024; 74:103179. [PMID: 39270529 DOI: 10.1016/j.msksp.2024.103179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 09/04/2024] [Accepted: 09/06/2024] [Indexed: 09/15/2024]
Abstract
BACKGROUND Investigating movement strategies that can be utilized to avoid pain-provocation could enhance the management of low back pain episodes. OBJECTIVE To assess the effect of visual cues at different heights on the kinematics of sit-to-stand movements, as well as perceived difficulty and pain levels. DESIGN Cross-over design comparing individuals with low back pain to healthy controls. METHODS 26 asymptomatic controls and 15 individuals with chronic, recurrent low back pain performed 5 sets of 5 sit-to-stand movements. High, middle, and low visual cues were used during sets 2-4. Spinal sagittal plane range of motion, peak spinal flexion and extension angles, and trunk centre of mass velocity were obtained from kinematic data. RESULTS The low cue led to significantly more head and lumbar spine flexion, while the high cue led to significantly more head and thoracic spine extension and increased thoracic spine range of motion. The low back pain group demonstrated a significantly lower vertical trunk centre of mass velocity than the control group during the high cue trials. There was a significant association between higher perceived difficulty scores and lower trunk centre of mass velocity for the low back pain group. Pain scores were not significantly different between cue conditions. CONCLUSION Visual cues can be used to temporarily change the spinal kinematics of sit-to-stand movements in people with and without low back pain. This could be helpful in clinical practice to encourage more, or less, movement in specific spinal regions, and avoid pain provocation to facilitate functional rehabilitation.
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Affiliation(s)
- Cathrine H Feier
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, ON, Canada
| | - Stephen H M Brown
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, ON, Canada.
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2
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Zhu C, Luo L, Li R, Guo J, Wang Q. Wearable Motion Analysis System for Thoracic Spine Mobility With Inertial Sensors. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1884-1895. [PMID: 38753470 DOI: 10.1109/tnsre.2024.3384926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
This study presents a wireless wearable portable system designed for the automatic quantitative spatio-temporal analysis of continuous thoracic spine motion across various planes and degrees of freedom (DOF). This includes automatic motion segmentation, computation of the range of motion (ROM) for six distinct thoracic spine movements across three planes, tracking of motion completion cycles, and visualization of both primary and coupled thoracic spine motions. To validate the system, this study employed an Inter-days experimental setting to conduct experiments involving a total of 957 thoracic spine movements, with participation from two representatives of varying age and gender. The reliability of the proposed system was assessed using the Intraclass Correlation Coefficient (ICC) and Standard Error of Measurement (SEM). The experimental results demonstrated strong ICC values for various thoracic spine movements across different planes, ranging from 0.774 to 0.918, with an average of 0.85. The SEM values ranged from 0.64° to 4.03°, with an average of 1.93°. Additionally, we successfully conducted an assessment of thoracic spine mobility in a stroke rehabilitation patient using the system. This illustrates the feasibility of the system for actively analyzing thoracic spine mobility, offering an effective technological means for non-invasive research on thoracic spine activity during continuous movement states.
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Fayad J, Eltes PE, Lazary A, Cristofolini L, Stagni R. Stereophotogrammetric approaches to multi-segmental kinematics of the thoracolumbar spine: a systematic review. BMC Musculoskelet Disord 2022; 23:1080. [PMID: 36503435 PMCID: PMC9743750 DOI: 10.1186/s12891-022-05925-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 10/12/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Spine disorders are becoming more prevalent in today's ageing society. Motion abnormalities have been linked to the prevalence and recurrence of these disorders. Various protocols exist to measure thoracolumbar spine motion, but a standard multi-segmental approach is still missing. This study aims to systematically evaluate the literature on stereophotogrammetric motion analysis approaches to quantify thoracolumbar spine kinematics in terms of measurement reliability, suitability of protocols for clinical application and clinical significance of the resulting functional assessment. METHODS Electronic databases (PubMed, Scopus and ScienceDirect) were searched until February 2022. Studies published in English, investigating the intersegmental kinematics of the thoracolumbar spine using stereophotogrammetric motion analysis were identified. All information relating to measurement reliability; measurement suitability and clinical significance was extracted from the studies identified. RESULTS Seventy-four studies met the inclusion criteria. 33% of the studies reported on the repeatability of their measurement. In terms of suitability, only 35% of protocols were deemed suitable for clinical application. The spinous processes of C7, T3, T6, T12, L1, L3 and L5 were the most widely used landmarks. The spine segment definitions were, however, found to be inconsistent among studies. Activities of daily living were the main tasks performed. Comparable results between protocols are however still missing. CONCLUSION The literature to date offers various stereophotogrammetric protocols to quantify the multi-segmental motion of the thoracolumbar spine, without a standard guideline being followed. From a clinical point of view, the approaches are still limited. Further research is needed to define a precise motion analysis protocol in terms of segment definition and clinical relevance.
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Affiliation(s)
- Jennifer Fayad
- grid.6292.f0000 0004 1757 1758Department of Industrial Engineering, Alma Mater Studiorum – Università di Bologna, Bologna, Italy ,National Centre for Spinal Disorders, Budapest, Hungary
| | - Peter Endre Eltes
- National Centre for Spinal Disorders, Budapest, Hungary ,In Silico Biomechanics Laboratory, National Centre for Spinal Disorders, Budapest, Hungary
| | - Aron Lazary
- National Centre for Spinal Disorders, Budapest, Hungary
| | - Luca Cristofolini
- grid.6292.f0000 0004 1757 1758Department of Industrial Engineering, Alma Mater Studiorum – Università di Bologna, Bologna, Italy
| | - Rita Stagni
- grid.6292.f0000 0004 1757 1758Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, Alma Mater Studiorum – Università Di Bologna, Bologna, Italy
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4
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Assessing Time-Varying Lumbar Flexion-Extension Kinematics Using Automated Pose Estimation. J Appl Biomech 2022; 38:355-360. [PMID: 35963613 DOI: 10.1123/jab.2022-0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 06/13/2022] [Accepted: 06/24/2022] [Indexed: 11/18/2022]
Abstract
The purpose of this research was to evaluate the algorithm DeepLabCut (DLC) against a 3D motion capture system (Vicon Motion Systems Ltd) in the analysis of lumbar and elbow flexion-extension movements. Data were acquired concurrently and tracked using DLC and Vicon. A novel DLC model was trained using video data derived from a subset of participants (training group). Accuracy and precision were assessed using data derived from the training group as well as in a new set of participants (testing group). Two-way analysis of variance were used to detect significant differences between the training and testing sets, capture methods (Vicon vs DLC), as well as potential higher order interaction effect between these independent variables in the estimation of flexion-extension angles and variability. No significant differences were observed in any planar angles, nor were any higher order interactions observed between each motion capture modality with the training versus testing data sets. Bland-Altman plots were used to depict the mean bias and level of agreement between DLC and Vicon for both training and testing data sets. This research suggests that DLC-derived planar kinematics of both the elbow and lumbar spine are of acceptable accuracy and precision when compared with conventional laboratory gold standards (Vicon).
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Hornung AL, Hornung CM, Mallow GM, Barajas JN, Rush A, Sayari AJ, Galbusera F, Wilke HJ, Colman M, Phillips FM, An HS, Samartzis D. Artificial intelligence in spine care: current applications and future utility. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2022; 31:2057-2081. [PMID: 35347425 DOI: 10.1007/s00586-022-07176-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 01/18/2022] [Accepted: 03/08/2022] [Indexed: 01/20/2023]
Abstract
PURPOSE The field of artificial intelligence is ever growing and the applications of machine learning in spine care are continuously advancing. Given the advent of the intelligence-based spine care model, understanding the evolution of computation as it applies to diagnosis, treatment, and adverse event prediction is of great importance. Therefore, the current review sought to synthesize findings from the literature at the interface of artificial intelligence and spine research. METHODS A narrative review was performed based on the literature of three databases (MEDLINE, CINAHL, and Scopus) from January 2015 to March 2021 that examined historical and recent advancements in the understanding of artificial intelligence and machine learning in spine research. Studies were appraised for their role in, or description of, advancements within image recognition and predictive modeling for spinal research. Only English articles that fulfilled inclusion criteria were ultimately incorporated in this review. RESULTS This review briefly summarizes the history and applications of artificial intelligence and machine learning in spine. Three basic machine learning training paradigms: supervised learning, unsupervised learning, and reinforced learning are also discussed. Artificial intelligence and machine learning have been utilized in almost every facet of spine ranging from localization and segmentation techniques in spinal imaging to pathology specific algorithms which include but not limited to; preoperative risk assessment of postoperative complications, screening algorithms for patients at risk of osteoporosis and clustering analysis to identify subgroups within adolescent idiopathic scoliosis. The future of artificial intelligence and machine learning in spine surgery is also discussed with focusing on novel algorithms, data collection techniques and increased utilization of automated systems. CONCLUSION Improvements to modern-day computing and accessibility to various imaging modalities allow for innovative discoveries that may arise, for example, from management. Given the imminent future of AI in spine surgery, it is of great importance that practitioners continue to inform themselves regarding AI, its goals, use, and progression. In the future, it will be critical for the spine specialist to be able to discern the utility of novel AI research, particularly as it continues to pervade facets of everyday spine surgery.
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Affiliation(s)
- Alexander L Hornung
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | | | - G Michael Mallow
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - J Nicolás Barajas
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Augustus Rush
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Arash J Sayari
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | | | - Hans-Joachim Wilke
- Institute of Orthopaedic Research and Biomechanics, Trauma Research Center Ulm, Ulm University, Ulm, Germany
| | - Matthew Colman
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Frank M Phillips
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Howard S An
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Dino Samartzis
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA.
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Esteban-González P, Sánchez-Romero EA, Villafañe JH. Analysis of the Active Measurement Systems of the Thoracic Range of Movements of the Spine: A Systematic Review and a Meta-Analysis. SENSORS (BASEL, SWITZERLAND) 2022; 22:3042. [PMID: 35459026 PMCID: PMC9026805 DOI: 10.3390/s22083042] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/28/2022] [Accepted: 04/07/2022] [Indexed: 06/14/2023]
Abstract
(1) Objective: to analyze current active noninvasive measurement systems of the thoracic range of movements of the spine. (2) Methods: A systematic review and meta-analysis were performed that included observational or clinical trial studies published in English or Spanish, whose subjects were healthy human males or females ≥18 years of age with reported measurements of thoracic range of motion measured with an active system in either flexion, extension, lateral bending, or axial rotation. All studies that passed the screening had a low risk of bias and good methodological results, according to the PEDro and MINORS scales. The mean values and 95% confidence interval of the reported measures were calculated for different types of device groups. To calculate the differences between the type of device measures, studies were pooled for different types of device groups using Review Manager software. (3) Results: 48 studies were included in the review; all had scores higher than 7.5 over 10 on the PEDro and MINORs methodological rating scales, collecting a total of 2365 healthy subjects, 1053 males and 1312 females; they were 39.24 ± 20.64 years old and had 24.44 ± 3.81 kg/m2 body mass indexes on average. We summarized and analyzed a total of 11,892 measurements: 1298 of flexoextension, 1394 of flexion, 1021 of extension, 491 of side-to-side lateral flexion, 637 of right lateral flexion, 607 of left lateral flexion, 2170 of side-to-side rotation, 2152 of right rotation and 2122 of left rotation. (4) Conclusions: All collected and analyzed measurements of physiological movements of the dorsal spine had very disparate results from each other, the cause of the reason for such analysis is that the measurement protocols of the different types of measurement tools used in these measurements are different and cause measurement biases. To solve this, it is proposed to establish a standardized measurement protocol for all tools.
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Affiliation(s)
- Pablo Esteban-González
- Department of Physiotherapy, Faculty of Sport Sciences, Universidad Europea de Madrid, 28670 Vil-laviciosa de Odón, Madrid, Spain
| | - Eleuterio A. Sánchez-Romero
- Department of Physiotherapy, Faculty of Sport Sciences, Universidad Europea de Madrid, 28670 Vil-laviciosa de Odón, Madrid, Spain
- Musculoskeletal Pain and Motor Control Research Group, Faculty of Sport Sciences, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Madrid, Spain
- Department of Physiotherapy, Faculty of Health Sciences, Universidad Europea de Canarias, 38300 La Orotava, Canary Islands, Spain
- Musculoskeletal Pain and Motor Control Research Group, Faculty of Health Sciences, Universidad Eu-ropea de Canarias, 38300 La Orotava, Canary Islands, Spain
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Oppici L, Grütters K, Garofolini A, Rosenkranz R, Narciss S. Deliberate Practice and Motor Learning Principles to Underpin the Design of Training Interventions for Improving Lifting Movement in the Occupational Sector: A Perspective and a Pilot Study on the Role of Augmented Feedback. Front Sports Act Living 2021; 3:746142. [PMID: 34796319 PMCID: PMC8593185 DOI: 10.3389/fspor.2021.746142] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 10/12/2021] [Indexed: 11/18/2022] Open
Abstract
Spine posture during repetitive lifting is one of the main risk factors for low-back injuries in the occupational sector. It is thus critical to design appropriate intervention strategies for training workers to improve their posture, reducing load on the spine during lifting. The main approach to train safe lifting to workers has been educational; however, systematic reviews and meta-analyses have shown that this approach does not improve lifting movement nor reduces the risk of low back injury. One of the main limitations of this approach lies in the amount, quality and context of practice of the lifting movement. In this article, first we argue for integrating psychologically-grounded perspectives of practice design in the development of training interventions for safe lifting. Principles from deliberate practice and motor learning are combined and integrated. Given the complexity of lifting, a training intervention should occur in the workplace and invite workers to repeatedly practice/perform the lifting movement with the clear goal of improving their lifting-related body posture. Augmented feedback has a central role in creating the suitable condition for achieving such intervention. Second, we focus on spine bending as risk factor and present a pilot study examining the benefits and boundary conditions of different feedback modalities for reducing bending during lifting. The results showed how feedback modalities meet differently key requirements of deliberate practice conditions, i.e., feedback has to be informative, individualized and actionable. Following the proposed approach, psychology will gain an active role in the development of training interventions, contributing to finding solutions for a reduction of risk factors for workers.
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Affiliation(s)
- Luca Oppici
- Psychology of Learning and Instruction, Department of Psychology, School of Science, Technische Universität Dresden, Dresden, Germany.,Centre for Tactile Internet With Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany
| | - Kim Grütters
- Psychology of Learning and Instruction, Department of Psychology, School of Science, Technische Universität Dresden, Dresden, Germany
| | - Alessandro Garofolini
- Institute for Health and Sport (IHES), Victoria University, Melbourne, VIC, Australia
| | - Robert Rosenkranz
- Centre for Tactile Internet With Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany.,Acoustic and Haptic Engineering, Faculty of Electrical and Computer Engineering, Technische Universität Dresden, Dresden, Germany
| | - Susanne Narciss
- Psychology of Learning and Instruction, Department of Psychology, School of Science, Technische Universität Dresden, Dresden, Germany.,Centre for Tactile Internet With Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany
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8
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Trinidad-Fernández M, Beckwée D, Cuesta-Vargas A, González-Sánchez M, Moreno FÁ, González-Jiménez J, Joos E, Vaes P. Differences in movement limitations in different low back pain severity in functional tests using an RGB-D camera. J Biomech 2020; 116:110212. [PMID: 33401131 DOI: 10.1016/j.jbiomech.2020.110212] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 11/25/2020] [Accepted: 12/11/2020] [Indexed: 11/19/2022]
Abstract
Low back pain (LBP) can lead to motor control disturbance which can be one of the causes of reoccurrence of the complaint. It is important to improve our knowledge of movement related disturbances during assessment in LBP and to classify patients according to the severity. The aim of this study is to present differences in kinematic variables using a RGB-D camera in order to classify LBP patients with different severity. A cross-sectional study was carried out. Subjects with non-specific subacute and chronic LBP were screened 6 weeks following an episode. Functional tests were bending trunk test, sock test and sit to stand test. Participants performed as many repetitions as possible during 30 s for each functional test. Angular displacement, velocity and acceleration, linear acceleration, time and repetitions were analysed. Participants were divided into two groups to determine their different LBP severity with a k-means clusters according to the results obtained in Roland Morris questionnaire (RMQ). Comparing different severity groups based on RMQ score (high impact = 17.15, low impact = 7.47), bending trunk test obtained significative differences in linear acceleration (p = 0.002-0.01). The differences of total linear acceleration during the Sit to Stand test were significative (p = 0.004-0.02). Sock test showed not significative differences between groups (p > 0.05). Linear acceleration variables during Sit to Stand test and Bending trunk test were significatively different between the different severity groups. RGB-D camera system and functional tests can detect kinematic differences in different type of LBP according to the functionality. Trial registration: ClinicalTrials.gov NCT03293095 "Functional Task Kinematic in Musculoskeletal Pathology" September 26, 2017.
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Affiliation(s)
- Manuel Trinidad-Fernández
- Rehabilitation Research (RERE) Research Group, Vrije Universiteit Brussel, 1090 Brussels, Belgium; Physiotherapy Department, Institute of Biomedical Research in Malaga (IBIMA), Clinimetric Group F-14, Universidad de Málaga, 29010 Málaga, Spain
| | - David Beckwée
- Rehabilitation Research (RERE) Research Group, Vrije Universiteit Brussel, 1090 Brussels, Belgium; Department of Rehabilitation Sciences and Physiotherapy, University of Antwerp, 2000 Antwerp, Belgium
| | - Antonio Cuesta-Vargas
- Physiotherapy Department, Institute of Biomedical Research in Malaga (IBIMA), Clinimetric Group F-14, Universidad de Málaga, 29010 Málaga, Spain; School of Clinical Science, Faculty of Health Science, Queensland University Technology, 4072 Brisbane, Australia.
| | - Manuel González-Sánchez
- Physiotherapy Department, Institute of Biomedical Research in Malaga (IBIMA), Clinimetric Group F-14, Universidad de Málaga, 29010 Málaga, Spain
| | - Francisco-Ángel Moreno
- Systems Engineering and Automation Deparment, Institute of Biomedical Research in Malaga (IBIMA), Universidad de Málaga, 29010 Málaga, Spain
| | - Javier González-Jiménez
- Systems Engineering and Automation Deparment, Institute of Biomedical Research in Malaga (IBIMA), Universidad de Málaga, 29010 Málaga, Spain
| | - Erika Joos
- Physical Medicine & Rehabilitation Department, UZ Brussel, 1090 Brussels, Belgium
| | - Peter Vaes
- Rehabilitation Research (RERE) Research Group, Vrije Universiteit Brussel, 1090 Brussels, Belgium
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Remedios SM, Armstrong DP, Graham RB, Fischer SL. Exploring the Application of Pattern Recognition and Machine Learning for Identifying Movement Phenotypes During Deep Squat and Hurdle Step Movements. Front Bioeng Biotechnol 2020; 8:364. [PMID: 32426346 PMCID: PMC7212384 DOI: 10.3389/fbioe.2020.00364] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 03/31/2020] [Indexed: 12/29/2022] Open
Abstract
Background Movement screens are increasingly used in sport and rehabilitation to evaluate movement competency. However, common screens are often evaluated using subjective visual detection of a priori prescribed discrete movement features (e.g., spine angle at maximum squat depth) and may not account for whole-body movement coordination, or associations between different discrete features. Objective To apply pattern recognition and machine learning techniques to identify whole-body movement pattern phenotypes during the performance of exemplar functional movement screening tasks; the deep squat and hurdle step. Additionally, we also aimed to compare how discrete kinematic measures, commonly used to score movement competency, differed between emergent groups identified via pattern recognition and machine learning. Methods Principal component analysis (PCA) was applied to 3-dimensional (3D) trajectory data from participant's deep squat (DS) and hurdle step performance, identifying emerging features that describe orthogonal modes of inter-trial variance in the data. A gaussian mixture model (GMM) was fit and used to cluster the principal component scores as an unsupervised machine learning approach to identify emergent movement phenotypes. Between group features were analyzed using a one-way ANOVA to determine if the objective classifications were significantly different from one another. Results Three clusters (i.e., phenotypes) emerged for the DS and right hurdle step (RHS) and 4 phenotypes emerged for the left hurdle step (LHS). Selected discrete points commonly used to score DS and hurdle step movements were different between emergent groups. In regard to the select discrete kinematic measures, 4 out of 5, 7 out of 7 and 4 out of 7, demonstrated a main effect (p < 0.05) between phenotypes for the DS, RHS, and LHS respectively. Conclusion Findings support that whole-body movement analysis, pattern recognition and machine learning techniques can objectively identify movement behavior phenotypes without the need to a priori prescribe movement features. However, we also highlight important considerations that can influence outcomes when using machine learning for this purpose.
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Affiliation(s)
- Sarah M Remedios
- Occupational Biomechanics and Ergonomics Laboratory, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
| | - Daniel P Armstrong
- Occupational Biomechanics and Ergonomics Laboratory, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
| | - Ryan B Graham
- Spine Biomechanics Laboratory, School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada
| | - Steven L Fischer
- Occupational Biomechanics and Ergonomics Laboratory, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
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10
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A Subject-Specific Approach to Detect Fatigue-Related Changes in Spine Motion Using Wearable Sensors. SENSORS 2020; 20:s20092646. [PMID: 32384664 PMCID: PMC7249110 DOI: 10.3390/s20092646] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/21/2020] [Accepted: 05/01/2020] [Indexed: 02/06/2023]
Abstract
An objective method to detect muscle fatigue-related kinematic changes may reduce workplace injuries. However, heterogeneous responses to muscle fatigue suggest that subject-specific analyses are necessary. The objectives of this study were to: (1) determine if wearable inertial measurement units (IMUs) could be used in conjunction with a spine motion composite index (SMCI) to quantify subject-specific changes in spine kinematics during a repetitive spine flexion-extension (FE) task; and (2) determine if the SMCI was correlated with measures of global trunk muscle fatigue. Spine kinematics were measured using wearable IMUs in 10 healthy adults during a baseline set followed by 10 sets of 50 spine FE repetitions. After each set, two fatigue measures were collected: perceived level of fatigue using a visual analogue scale (VAS), and maximal lift strength. SMCIs incorporating 10 kinematic variables from 2 IMUs (pelvis and T8 vertebrae) were calculated and used to quantify subject-specific changes in movement. A main effect of set was observed (F (1.7, 15.32) = 10.42, p = 0.002), where the SMCI became significantly greater than set 1 starting at set 4. Significant correlations were observed between the SMCI and both fatigue VAS and maximal lift strength at the individual and study level. These findings support the use of wearable IMUs to detect subject-specific changes in spine motion associated with muscle fatigue.
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11
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Beaudette SM, Briar KJ, Mavor MP, Graham RB. The effect of head and gaze orientation on spine kinematics during forward flexion. Hum Mov Sci 2020; 70:102590. [PMID: 32217207 DOI: 10.1016/j.humov.2020.102590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 12/12/2019] [Accepted: 01/31/2020] [Indexed: 01/24/2023]
Abstract
Compound, or awkward, spine postures have been suggested as a biomechanical risk factor for low back injury. This experiment investigates the influence of head (i.e. head-on-torso) and gaze (i.e. eye-in-head) orientation on three-dimensional (3D) neck and spine range of motion (ROM) during forward flexion movements. To emulate previous experimental protocols and replicate real-world scenarios, a sample of ten young, healthy males (mean ± standard deviation: age: 20.8 ± 1.03 years, height: 180.2 ± 7.36 cm, and mass: 81.9 ± 6.47 kg) completed forward flexion movements with a constrained and unconstrained pelvis, respectively. Surface kinematics were gathered from the head and spine (C7-S1). Movements were completed under a baseline condition as well as upward, downward, leftward, and rightward head and gaze orientations. For each condition, mean neck angle and inter-segmental spine (C7T1 through L5S1) ROM were evaluated. The results demonstrate that directed head and gaze orientations can influence the ROM of specific spine regions during a forward flexion task. With leftward and rightward directed head and gaze orientations, the neck became increasingly twisted and superior thoracic segments (i.e. C7T1-T2T3) were significantly more twisted during the leftward head orientation condition than the baseline condition. With upward and downward directed head and gaze orientations, a similar effect was observed for neck and superior thoracic (i.e. C7T1-T4T5) flexion-extension. Interestingly, it was also demonstrated that changes in upward/downward head orientation can also change flexion-extension kinematics of the thoracolumbar region as well (i.e. T7T8-L1L2), suggesting that head postures requiring neck extension may also promote extension throughout these spine regions. These findings provide evidence for a functional link between changes in neck flexion-extension posture and flexion-extension movement of the thoracolumbar region of the spine.
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Affiliation(s)
- Shawn M Beaudette
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada
| | - K Josh Briar
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada
| | - Matthew P Mavor
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada
| | - Ryan B Graham
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada.
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12
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Beange KHE, Chan ADC, Beaudette SM, Graham RB. Concurrent validity of a wearable IMU for objective assessments of functional movement quality and control of the lumbar spine. J Biomech 2019; 97:109356. [PMID: 31668717 DOI: 10.1016/j.jbiomech.2019.109356] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 08/14/2019] [Accepted: 09/18/2019] [Indexed: 11/18/2022]
Abstract
Inertial measurement units (IMUs) are being recognized in clinical and rehabilitation settings for their ability to assess movement-related disorders of the spine for better guidance of treatment-planning and tracking of recovery. This study evaluated the Mbientlab MetaMotionR IMUs, relative to Vicon motion capture equipment in measuring local dynamic stability of the spine (quantified using maximum finite-time Lyapunov exponent; λmax), lumbopelvic coordination (quantified using mean absolute relative phase; MARP), and intersegmental motor variability (quantified using deviation phase; DP) of lumbopelvic segments in 10 participants during 35 cycles of repetitive spine flexion-extension (FE). Intraclass correlations were strong between systems when using both the FE angle time-series and the sum of squares (SS) time-series to measure local dynamic stability (0.807 ≤ICC2,1λmax,FE ≤ 0.919; 0.738 ≤ ICC2,1λmax,SS ≤ 0.868), sagittal-plane lumbopelvic coordination (0.961 ≤ICC2,1MARP ≤ 0.963), and sagittal-plane lumbopelvic variability (0.961 ≤ICC2,1DP ≤ 0.963). It was concluded that the MetaMotionR IMUs can be reliably used for measuring features associated with spine movement quality and motor control during a repetitive FE task. Future work will assess the reliability of sensor placement, performance during multi-directional movements, and ability to discern clinical and healthy populations based on assessment of movement quality and control.
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Affiliation(s)
- Kristen H E Beange
- Department of Systems and Computer Engineering, Faculty of Engineering and Design, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada; Ottawa-Carleton Institute for Biomedical Engineering, Ottawa, Ontario, Canada
| | - Adrian D C Chan
- Department of Systems and Computer Engineering, Faculty of Engineering and Design, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada; School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, 200 Lees Avenue, Ottawa, Ontario K1N 6N5, Canada; Ottawa-Carleton Institute for Biomedical Engineering, Ottawa, Ontario, Canada
| | - Shawn M Beaudette
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, 200 Lees Avenue, Ottawa, Ontario K1N 6N5, Canada
| | - Ryan B Graham
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, 200 Lees Avenue, Ottawa, Ontario K1N 6N5, Canada; Ottawa-Carleton Institute for Biomedical Engineering, Ottawa, Ontario, Canada.
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