Abstract
Slip, trip and fall (STF) accidents are a major problem for companies in many industries and cause massive work absences. According to the German employers' liability insurance associations, this type of accident has been leading the list of reportable occupational accidents in the traffic, transport and logistics sector for years. A total of 172,045 STF accidents occurred during the reporting period of the German Social Accident Insurance (DGUV Report 2021) seven of which were fatal, and 2,694 new accident pensions. This paper focuses on the standardized acquisition of kinematic data of STF events and its use to assess dynamic stability control during locomotion for machine learning. Accurate detection of near falls via machine learning could help to identify subjects at high risk of falling and ensure that fall prevention interventions are provided to targeted individuals.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
DGUV. Statistik Arbeitsunfallgeschehen 2019 (2020). https://www.dguv.de/de/zahlen-fakten/index.jsp.
Hsiao, H.: Fall prevention research and practice: a total worker safety approach. Ind. Health 52, 381–392 (2014)
BAuA, Sturz, Ausrutschen, Stolpern, Umknicken (2021).https://www.baua.de/DE/Themen/Arbeitsgestaltung-im-Betrieb/Gefaehrdungsbeurteilung/Expertenwissen/Mechanische-Gefaehrdungen/Sturz-Ausrutschen-Stolpern-Umknicken/Sturz-Ausrutschen-Stolpern-Umknicken_node.html
BGHM. Vorsicht, Rutschgefahr! Stolpern, Ausrutschen, Stürzen - Die häufigsten Unfallursachen bei der Arbeit (2021). https://www.bghm.de/bghm/presseservice/text-portal-fuer-interne-kommunikation/vorsicht-rutschgefahr
Verkehr, B.: Stolpern, Rutschen, Stürzen (2021). https://www.bg-verkehr.de/arbeitssicherheit-gesundheit/branchen/gueterkraftverkehr/animationsfilme/stolpern-rutschen-stuerzen
DGUV. Statistik Arbeitsunfallgeschehen 2021 (2021). https://www.dguv.de/de/zahlen-fakten/index.jsp.
Mohr, J.O.: Fit gegen das Stolpern – Projektstudie der HFUK Nord. 6. DGUV-Fachgespräch Ergonomie, pp. 125–127 (2017)
Bentley, T.A.: Slip, trip and fall accidents occurring during the delivery of mail. Ergonomics 41, 1859–1872 (1998)
Wetzel, C.: Entwicklung einer Rutschhemmungsmatrix zur Auswahl von Bodenbelägen und Schuhen zur Reduzierung von Ausgleitunfällen. Bergische Universität Wuppertal (2013)
Lehto, M.R., Cook, B.T.: Occupational health and safety management. In: Handbook of Human Factors and Ergonomics, pp. 701–733 (2012)
E. O. F. D. 89/391/EEC. The introduction of measures to encourage improvements in the safety and health of workers at work. Official Journal of the European Union L 183, 29/06/1989, pp. 1–8 (2008)
Paridon, H.: Entstehung von Stolper-, Rutsch- und Sturzunfälle. BGAG-Report 1/05 (2005)
Chang, W.-R., Leclercq, S., Lockhart, T.E., Haslam, R.: State of science: occupational slips, trips and falls on the same level. In: Ergonomics, pp. 861–883 (2016)
Haslam, R.A., Bentley, T.A.: Follow-up investigations of slip, trip and fall accidents among postal delivery workers. In: Safety Science, pp. 33–47 (1999)
Bentley, T.A., Halsam, R.A.: Identification of risk factors and countermeasures for slip, trip and fall accidents during the delivery of mail. In: Applied Ergonomics, pp. 127–134 (2001)
DGUV. DGUV Information 208–035 - Zustellen von Sendungen (2020)
Aziz, O., Musngi, M., Park, E.J., Mori, G., Robinovitch, S.N.: A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials. Med. Biol. Eng. Compu. 55(1), 45–55 (2016). https://doi.org/10.1007/s11517-016-1504-y
Casilari, E., Lora-Rivera, R., GarcÃa-Lagos, F.: A study on the application of convolutional neural networks to fall detection evaluated with multiple public datasets. Sensors 20(5), 2020 (2020)
Bagalà , F., et al.: Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls. PLoS ONE 7(5) (2012)
I. Pang, Y. Okubo, D. Sturnieks, S. R. Lord und M. A. Brodie, „Detection of Near Falls Using Wearable Devices,“ Journal of Geriatric Physical Therapy, pp. 48–56, 2019
Lee, J.K., Robinovitch, S.N., Park, E.J.: Inertial sensing-based pre-impact de-tection of falls involving near-fall scenarios. IEEE Trans. Neural Syst. Rehabil. Eng. 23(2), 258–266 (2015)
Albert, M.V., Kording, K., Herrmann, M., Jayaraman, A.: Fall classification by machine learning using mobile phones. PloS One 7(5) (2012)
Kangas, M., Konttila, A., Lindgren, P., Winblad, I., Jämsä, T.: Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait Posture, 285–291 (2008)
Nyan, M.N., Tay, F.E.H., Murugasu, E.: A wearable system for pre-impact fall detection. J. Biomech., 3475–3481 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Schneider, M. et al. (2023). Generation of Consistent Slip, Trip and Fall Kinematic Data via Instability Detection and Recovery Performance Analysis for Use in Machine Learning Algorithms for (Near) Fall Detection. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. HCII 2023. Lecture Notes in Computer Science, vol 14029. Springer, Cham. https://doi.org/10.1007/978-3-031-35748-0_22
Download citation
DOI: https://doi.org/10.1007/978-3-031-35748-0_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-35747-3
Online ISBN: 978-3-031-35748-0
eBook Packages: Computer ScienceComputer Science (R0)