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Gan X, Liu X, Cai D, Zhang R, Li F, Fang H, Huang J, Qiu C, Zhan H. Wearable accelerometers reveal objective assessment of walking symmetry and regularity in idiopathic scoliosis patients. PeerJ 2024; 12:e17739. [PMID: 39035168 PMCID: PMC11259127 DOI: 10.7717/peerj.17739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/23/2024] [Indexed: 07/23/2024] Open
Abstract
Background Scoliosis is a multifaceted three-dimensional deformity that significantly affects patients' balance function and walking process. While existing research primarily focuses on spatial and temporal parameters of walking and trunk/pelvic kinematics asymmetry, there remains controversy regarding the symmetry and regularity of bilateral lower limb gait. This study aims to investigate the symmetry and regularity of bilateral lower limb gait and examine the balance control strategy of the head during walking in patients with idiopathic scoliosis. Methods The study involved 17 patients with idiopathic scoliosis of Lenke 1 and Lenke 5 classifications, along with 17 healthy subjects for comparison. Three-dimensional accelerometers were attached to the head and L5 spinous process of each participant, and three-dimensional motion acceleration signals were collected during a 10-meter walking test. Analysis of the collected acceleration signals involved calculating five variables related to the symmetry and regularity of walking: root mean square (RMS) of the acceleration signal, harmonic ratio (HR), step regularity, stride regularity, and gait symmetry. Results Our analysis reveals that, during the walking process, the three-dimensional motion acceleration signals acquired from the lumbar region of patients diagnosed with idiopathic scoliosis exhibit noteworthy disparities in the RMS of the vertical axis (RMS-VT) and the HR of the vertical axis (HR-VT) when compared to the corresponding values in the healthy control (RMS-VT: 1.6 ± 0.41 vs. 3 ± 0.47, P < 0.05; HR-VT: 3 ± 0.72 vs. 3.9 ± 0.71, P < 0.05). Additionally, the motion acceleration signals of the head in three-dimensional space, including the RMS in the anterior-posterior and vertical axis, the HR-VT, and the values of step regularity in both anterior-posterior and vertical axis, as well as the values of stride regularity in all three axes, are all significantly lower than those in the healthy control group (P < 0.05). Conclusion The findings of the analysis suggest that the application of three-dimensional accelerometer sensors proves efficacious and convenient for scrutinizing the symmetry and regularity of walking in individuals with idiopathic scoliosis. Distinctive irregularities in gait symmetry and regularity manifest in patients with idiopathic scoliosis, particularly within the antero-posterior and vertical direction. Moreover, the dynamic balance control strategy of the head in three-dimensional space among patients with idiopathic scoliosis exhibits a relatively conservative nature when compared to healthy individuals.
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Affiliation(s)
- Xiaopeng Gan
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Xin Liu
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Danxian Cai
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Rongbin Zhang
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Fanqiang Li
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Haohuang Fang
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Jingrou Huang
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Chenguang Qiu
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Hongrui Zhan
- Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
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Bezold J, Krell-Roesch J, Eckert T, Jekauc D, Woll A. Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review. Eur Rev Aging Phys Act 2021; 18:15. [PMID: 34243722 PMCID: PMC8272315 DOI: 10.1186/s11556-021-00266-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 06/13/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Higher age and cognitive impairment are associated with a higher risk of falling. Wearable sensor technology may be useful in objectively assessing motor fall risk factors to improve physical exercise interventions for fall prevention. This systematic review aims at providing an updated overview of the current research on wearable sensors for fall risk assessment in older adults with or without cognitive impairment. Therefore, we addressed two specific research questions: 1) Can wearable sensors provide accurate data on motor performance that may be used to assess risk of falling, e.g., by distinguishing between faller and non-faller in a sample of older adults with or without cognitive impairment?; and 2) Which practical recommendations can be given for the application of sensor-based fall risk assessment in individuals with CI? A systematic literature search (July 2019, update July 2020) was conducted using PubMed, Scopus and Web of Science databases. Community-based studies or studies conducted in a geriatric setting that examine fall risk factors in older adults (aged ≥60 years) with or without cognitive impairment were included. Predefined inclusion criteria yielded 16 cross-sectional, 10 prospective and 2 studies with a mixed design. RESULTS Overall, sensor-based data was mainly collected during walking tests in a lab setting. The main sensor location was the lower back to provide wearing comfort and avoid disturbance of participants. The most accurate fall risk classification model included data from sit-to-walk and walk-to-sit transitions collected over three days of daily life (mean accuracy = 88.0%). Nine out of 28 included studies revealed information about sensor use in older adults with possible cognitive impairment, but classification models performed slightly worse than those for older adults without cognitive impairment (mean accuracy = 79.0%). CONCLUSION Fall risk assessment using wearable sensors is feasible in older adults regardless of their cognitive status. Accuracy may vary depending on sensor location, sensor attachment and type of assessment chosen for the recording of sensor data. More research on the use of sensors for objective fall risk assessment in older adults is needed, particularly in older adults with cognitive impairment. TRIAL REGISTRATION This systematic review is registered in PROSPERO ( CRD42020171118 ).
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Affiliation(s)
- Jelena Bezold
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131 Karlsruhe, Germany
| | - Janina Krell-Roesch
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131 Karlsruhe, Germany
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Tobias Eckert
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131 Karlsruhe, Germany
| | - Darko Jekauc
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131 Karlsruhe, Germany
| | - Alexander Woll
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131 Karlsruhe, Germany
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Dasgupta P, VanSwearingen J, Godfrey A, Redfern M, Montero-Odasso M, Sejdic E. Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review. IEEE Trans Neural Syst Rehabil Eng 2021; 29:249-261. [PMID: 33315570 PMCID: PMC7995554 DOI: 10.1109/tnsre.2020.3044260] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion's translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults.
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Betteridge CMW, Natarajan P, Fonseka RD, Ho D, Mobbs R, Choy WJ. Objective falls-risk prediction using wearable technologies amongst patients with and without neurogenic gait alterations: a narrative review of clinical feasibility. Mhealth 2021; 7:61. [PMID: 34805392 PMCID: PMC8572751 DOI: 10.21037/mhealth-21-7] [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: 02/16/2021] [Accepted: 06/12/2021] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVES The present narrative review aims to collate the literature regarding the current use of wearable gait measurement devices for falls-risk assessment in neurological and non-neurological populations. Thereby, this review seeks to determine the extent to which the aforementioned barriers inhibit clinical use. BACKGROUND Falls contribute a significant disease burden in most western countries, resulting in increased morbidity and mortality with substantial therapeutic costs. The recent development of gait analysis sensor technologies has enabled quantitative measurement of several gait features related to falls risk. However, three main barriers to implementation exist: accurately measuring gait-features associated with falls, differentiating between fallers and non-fallers using these gait features, and the accuracy of falls predictive algorithms developed using these gait measurements. METHODS Searches of Medline, PubMed, Embase and Scopus were screened to identify 46 articles relevant to the present study. Studies performing gait assessment using any wearable gait assessment device and analysing correlation with the occurrence of falls during a retrospective or prospective study period were included. Risk of Bias was assessed using the Centre for Evidence Based Medicine (CEBM) Criteria. CONCLUSIONS Falls prediction algorithms based entirely, or in-part, on gait data have shown comparable or greater success of predicting falls than existing stratification scoring systems such as the 10-meter walk test or timed-up-and-go. However, data is lacking regarding their accuracy in neurological patient populations. Inertial measurement units (IMU) have displayed competency in obtaining and interpreting gait metrics relevant to falls risk. They have the potential to enhance the accuracy and efficiency of falls risk assessment in inpatient and outpatient setting.
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Affiliation(s)
- Callum M. W. Betteridge
- Department of Medicine, University of New South Wales, Sydney, Australia
- NeuroSpineClinic, Suite 7 Level 7, Prince of Wales Private Hospital, Randwick, Australia
- NeuroSpine Surgery Research Group, Sydney, Australia
- Wearables and Gait Assessment Group, Sydney, Australia
| | - Pragadesh Natarajan
- Department of Medicine, University of New South Wales, Sydney, Australia
- NeuroSpineClinic, Suite 7 Level 7, Prince of Wales Private Hospital, Randwick, Australia
- NeuroSpine Surgery Research Group, Sydney, Australia
- Wearables and Gait Assessment Group, Sydney, Australia
| | - R. Dineth Fonseka
- Department of Medicine, University of New South Wales, Sydney, Australia
- NeuroSpineClinic, Suite 7 Level 7, Prince of Wales Private Hospital, Randwick, Australia
- NeuroSpine Surgery Research Group, Sydney, Australia
- Wearables and Gait Assessment Group, Sydney, Australia
| | - Daniel Ho
- Department of Medicine, University of New South Wales, Sydney, Australia
- NeuroSpineClinic, Suite 7 Level 7, Prince of Wales Private Hospital, Randwick, Australia
- NeuroSpine Surgery Research Group, Sydney, Australia
- Wearables and Gait Assessment Group, Sydney, Australia
| | - Ralph Mobbs
- Department of Medicine, University of New South Wales, Sydney, Australia
- NeuroSpineClinic, Suite 7 Level 7, Prince of Wales Private Hospital, Randwick, Australia
- NeuroSpine Surgery Research Group, Sydney, Australia
- Wearables and Gait Assessment Group, Sydney, Australia
| | - Wen Jie Choy
- Department of Medicine, University of New South Wales, Sydney, Australia
- NeuroSpineClinic, Suite 7 Level 7, Prince of Wales Private Hospital, Randwick, Australia
- NeuroSpine Surgery Research Group, Sydney, Australia
- Wearables and Gait Assessment Group, Sydney, Australia
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Gillain S, Boutaayamou M, Schwartz C, Dardenne N, Bruyère O, Brüls O, Croisier JL, Salmon E, Reginster JY, Garraux G, Petermans J. Gait symmetry in the dual task condition as a predictor of future falls among independent older adults: a 2-year longitudinal study. Aging Clin Exp Res 2019; 31:1057-1067. [PMID: 31069697 DOI: 10.1007/s40520-019-01210-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Accepted: 04/27/2019] [Indexed: 11/27/2022]
Abstract
BACKGROUND Given the potential consequences of falls among older adults, a major challenge is to identify people at risk before the first event. In this context, gait parameters have been suggested as markers of fall risk. AIM To examine, among older people, the prospective relationship between gait patterns assessed in comfortable and challenging walking conditions, and future fall(s). METHOD A total of 105 adults older than 65 years, living independently at home and without a recent fall history were included in a 2-year, longitudinal, observational study. All underwent physical and functional assessment. Gait speed, stride length, frequency, symmetry and regularity and Minimum Toe Clearance (MTC) were recorded in comfortable (CW), fast (FW) and dual task walking (DTW) conditions. Gait parameter changes occurring between CW and FW and between CW and DTW were calculated and expressed in percent. DTW cost was calculated as the change of DTW relative to CW. Fall events were recorded using fall diaries. Comparisons according to fall occurrence were performed by means of univariate analysis and multivariate binary logistic regression analysis. RESULTS Two-year follow-up was available for 96 participants, of whom 35 (36.5%) fell at least once. Comparative analysis showed that future fallers had shorter FW stride length and higher symmetry DTW cost than non-fallers (p < 0.05). Binary logistic regression analysis showed that each additional percent of stride symmetry cost was associated with an increase in future fall risk (odds ratio 1.018, 95% Confidence Interval (CI) 1.002-1.033; p = 0.027). DISCUSSION Our results confirm the association between a symmetry decrease in DTW and future fall(s). Indeed in this study, the mean symmetry DTW cost in fallers is almost 20% higher than in non-fallers, meaning a fall risk that is around 36% higher than among non-fallers. CONCLUSION This exploratory study shows the usefulness of considering gait parameters, particularly symmetry in challenging walking conditions, for early identification of future fallers.
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Affiliation(s)
- Sophie Gillain
- Geriatric Department, Liège University Hospital, C.H.U. site NDB, Route de Gaillarmont, 600, 4032, Chênée, Belgium.
| | - Mohamed Boutaayamou
- INTELSIG Laboratory, Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium
| | - Cedric Schwartz
- Laboratory of Human Motion Analysis-LAMH, University of Liège, Liège, Belgium
| | - Nadia Dardenne
- Laboratory of Human Motion Analysis-LAMH, University of Liège, Liège, Belgium
| | - Olivier Bruyère
- Research Unit in Public Health, Epidemiology and Health Economics, University of Liege, Liège, Belgium
| | - Olivier Brüls
- Laboratory of Human Motion Analysis-LAMH, University of Liège, Liège, Belgium
| | - Jean-Louis Croisier
- Laboratory of Human Motion Analysis-LAMH, University of Liège, Liège, Belgium
- Science of Motricity Department, University of Liège, Liège, Belgium
| | - Eric Salmon
- Neurology Department and GIGA Cyclotron Research Centre, University of Liège, Liège, Belgium
| | - Jean-Yves Reginster
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Ageing, Liège, Belgium
| | - Gaëtan Garraux
- Laboratory of Human Motion Analysis-LAMH, University of Liège, Liège, Belgium
- Neurology Department and GIGA Cyclotron Research Centre, University of Liège, Liège, Belgium
| | - Jean Petermans
- Geriatric Department, Liège University Hospital, C.H.U. site NDB, Route de Gaillarmont, 600, 4032, Chênée, Belgium
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Wearable Inertial Sensing for ICT Management of Fall Detection, Fall Prevention, and Assessment in Elderly. TECHNOLOGIES 2018. [DOI: 10.3390/technologies6040091] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Falls are one of the most common causes of accidental injury: approximately, 37.3 million falls requiring medical intervention occur each year. Fall-related injuries may cause disabilities, and in some extreme cases, premature death among older adults, which has a significant impact on health and social care services. In recent years, information and communication technologies (ICT) have helped enhance the autonomy and quality of life of elderly people, and significantly reduced the costs associated with elderly care. We designed and developed an integrated fall detection and prevention ICT service for elderly people, which was based on two wearable smart sensors, called, respectively, WIMU fall detector and WIMU data-logger (Wearable Inertial Measurement Unit, WIMU); their goal was either to detect falls and promptly react in case of fall events, or to quantify fall risk instrumentally. The WIMU fall detector is intended to be worn at the waist level for use during activities of daily living; the WIMU logger is intended for the quantitative assessment of tested individuals during the execution of clinical tests. Both devices provide their service in conjunction with an Android mobile device. The ICT service was developed and tested within the European project I-DONT-FALL (Integrated prevention and Detection sOlutioNs Tailored to the population and risk factors associated with FALLs, funded by EU, action EU CIP-ICT-PSP-2011-5: GA #CIP-297225). Sensor description and preliminary testing results are provided in this paper.
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