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Marom P, Brik M, Agay N, Dankner R, Katzir Z, Keshet N, Doron D. The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability. SENSORS (BASEL, SWITZERLAND) 2024; 24:3594. [PMID: 38894386 PMCID: PMC11175355 DOI: 10.3390/s24113594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/20/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024]
Abstract
An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower extremity disability. Spatiotemporal gait parameters were extracted from the treadmill and from two smartphones, one on each leg. Inter-device reliability was evaluated using Pearson correlation, intra-cluster correlation coefficient (ICC), and Cohen's d, comparing the application's readings from the two phones. Validity was assessed by comparing readings from each phone to the treadmill. Twenty-eight patients completed the study; the median age was 45.5 years, and 61% were males. The ICC between the phones showed a high correlation (r = 0.89-1) and good-to-excellent reliability (ICC range, 0.77-1) for all the gait parameters examined. The correlations between the phones and the treadmill were mostly above 0.8. The ICC between each phone and the treadmill demonstrated moderate-to-excellent validity for all the gait parameters (range, 0.58-1). Only 'step length of the impaired leg' showed poor-to-good validity (range, 0.37-0.84). Cohen's d effect size was small (d < 0.5) for all the parameters. The studied application demonstrated good reliability and validity for spatiotemporal gait assessment in patients with unilateral lower limb disability.
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Affiliation(s)
- Pnina Marom
- Reuth Research and Development Institute, Reuth Rehabilitation Hospital, Tel Aviv 6772830, Israel; (M.B.); (R.D.); (Z.K.)
- Department of Health Promotion, School of Public Health, Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Michael Brik
- Reuth Research and Development Institute, Reuth Rehabilitation Hospital, Tel Aviv 6772830, Israel; (M.B.); (R.D.); (Z.K.)
| | - Nirit Agay
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Ramat Gan 5262000, Israel;
| | - Rachel Dankner
- Reuth Research and Development Institute, Reuth Rehabilitation Hospital, Tel Aviv 6772830, Israel; (M.B.); (R.D.); (Z.K.)
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Ramat Gan 5262000, Israel;
- Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Zoya Katzir
- Reuth Research and Development Institute, Reuth Rehabilitation Hospital, Tel Aviv 6772830, Israel; (M.B.); (R.D.); (Z.K.)
- Department of General Medicine, School of Medicine, Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Naama Keshet
- Department of Physical Therapy, Reuth Rehabilitation Hospital, Tel Aviv 6772830, Israel;
| | - Dana Doron
- Ambulatory Day Care, Reuth Rehabilitation Hospital, Tel Aviv 6772830, Israel
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Rasouli Kahaki Z, Choobineh A, Razeghi M, Karimi MT, Safarpour AR. Dynamic stability evaluation of trunk accelerations during walking in blind and sighted individuals. BMC Ophthalmol 2024; 24:127. [PMID: 38515065 PMCID: PMC10958951 DOI: 10.1186/s12886-024-03394-w] [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: 07/15/2023] [Accepted: 03/13/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Dynamic stability is a fundamental goal in standing activities. In this regard, monitoring, analysis, and interventions made to improve stability is a research topic investigated in the biomechanics of human movements. Vision has a major role to play in controlling human movement. Nonetheless, little is known about the effects of visual deprivation, especially from birth on dynamic gait stability. METHODS The current study was conducted on 20 congenital blind and 10 sighted people (15-38 years). To evaluate the dynamic stability, descriptive data, harmonic ratio (HR), improved harmonic ratio (iHR), and root mean square (RMS), based on trunk acceleration data were measured in three axes: anteroposterior (AP), vertical (V), and mediolateral (ML) while participants walked an eight-meter straight path. RESULTS In the comparison of blind and sighted people (eyes open), standard deviation, HR, iHR, and RMS indices were found to be significantly different in both AP and V directions. All the mentioned parameters were significantly lower in blind than in sighted participants. In the comparison of blind people and sighted ones with closed eyes, changes were observed in the maximum, range, standard deviation, and RMS only in the AP axis. In the comparison between eyes open and closed in sighted people, a significant difference was found only in the harmonic ratio of the vertical axis. CONCLUSION Visual deprivation led to a decrease in dynamic stability parameters in the AP and V axes. Even the movement of sighted people in unchallenged conditions is dependent on visual information.
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Affiliation(s)
- Zeinab Rasouli Kahaki
- Student Research Committee, Department of Ergonomics, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Alireza Choobineh
- Research Center for Health Sciences, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohsen Razeghi
- Department of physiotherapy, School of Rehabilitation Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Taghi Karimi
- Department of Orthotics and Prosthetics, School of Rehabilitation Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Ali Reza Safarpour
- Gastroenterohepatology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Strongman C, Cavallerio F, Timmis MA, Morrison A. A Scoping Review of the Validity and Reliability of Smartphone Accelerometers When Collecting Kinematic Gait Data. SENSORS (BASEL, SWITZERLAND) 2023; 23:8615. [PMID: 37896708 PMCID: PMC10611257 DOI: 10.3390/s23208615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 10/18/2023] [Accepted: 10/19/2023] [Indexed: 10/29/2023]
Abstract
The aim of this scoping review is to evaluate and summarize the existing literature that considers the validity and/or reliability of smartphone accelerometer applications when compared to 'gold standard' kinematic data collection (for example, motion capture). An electronic keyword search was performed on three databases to identify appropriate research. This research was then examined for details of measures and methodology and general study characteristics to identify related themes. No restrictions were placed on the date of publication, type of smartphone, or participant demographics. In total, 21 papers were reviewed to synthesize themes and approaches used and to identify future research priorities. The validity and reliability of smartphone-based accelerometry data have been assessed against motion capture, pressure walkways, and IMUs as 'gold standard' technology and they have been found to be accurate and reliable. This suggests that smartphone accelerometers can provide a cheap and accurate alternative to gather kinematic data, which can be used in ecologically valid environments to potentially increase diversity in research participation. However, some studies suggest that body placement may affect the accuracy of the result, and that position data correlate better than actual acceleration values, which should be considered in any future implementation of smartphone technology. Future research comparing different capture frequencies and resulting noise, and different walking surfaces, would be useful.
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Affiliation(s)
- Clare Strongman
- Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, East Road, Cambridge CB1 1PT, UK; (F.C.); (M.A.T.); (A.M.)
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Rozanski G, Delgado A, Putrino D. Spatiotemporal parameters from remote smartphone-based gait analysis are associated with lower extremity functional scale categories. FRONTIERS IN REHABILITATION SCIENCES 2023; 4:1189376. [PMID: 37565184 PMCID: PMC10410151 DOI: 10.3389/fresc.2023.1189376] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/12/2023] [Indexed: 08/12/2023]
Abstract
Objective Self-report tools are recommended in research and clinical practice to capture individual perceptions regarding health status; however, only modest correlations are found with performance-based results. The Lower Extremity Functional Scale (LEFS) is one well-validated measure of impairment affecting physical activities that has been compared with objective tests. More recently, mobile gait assessment software can provide comprehensive motion tracking output from ecologically valid environments, but how this data relates to subjective scales is unknown. Therefore, the association between the LEFS and walking variables remotely collected by a smartphone was explored. Methods Proprietary algorithms extracted spatiotemporal parameters detected by a standard integrated inertial measurement unit from 132 subjects enrolled in physical therapy for orthopedic or neurological rehabilitation. Users initiated ambulation recordings and completed questionnaires through the OneStep digital platform. Discrete categories were created based on LEFS score cut-offs and Analysis of Variance was applied to estimate the difference in gait metrics across functional groups (Low-Medium-High). Results The main finding of this cross-sectional retrospective study is that remotely-collected biomechanical walking data are significantly associated with individuals' self-evaluated function as defined by LEFS categorization (n = 132) and many variables differ between groups. Velocity was found to have the strongest effect size. Discussion When patients are classified according to subjective mobility level, there are significant differences in quantitative measures of ambulation analyzed with smartphone-based technology. Capturing real-time information about movement is important to obtain accurate impressions of how individuals perform in daily life while understanding the relationship between enacted activity and relevant clinical outcomes.
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Affiliation(s)
- Gabriela Rozanski
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Park J, Lee HJ, Park JS, Kim CH, Jung WJ, Won S, Bae JB, Han JW, Kim KW. Development of a Gait Feature-Based Model for Classifying Cognitive Disorders Using a Single Wearable Inertial Sensor. Neurology 2023; 101:e12-e19. [PMID: 37188539 PMCID: PMC10351320 DOI: 10.1212/wnl.0000000000207372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 03/17/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Gait changes are potential markers of cognitive disorders (CDs). We developed a model for classifying older adults with CD from those with normal cognition using gait speed and variability captured from a wearable inertial sensor and compared its diagnostic performance for CD with that of the model using the Mini-Mental State Examination (MMSE). METHODS We enrolled community-dwelling older adults with normal gait from the Korean Longitudinal Study on Cognitive Aging and Dementia and measured their gait features using a wearable inertial sensor placed at the center of body mass while they walked on a 14-m long walkway thrice at comfortable paces. We randomly split our entire dataset into the development (80%) and validation (20%) datasets. We developed a model for classifying CD using logistic regression analysis from the development dataset and validated it in the validation dataset. In both datasets, we compared the diagnostic performance of the model with that using the MMSE. We estimated optimal cutoff score of our model using receiver operator characteristic analysis. RESULTS In total, 595 participants were enrolled, of which 101 of them experienced CD. Our model included both gait speed and temporal gait variability and exhibited good diagnostic performance for classifying CD from normal cognition in both the development (area under the receiver operator characteristic curve [AUC] = 0.788, 95% CI 0.748-0.823, p < 0.001) and validation datasets (AUC = 0.811, 95% CI 0.729-0.877, p < 0.001). Our model showed comparable diagnostic performance for CD with that of the model using the MMSE in both the development (difference in AUC = 0.026, standard error [SE] = 0.043, z statistic = 0.610, p = 0.542) and validation datasets (difference in AUC = 0.070, SE = 0.073, z statistic = 0.956, p = 0.330). The optimal cutoff score of the gait-based model was >-1.56. DISCUSSION Our gait-based model using a wearable inertial sensor may be a promising diagnostic marker of CD in older adults. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that gait analysis can accurately distinguish older adults with CDs from healthy controls.
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Affiliation(s)
- Jeongbin Park
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Hyang Jun Lee
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Ji Sun Park
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Chae Hyun Kim
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea.
| | - Woo Jin Jung
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Seunghyun Won
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Jong Bin Bae
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Ji Won Han
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea
| | - Ki Woong Kim
- From the PlanB4U Research Institute (J.P., C.H.K., W.J.J., K.W.K.), Seongnam; Department of Neuropsychiatry (H.J.L., J.B.B., J.W.H., K.W.K.), Seoul National University Bundang Hospital, Seongnam; Department of Brain and Cognitive Science (J.S.P., K.W.K.), Seoul National University College of Natural Sciences; Medical Research Collaborating Center (S.W.), Seoul National University Bundang Hospital, Seongnam; and Department of Psychiatry (K.W.K.), Seoul National University, College of Medicine, Korea.
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Werner C, Hezel N, Dongus F, Spielmann J, Mayer J, Becker C, Bauer JM. Validity and reliability of the Apple Health app on iPhone for measuring gait parameters in children, adults, and seniors. Sci Rep 2023; 13:5350. [PMID: 37005465 PMCID: PMC10067003 DOI: 10.1038/s41598-023-32550-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 03/29/2023] [Indexed: 04/04/2023] Open
Abstract
This study assessed the concurrent validity and test-retest-reliability of the Apple Health app on iPhone for measuring gait parameters in different age groups. Twenty-seven children, 28 adults and 28 seniors equipped with an iPhone completed a 6-min walk test (6MWT). Gait speed (GS), step length (SL), and double support time (DST) were extracted from the gait recordings of the Health app. Gait parameters were simultaneously collected with an inertial sensors system (APDM Mobility Lab) to assess concurrent validity. Test-retest reliability was assessed via a second iPhone-instrumented 6MWT 1 week later. Agreement of the Health App with the APDM Mobility Lab was good for GS in all age groups and for SL in adults/seniors, but poor to moderate for DST in all age groups and for SL in children. Consistency between repeated measurements was good to excellent for all gait parameters in adults/seniors, and moderate to good for GS and DST but poor for SL in children. The Health app on iPhone is reliable and valid for measuring GS and SL in adults and seniors. Careful interpretation is required when using the Health app in children and when measuring DST in general, as both have shown limited validity and/or reliability.
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Affiliation(s)
- Christian Werner
- Geriatric Center, Agaplesion Bethanien Hospital Heidelberg, Heidelberg University Hospital, 69126, Heidelberg, Germany.
| | - Natalie Hezel
- Geriatric Center, Agaplesion Bethanien Hospital Heidelberg, Heidelberg University Hospital, 69126, Heidelberg, Germany
| | - Fabienne Dongus
- Institute of Sports and Sports Science, Heidelberg University, 69120, Heidelberg, Germany
| | | | - Jan Mayer
- TSG ResearchLab, 74939, Zuzenhausen, Germany
| | - Clemens Becker
- Unit of Digital Geriatric Medicine, Heidelberg University Hospital, 69115, Heidelberg, Germany
| | - Jürgen M Bauer
- Geriatric Center, Agaplesion Bethanien Hospital Heidelberg, Heidelberg University Hospital, 69126, Heidelberg, Germany
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Tripodi N, Dagiandis T, Hameed A, Heilberg L, Olbinski E, Reid C, White A, McLaughlin P. Inter-rater reliability between osteopaths of differing clinical experience on sagittal plane running gait analysis: A pilot study. INT J OSTEOPATH MED 2022. [DOI: 10.1016/j.ijosm.2022.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
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Rozanski G, Putrino D. Recording context matters: Differences in gait parameters collected by the OneStep smartphone application. Clin Biomech (Bristol, Avon) 2022; 99:105755. [PMID: 36058106 DOI: 10.1016/j.clinbiomech.2022.105755] [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: 02/01/2022] [Revised: 08/22/2022] [Accepted: 08/25/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Detailed understanding of impairments that underlie walking dysfunction through objective measures is essential to diagnosis, evaluation and care planning. Despite significant developments in motion tracking technologies, there is a dearth of research about the influence of remote monitoring context on performance. The objective of this study was to determine whether gait parameters collected by the OneStep smartphone application differ based on the recording condition. METHODS Retrospective repeated measures univariate analysis was performed on data extracted based on detected activity, either spontaneous (background recording) or consciously initiated (in app) walks, of 25 patients enrolled in a physical therapy program. FINDINGS Across 7227 walking bouts, significant differences between the two paradigms in velocity (g = 0.48), double support (g = 0.37), stride length (g = 0.37) and step length of the affected side (g = 0.32) were revealed. Overall, the passively recorded walks presented a less clinically favorable spatiotemporal pattern for each of these variables. INTERPRETATION The recording context of walks that were used for analysis appears to significantly affect the biomechanical output of the OneStep application. It is unclear whether the disparity found would impact functional recovery of individuals undergoing rehabilitation due to neurological or musculoskeletal disorder. Clinicians may consider this information when incorporating remotely-acquired quantitative gait analysis and interpreting care outcomes as part of therapeutic practice. Future work can further investigate the behavioral and environmental factors contributing to how movement occurs in specific clinical populations when monitored via mobile health systems.
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Affiliation(s)
- Gabriela Rozanski
- Abilities Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - David Putrino
- Abilities Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
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Body CoM Acceleration for Rapid Analysis of Gait Variability and Pedestrian Effects on Structures. BUILDINGS 2022. [DOI: 10.3390/buildings12020251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Knowledge of body motion features and walk-induced effects is of primary importance for the vibration analysis of structures, especially low-frequency slabs and lightweight and/or slender systems, as well as for clinical applications. Structurally speaking, consolidated literature procedures are available for a wide set of constructional solutions and typologies. A basic assumption consists in the description of walking humans’ effects on structures through equivalent deterministic loads, in which the ground vertical reaction force due to pedestrians depends on their mass and motion frequency. However, a multitude of additional parameters should be taken into account and properly confirmed by dedicated laboratory studies. In this paper, the focus is on the assessment of a rapid analysis protocol in which attention is given to pedestrian input, based on a minimized sensor setup. The study of gait variability and related effects for structural purposes is based on the elaboration of single Wi-Fi sensor, body centre of mass (CoM) accelerations. A total of 50 walking configurations was experimentally investigated in laboratory or in field conditions (for more than 500 recorded gaits), with the support of an adult volunteer. Parametric gait analysis is presented considering different substructure conditions and motion configurations. Body CoM acceleration records are then used for the analysis of a concrete slab, where the attention is focused on the effects of (i) rough experimental body CoM input, or (ii) experimentally derived synthetized gait input. The effects on the structural side of rough experimental walk time histories or synthetized experimental stride signals are discussed.
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