Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review

Salari N, Darvishi N, Ahmadipanah M, et al. Global prevalence of falls in the older adults: a comprehensive systematic review and meta-analysis. J Orthop Surg Res. 2022;17(1):334. https://doi.org/10.1186/s13018-022-03222-1.

Article  PubMed  PubMed Central  Google Scholar 

Tsai Y-J, Yang P-Y, Yang Y-C, et al. Prevalence and risk factors of falls among community-dwelling older people: results from three consecutive waves of the national health interview survey in Taiwan. BMC Geriatr. 2020;20(1):529. https://doi.org/10.1186/s12877-020-01922-z.

Article  PubMed  PubMed Central  Google Scholar 

Vaishya R, Vaish A. Falls in older adults are serious. Indian J Orthop. 2020;54(1):69–74. https://doi.org/10.1007/s43465-019-00037-x.

Article  PubMed  PubMed Central  Google Scholar 

Soomar SM, Dhalla Z. Injuries and outcomes resulting due to falls in elderly patients presenting to the Emergency Department of a tertiary care hospital – a cohort study. BMC Emerg Med. 2023;23(1):14. https://doi.org/10.1186/s12873-023-00784-z.

Article  PubMed  PubMed Central  Google Scholar 

Montero-Odasso M, van der Velde N, Martin FC, et al. World guidelines for falls prevention and management for older adults: a global initiative. Age Ageing. 2022; 51(9):afac205. https://doi.org/10.1093/ageing/afac205.

Muir SW, Gopaul K, Montero Odasso MM. The role of cognitive impairment in fall risk among older adults: a systematic review and meta-analysis. Age and Ageing. 2012;41(3):299–308. https://doi.org/10.1093/ageing/afs012.

Article  PubMed  Google Scholar 

Kirova AM, Bays RB, Lagalwar S. Working memory and executive function decline across normal aging, mild cognitive impairment, and Alzheimer’s disease. Biomed Res Int. 2015;2015:748212. https://doi.org/10.1155/2015/748212.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang W, Low LF, Schwenk M, et al. Review of gait, cognition, and fall risks with implications for fall prevention in older adults with dementia. Dement Geriatr Cogn Disord. 2019;48(1–2):17–29. https://doi.org/10.1159/000504340.

Article  PubMed  Google Scholar 

Radavelli-Bagatini S, Macpherson H, Scott D, et al. Impaired muscle function, including its decline, is related to greater long-term late-life dementia risk in older women. J Cachexia Sarcopenia Muscle. 2023;14(3):1508–19. https://doi.org/10.1002/jcsm.13227.

Kim M, Won CW. Sarcopenia is associated with cognitive impairment mainly due to slow gait speed: results from the Korean frailty and aging cohort study (KFACS). Int J Environ Res Public Health. 2019;16(9):1491. https://doi.org/10.3390/ijerph16091491.

Article  PubMed  PubMed Central  Google Scholar 

Billot M, Calvani R, Urtamo A, et al. Preserving mobility in older adults with physical frailty and sarcopenia: opportunities, challenges, and recommendations for physical activity interventions. Clin Interv Aging. 2020;15:1675–90. https://doi.org/10.2147/cia.S253535.

Article  PubMed  PubMed Central  Google Scholar 

Ng TKS, Han MFY, Loh PY, et al. Differential associations between simple physical performance tests with global and specific cognitive functions in cognitively normal and mild cognitive impairment: a cross-sectional cohort study of Asian community-dwelling older adults. BMC Geriatr. 2022;22(1):798. https://doi.org/10.1186/s12877-022-03434-4.

Article  PubMed  PubMed Central  Google Scholar 

Chantanachai T, Taylor ME, Lord SR, et al. Risk factors for falls in community-dwelling older people with mild cognitive impairment: a prospective one-year study. PeerJ. 2022;10:e13484. https://doi.org/10.7717/peerj.13484.

Article  PubMed  PubMed Central  Google Scholar 

Winter H, Watt K, Peel NM. Falls prevention interventions for community-dwelling older persons with cognitive impairment: a systematic review. Int Psychogeriatr. 2013;25(2):215–27. https://doi.org/10.1017/S1041610212001573.

Article  PubMed  Google Scholar 

Casas-Herrero A, Anton-Rodrigo I, Zambom-Ferraresi F, et al. Effect of a multicomponent exercise programme (VIVIFRAIL) on functional capacity in frail community elders with cognitive decline: study protocol for a randomized multicentre control trial. Trials. 2019;20(1):362. https://doi.org/10.1186/s13063-019-3426-0.

Article  PubMed  PubMed Central  Google Scholar 

Eckstrom E, Parker EM, Lambert GH, et al. Implementing STEADI in Academic Primary Care to Address Older Adult Fall Risk. Innov Aging. 2017;1(2):igx028. https://doi.org/10.1093/geroni/igx028.

Article  PubMed  PubMed Central  Google Scholar 

Phelan EA, Mahoney JE, Voit JC, et al. Assessment and management of fall risk in primary care settings. Med Clin North Am. 2015;99(2):281–93. https://doi.org/10.1016/j.mcna.2014.11.004.

Article  PubMed  PubMed Central  Google Scholar 

Welch SA, Ward RE, Beauchamp MK, et al. The short physical performance battery (SPPB): a quick and useful tool for fall risk stratification among older primary care patients. J Am Med Dir Assoc. 2021;22(8):1646–51. https://doi.org/10.1016/j.jamda.2020.09.038.

Article  PubMed  Google Scholar 

Shimada H, Suzukawa M, Ishizaki T, et al. Relationship between subjective fall risk assessment and falls and fall-related fractures in frail elderly people. BMC Geriatr. 2011;11(1):40. https://doi.org/10.1186/1471-2318-11-40.

Article  PubMed  PubMed Central  Google Scholar 

Rajagopalan R, Litvan I, Jung TP. Fall prediction and prevention systems: recent trends, challenges, and future research directions. Sensors (Basel). 2017;17(11):2509. https://doi.org/10.3390/s17112509.

Article  PubMed  Google Scholar 

Sun R, Sosnoff JJ. Novel sensing technology in fall risk assessment in older adults: a systematic review. BMC Geriatr. 2018;18(1):14. https://doi.org/10.1186/s12877-018-0706-6.

Article  PubMed  PubMed Central  Google Scholar 

Marschollek M, Rehwald A, Wolf K-H, et al. Sensors vs. experts - a performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients. BMC Med Inform Decision Making. 2011;11(1):48. https://doi.org/10.1186/1472-6947-11-48.

Article  Google Scholar 

Ejupi A, Lord SR, Delbaere K. New methods for fall risk prediction. Curr Opin Clin Nutr Metab Care. 2014;17(5):407–11. https://doi.org/10.1097/mco.0000000000000081.

Article  PubMed  Google Scholar 

Chen M, Wang H, Yu L, et al. A systematic review of wearable sensor-based technologies for fall risk assessment in older adults. Sensors (Basel). 2022;22(18):6752. https://doi.org/10.3390/s22186752.

Article  PubMed  Google Scholar 

Bezold J, Krell-Roesch J, Eckert T, et al. Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review. Eur Rev Aging Phys Act. 2021;18(1):15. https://doi.org/10.1186/s11556-021-00266-w.

Article  PubMed  PubMed Central  Google Scholar 

Ouzzani M, Hammady H, Fedorowicz Z, et al. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210. https://doi.org/10.1186/s13643-016-0384-4.

Article  PubMed  PubMed Central  Google Scholar 

Zou KH, O’Malley AJ, Mauri L. Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models. Circulation. 2007;115(5):654–7. https://doi.org/10.1161/CIRCULATIONAHA.105.594929.

Article  PubMed  Google Scholar 

Li F, He H. Assessing the accuracy of diagnostic tests. Shanghai Arch Psychiatry. 2018;30(3):207–12. https://doi.org/10.11919/j.issn.1002-0829.218052.

Article  PubMed  PubMed Central  Google Scholar 

Nahm FS. Receiver operating characteristic curve: overview and practical use for clinicians. Korean J Anesthesiol. 2022;75(1):25–36. https://doi.org/10.4097/kja.21209.

Article  PubMed  PubMed Central  Google Scholar 

Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2013. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.

Herzog R, Álvarez-Pasquin MJ, Díaz C, et al. Are healthcare workers’ intentions to vaccinate related to their knowledge, beliefs and attitudes? a systematic review. BMC Public Health. 2013;13(1):154. https://doi.org/10.1186/1471-2458-13-154.

Article  PubMed  PubMed Central  Google Scholar 

Srulijes K, Klenk J, Schwenk M, et al. Fall risk in relation to individual physical activity exposure in patients with different neurodegenerative diseases: a pilot study. Cerebellum. 2019;18(3):340–8. https://doi.org/10.1007/s12311-018-1002-x.

Article  PubMed  Google Scholar 

Schniepp R, Huppert A, Decker J, et al. Multimodal mobility assessment predicts fall frequency and severity in cerebellar ataxia. Cerebellum. 2023;22(1):85–95. https://doi.org/10.1007/s12311-021-01365-1.

Article  PubMed  Google Scholar 

Adeli V, Korhani N, Sabo A, et al. Ambient monitoring of gait and machine learning models for dynamic and short-term falls risk assessment in people with dementia. IEEE J Biomed Health Inform. 2023;27(7):3599–609. https://doi.org/10.1109/JBHI.2023.3267039.

Article  PubMed  Google Scholar 

Najafi B, Aminian K, Loew F, et al. Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly. IEEE Trans Biomed Eng. 2002;49(8):843–51. https://doi.org/10.1109/tbme.2002.800763.

Article  PubMed  Google Scholar 

Schniepp R, Huppert A, Decker J, et al. Fall prediction in neurological gait disorders: differential contributions from clinical assessment, gait analysis, and daily-life mobility monitoring. J Neurol. 2021;268(9):3421–34. https://doi.org/10.1007/s00415-021-10504-x.

Article  PubMed  PubMed Central  Google Scholar 

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