Objective Assessment of Fall Risk in Parkinson's Disease Using a Body-Fixed Sensor Worn for 3 Days
Open accessAbstract
BACKGROUND: Patients with Parkinson's disease (PD) suffer from a high fall risk. Previous approaches for evaluating fall risk are based on self-report or testing at a given time point and may, therefore, be insufficient to optimally capture fall risk. We tested, for the first time, whether metrics derived from 3 day continuous recordings are associated with fall risk in PD. METHODS AND MATERIALS: 107 patients (Hoehn & Yahr Stage: 2.6±0.7) wore a small, body-fixed sensor (3D accelerometer) on lower back for 3 days. Walking quantity (e.g., steps per 3-days) and quality (e.g., frequency-derived measures of gait variability) were determined. Subjects were classified as fallers or non-fallers based on fall history. Subjects were also followed for one year to evaluate predictors of the transition from non-faller to faller. RESULTS: The 3 day acceleration derived measures were significantly different in fallers and non-fallers and were significantly correlated with previously validated measures of fall risk. Walking quantity was similar in the two groups. In contrast, the fallers walked with higher step-to-step variability, e.g., anterior-posterior width of the dominant frequency was larger (p = 0.012) in the fallers (0.78 ± 0.17 Hz) compared to the non-fallers (0.71 ± 0.07 Hz). Among subjects who reported no falls in the year prior to testing, sensor-derived measures predicted the time to first fall (p = 0.0034), whereas many traditional measures did not. Cox regression analysis showed that anterior-posterior width was significantly (p = 0.0039) associated with time to fall during the follow-up period, even after adjusting for traditional measures. CONCLUSIONS/SIGNIFICANCE: These findings indicate that a body-fixed sensor worn continuously can evaluate fall risk in PD. This sensor-based approach was able to identify transition from non-faller to faller, whereas many traditional metrics were not successful. This approach may facilitate earlier detection of fall risk and may in the future, help reduce high costs associated with falls.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Quantification of missteps and risk of falling was shown to discriminate non-fallers and fallers.
“Quantification of missteps and risk of falling was shown to discriminate non-fallers and fallers [35, 36].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [35]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Development and validation of a geriatric depression screening scale: a preliminary report
Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M., & Leirer, V. O. (1982) · Journal of Psychiatric Research · doi:10.1016/0022-3956(82)90033-4 · Cited by 15,025 · see citing works
The Timed “Up & Go”: A Test of Basic Functional Mobility for Frail Elderly Persons
Podsiadlo, D., & Richardson, S. (1991) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1991.tb01616.x · Cited by 14,418 · cited 1× · see citing works
“In addition to fall history, a known predictor of future falls, other ‘‘traditional’’ measures of fall risk included performance-based measures of balance and mobility: the pull test [17], Dynamic Gait Index [21], the Berg Balance Test [22], and the Timed Up and Go [23].”
MethodMeasuring balance in the elderly: validation of an instrument.
Berg, K., Wood-Dauphinée, S., Williams, J. I., & Maki, B. E. (1992) · PubMed · Cited by 2,961 · see citing works
The Activities-specific Balance Confidence (ABC) Scale
Powell, L. E., & Myers, A. M. (1995) · The Journals of Gerontology Series A · doi:10.1093/gerona/50a.1.m28 · Cited by 2,877 · see citing works
Lamb, S. E., Jørstad‐Stein, E. C., Hauer, K. A., Becker, C., & on behalf of the Prevention of Falls Network Europe and Outcomes Consensus Group (2005) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2005.53455.x · Cited by 2,078 · see citing works
Motor Control: Theory and Practical Applications
Shumway‐Cook, A., & Woollacott, M. H. (1995) · Cited by 1,494 · see citing works
Goetz, C. G., Fahn, S., Martínez‐Martín, P., Poewe, W. H., Sampaio, C., Stebbins, G. T., Stern, M. B., Tilley, B. C., Dodel, R. C., Dubois, B., et al. (2006) · Movement Disorders · doi:10.1002/mds.21198 · Cited by 1,404 · see citing works
Bloem, B. R., Hausdorff, J. M., Visser, J. E., & Giladi, N. (2004) · Movement Disorders · doi:10.1002/mds.20115 · Cited by 1,298 · see citing works
Self-citationWolf, S. L., Barnhart, H. X., Kutner, N. G., McNeely, E., Coogler, C., Xu, T., & Atlanta FICSIT Group (1996) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1996.tb01432.x · Cited by 1,142 · see citing works
Hausdorff, J. M., Cudkowicz, M., Firtion, R., Wei, J. Y., & Goldberger, A. L. (1998) · Movement Disorders · doi:10.1002/mds.870130310 · Cited by 897 · see citing works
Self-citationAssessment of spatio-temporal gait parameters from trunk accelerations during human walking
Zijlstra, W., & Hof, A. L. (2003) · Gait & Posture · doi:10.1016/s0966-6362(02)00190-x · Cited by 873 · see citing works
Prospective assessment of falls in Parkinson's disease
Bloem, B. R., Grimbergen, Y. A. M., Cramer, M., Willemsen, M., & Zwinderman, A. H. (2001) · Journal of Neurology · doi:10.1007/s004150170047 · Cited by 869 · see citing works
Normative spatiotemporal gait parameters in older adults
Hollman, J. H., McDade, E., & Petersen, R. C. (2011) · Gait & Posture · doi:10.1016/j.gaitpost.2011.03.024 · Cited by 814 · see citing works
Quantitative gait dysfunction and risk of cognitive decline and dementia
Verghese, J., Wang, C., Lipton, R. B., Holtzer, R., & Xue, X. (2007) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.2006.106914 · Cited by 797 · see citing works
Estimation of gait cycle characteristics by trunk accelerometry
Moe‐Nilssen, R., & Helbostad, J. L. (2003) · Journal of Biomechanics · doi:10.1016/s0021-9290(03)00233-1 · Cited by 641 · see citing works
Nieuwboer, A., Rochester, L., Herman, T., Vandenberghe, W., Emil, G. E., Thomaes, T., & Giladi, N. (2009) · Gait & Posture · doi:10.1016/j.gaitpost.2009.07.108 · Cited by 637 · see citing works
Self-citationHausdorff, J. M. (2009) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.3147408 · Cited by 633 · see citing works
Self-citationThe Effect of Age on Variability in Gait
Gabell, A., & Nayak, U. S. (1984) · Journal of Gerontology · doi:10.1093/geronj/39.6.662 · Cited by 574 · see citing works
Mapping mHealth research: a decade of evolution
Fiordelli, M., Diviani, N., & Schulz, P. J. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2430 · Cited by 570 · see citing works
Predictors of future falls in Parkinson disease
Kerr, G., Worringham, C. J., Cole, M. H., Lacherez, P. F., Wood, J. M., & Silburn, P. A. (2010) · Neurology · doi:10.1212/wnl.0b013e3181e7b688 · Cited by 550 · see citing works
Recurrent Falls in Parkinson’s Disease: A Systematic Review
Allen, N. E., Schwarzel, A. K., & Canning, C. G. (2013) · Parkinson s Disease · doi:10.1155/2013/906274 · Cited by 540 · see citing works
Brach, J. S., Berlin, J. E., VanSwearingen, J. M., Newman, A. B., & Studenski, S. A. (2005) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-2-21 · Cited by 485 · see citing works
Schaafsma, J. D., Giladi, N., Balash, Y., Bartels, A. L., Gurevich, T., & Hausdorff, J. M. (2003) · Journal of the Neurological Sciences · doi:10.1016/s0022-510x(03)00104-7 · Cited by 480 · see citing works
Self-citationGait Dysfunction in Mild Cognitive Impairment Syndromes
Verghese, J., Robbins, M. S., Holtzer, R., Zimmerman, M. E., Wang, C., Xue, X., & Lipton, R. B. (2008) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2008.01758.x · Cited by 435 · see citing works
Lord, S. E., Galna, B., Verghese, J., Coleman, S. Y., Burn, D. J., & Rochester, L. (2012) · The Journals of Gerontology Series A · doi:10.1093/gerona/gls255 · Cited by 414 · see citing works
History of falls in Parkinson disease is associated with reduced cholinergic activity
Bohnen, N. I., Müller, M. L. T. M., Koeppe, R. A., Studenski, S. A., Kilbourn, M., Frey, K. A., & Albin, R. L. (2009) · Neurology · doi:10.1212/wnl.0b013e3181c1ded6 · Cited by 409 · see citing works
Plotnik, M., Giladi, N., & Hausdorff, J. M. (2007) · Experimental Brain Research · doi:10.1007/s00221-007-0955-7 · Cited by 364 · see citing works
Self-citationAshburn, A. (2001) · Age and Ageing · doi:10.1093/ageing/30.1.47 · Cited by 330 · see citing works
Moving forward on gait measurement: Toward a more refined approach
Lord, S., Galna, B., & Rochester, L. (2013) · Movement Disorders · doi:10.1002/mds.25545 · Cited by 314 · see citing works
Weiss, A., Brozgol, M., Dorfman, M., Herman, T., Shema, S., Giladi, N., & Hausdorff, J. M. (2013) · Neurorehabilitation and neural repair · doi:10.1177/1545968313491004 · Cited by 301 · see citing works
Self-citationDobkin, B. H., & Dorsch, A. K. (2011) · Neurorehabilitation and neural repair · doi:10.1177/1545968311425908 · Cited by 295 · see citing works
Effects of Cognitive Challenge on Gait Variability in Patients with Parkinson's Disease
Hausdorff, J. M., Balash, J., & Giladi, N. (2003) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/0891988702250580 · Cited by 289 · see citing works
Self-citationGait disorders and balance disturbances in Parkinsonʼs disease: clinical update and pathophysiology
Boonstra, T. A., van der Kooij, H., Munneke, M., & Bloem, B. R. (2008) · Current Opinion in Neurology · doi:10.1097/wco.0b013e328305bdaf · Cited by 272 · see citing works
Moe‐Nilssen, R., & Helbostad, J. L. (2004) · Gait & Posture · doi:10.1016/j.gaitpost.2004.01.013 · Cited by 247 · see citing works
The interplay of cholinergic function, attention, and falls in Parkinson's disease
Yarnall, A. J., Rochester, L., & Burn, D. J. (2011) · Movement Disorders · doi:10.1002/mds.23932 · Cited by 241 · see citing works
Stance time and step width variability have unique contributing impairments in older persons
Brach, J. S., Studenski, S. A., Perera, S., VanSwearingen, J. M., & Newman, A. B. (2007) · Gait & Posture · doi:10.1016/j.gaitpost.2007.05.016 · Cited by 213 · see citing works
Weiss, A., Sharifi, S., Plotnik, M., van Vugt, J. P. P., Giladi, N., & Hausdorff, J. M. (2011) · Neurorehabilitation and neural repair · doi:10.1177/1545968311424869 · Cited by 198 · see citing works
Self-citationAmbulatory activity in incident Parkinson’s: more than meets the eye?
Lord, S., Godfrey, A., Galna, B., Mhiripiri, D., Burn, D. J., & Rochester, L. (2013) · Journal of Neurology · doi:10.1007/s00415-013-7037-5 · Cited by 187 · see citing works
Gait Variability in Community-Dwelling Older Adults
Brach, J. S., Berthold, R. V., Craik, R. L., VanSwearingen, J. M., & Newman, A. B. (2001) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2001.49274.x · Cited by 178 · see citing works
Dynamic Stability in the Elderly: Identifying a Possible Measure
Yack, H. J., & Berger, R. C. (1993) · Journal of Gerontology · doi:10.1093/geronj/48.5.m225 · Cited by 174 · see citing works
Latt, M. D., Menz, H. B., Fung, V. S. C., & Lord, S. R. (2009) · The Journals of Gerontology Series A · doi:10.1093/gerona/glp009 · Cited by 156 · see citing works
Gait alterations in healthy carriers of the LRRK2 G2019S mutation
Mirelman, A., Gurevich, T., Giladi, N., Bar‐Shira, A., Orr‐Urtreger, A., & Hausdorff, J. M. (2011) · Annals of Neurology · doi:10.1002/ana.22165 · Cited by 149 · see citing works
Self-citationPredicting Fallers in a Community-Based Sample of People with Parkinson’s Disease
Ashburn, A., Stack, E. L., Pickering, R. M., & Ward, C. D. (2001) · Gerontology · doi:10.1159/000052812 · Cited by 145 · see citing works
Wearable motion sensors to continuously measure real-world physical activities
Dobkin, B. H. (2013) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000026 · Cited by 141 · see citing works
Gait variability measures may represent different constructs
Moe‐Nilssen, R., Aaslund, M. K., Hodt-Billington, C., et al. (2010) · Gait & Posture · doi:10.1016/j.gaitpost.2010.03.019 · Cited by 97 · see citing works
Reevaluating the Implications of Recurrent Falls in Older Adults: Location Changes the Inference
Kelsey, J. L., Procter-Gray, E., Berry, S. D., Hannan, M. T., Kiel, D. P., Lipsitz, L. A., & Li, W. (2012) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2011.03834.x · Cited by 91 · see citing works
The pattern of habitual sedentary behavior is different in advanced Parkinson's disease
CHASTIN, S. F. M., Baker, K., Jones, D. E., Burn, D. J., Granat, M. H., & Rochester, L. (2010) · Movement Disorders · doi:10.1002/mds.23146 · Cited by 85 · see citing works
van Hees, V. T., van Lummel, R. C., & Westerterp, K. R. (2009) · Obesity · doi:10.1038/oby.2009.55 · Cited by 85 · see citing works
Stevens, J. A., Powell, K. E., Smith, S. M., Wingo, P. A., & Sattin, R. W. (1997) · Annals of Epidemiology · doi:10.1016/s1047-2797(96)00110-x · Cited by 83 · see citing works
Fall risk and gait in Parkinson's disease: The role of the LRRK2 G2019S mutation
Mirelman, A., Heman, T., Yasinovsky, K., Thaler, A., Gurevich, T., Marder, K. S., Bressman, S., Bar‐Shira, A., Orr‐Urtreger, A., Giladi, N., et al. (2013) · Movement Disorders · doi:10.1002/mds.25587 · Cited by 80 · see citing works
Self-citationRochester, L., CHASTIN, S. F. M., Lord, S., Baker, K., & Burn, D. J. (2011) · Journal of Neurology · doi:10.1007/s00415-011-6301-9 · Cited by 71 · see citing works
Concurrent validity of accelerometry to measure gait in Parkinsons Disease
Lord, S., Rochester, L., Baker, K., & Nieuwboer, A. (2008) · Gait & Posture · doi:10.1016/j.gaitpost.2007.04.001 · Cited by 69 · see citing works
Herman, T., Rosenberg‐Katz, K., Jacob, Y., Auriel, E., Gurevich, T., Giladi, N., & Hausdorff, J. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055193 · Cited by 69 · see citing works
Self-citationMoore, S. T., Dilda, V., Hakim, B., & MacDougall, H. G. (2011) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-10-82 · Cited by 43 · see citing works
Unraveling dynamics of human physical activity patterns in chronic pain conditions
Paraschiv-Ionescu, A., Buchser, E., & Aminian, K. (2013) · Scientific Reports · doi:10.1038/srep02019 · Cited by 36 · see citing works
Identifying fallers with Parkinson's disease using home‐based tests: Who is at risk?
Lim, I., van Wegen, E. E. H., Jones, D. E., Rochester, L., Nieuwboer, A., Willems, A., Baker, K., Hetherington, V., & Kwakkel, G. (2008) · Movement Disorders · doi:10.1002/mds.22209 · Cited by 27 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Technology in Parkinson’s disease: challenges and opportunities
Espay, A. J., Bonato, P., Nahab, F. B., Maetzler, W., Dean, J. M., Klucken, J., Eskofier, B. M., Merola, A., Horak, F., Lang, A. E., et al. (2016) · Movement Disorders · doi:10.1002/mds.26642 · Cited by 654 · see citing works
Self-citationPasluosta, C. F., Gassner, H., Winkler, J., Klucken, J., & Eskofier, B. M. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2461555 · Cited by 323 · see citing works
Godinho, C., Domingos, J., Cunha, G., Santos, A. T., Fernandes, R. M., Abreu, D., Gonçalves, N., Matthews, H., Isaacs, T., Duffen, J., et al. (2016) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-016-0136-7 · Cited by 226 · see citing works
Rodríguez-Martín, D., Samà, A., Pérez-López, C., Català, A., Moreno Arostegui, J. M., Cabestany, J., Bayés, À., Alcaine, S., Mestre, B., Prats, A., et al. (2017) · PLOS ONE · doi:10.1371/journal.pone.0171764 · Cited by 237 · see citing works
Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review.
Block, V. A. J., Pitsch, E., Tahir, P., Cree, B. A. C., Allen, D. D., & Gelfand, J. M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0154335 · Cited by 198 · see citing works
“Abnormal gait patterns, such as lower amplitude and greater step-to-step variability, were associated with fall risk in people with PD whereas total walking amount was not.[144] People with PD tend to take fewer steps and do shorter bouts of physical activity than the general population.”
BackgroundJohansson, D., Malmgren, K., & Alt Murphy, M. (2018) · Journal of Neurology · doi:10.1007/s00415-018-8786-y · Cited by 188 · see citing works
Continuous monitoring of turning in Parkinson’s disease: Rehabilitation potential
Mancini, M., El-Gohary, M., Pearson, S., McNames, J., Schlueter, H., Nutt, J. G., King, L. A., & Horak, F. B. (2015) · NeuroRehabilitation · doi:10.3233/nre-151236 · Cited by 175 · see citing works
A clinical view on the development of technology‐based tools in managing Parkinson's disease
Maetzler, W., Klucken, J., & Horne, M. (2016) · Movement Disorders · doi:10.1002/mds.26673 · Cited by 162 · see citing works
Hsu, W.-C., Sugiarto, T., Lin, Y.-J., Yang, F.-C., Lin, Z.-Y., Sun, C.-T., Hsu, C.-L., & Chou, K.-N. (2018) · Sensors · doi:10.3390/s18103397 · Cited by 101 · see citing works
- Authors
- Weiss, A., Herman, T., Giladi, N., & Hausdorff, J. M.
- Affiliations
- Tel Aviv Sourasky Medical Center (IL)
- Tel Aviv University (IL)
- Harvard University (US)
- Corresponding author
- Hausdorff, Jeffrey M.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-05-06
- Volume
- 9
- Issue
- 5
- Pages
- e96675
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4011791
- OpenAlex
- W2057105744
- Cited by
- 225
- References
- 57
- Citations by year
- 2026: 12 · 2025: 12 · 2024: 15 · 2023: 16 · 2022: 16 · 2021: 24 · 2020: 20 · 2019: 22 · 2018: 29 · 2017: 17 · 2016: 20 · 2015: 19 · 2014: 3
- FWCI
- 50.38
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- European Commission (288878)
- Israel Science Foundation
- National Institutes of Health
- National Institute on Aging (R21AG034227)
- Topics
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- Parkinson's disease, fall risk assessment, gait variability, step-to-step variability, fall risk prediction, wearable sensors
- MeSH terms
- Accidental Falls, Adult, Aged, Demography, Female, Gait, Humans, Male, Middle Aged, Monitoring, Physiologic, Parkinson Disease, Severity of Illness Index, Time Factors, Walking, Risk Assessment, Kaplan-Meier Estimate, Self Report, Accelerometry
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
