Skip to main content

2020 | OriginalPaper | Buchkapitel

Assistive Smart Cane (ASCane) for Fall Detection: First Advances

verfasst von : Pedro Mouta, Nuno Ferrete Ribeiro, Cristina P. Santos, Rui Moreira

Erschienen in: XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The development of fall detection systems with the capability of real-time monitoring is necessary considering that a large amount of people die and suffer severe consequences from falls. Due to their advantages, daily life accessories can be a solution to embed fall-related systems, and canes are no exception. In this paper, it is presented a cane with fall detection abilities. The ASCane is instrumented with an inertial sensor which data will be tested with three different fixed multi-threshold fall detection algorithms, one dynamic multi-threshold and machine learning methods from the literature. They were tested and modified to account the use of a cane. The best performance resulted in a sensitivity and specificity of 96.90% and 98.98%, respectively.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
3.
Zurück zum Zitat Lachtar, A., Val, T., Kachouri, A., Lachtar, A., Val, T., Kachouri, A.: 3DCane: a monitoring system for the elderly using a connected walking stick. Int. J. Comput. Sci. Inf. Secur. 14(8), 1–8 (2017) Lachtar, A., Val, T., Kachouri, A., Lachtar, A., Val, T., Kachouri, A.: 3DCane: a monitoring system for the elderly using a connected walking stick. Int. J. Comput. Sci. Inf. Secur. 14(8), 1–8 (2017)
4.
Zurück zum Zitat Cates, B., Sim, T., Heo, H.M., Kim, B., Kim, H., Mun, J.H.: A novel detection model and its optimal features to classify falls from low- and high-acceleration activities of daily life using an insole sensor system. Sensors (Switzerland) 18(4) (2018). https://doi.org/10.3390/s18041227CrossRef Cates, B., Sim, T., Heo, H.M., Kim, B., Kim, H., Mun, J.H.: A novel detection model and its optimal features to classify falls from low- and high-acceleration activities of daily life using an insole sensor system. Sensors (Switzerland) 18(4) (2018). https://​doi.​org/​10.​3390/​s18041227CrossRef
12.
Zurück zum Zitat Ashfak Habib, M., Mohktar, M.S., Bahyah Kamaruzzaman, S., Seang Lim, K., Maw Pin, T., Ibrahim, F.: Smartphone-based solutions for fall detection and prevention: challenges and open issues. Sensors (Switzerland) 14(4), 7181–7208 (2014). https://doi.org/10.3390/s140407181CrossRef Ashfak Habib, M., Mohktar, M.S., Bahyah Kamaruzzaman, S., Seang Lim, K., Maw Pin, T., Ibrahim, F.: Smartphone-based solutions for fall detection and prevention: challenges and open issues. Sensors (Switzerland) 14(4), 7181–7208 (2014). https://​doi.​org/​10.​3390/​s140407181CrossRef
15.
18.
Zurück zum Zitat Shibuya, N., Nukala, B.T., Rodriguez, A.I., Tsay, J., Nguyen, T.Q., Zupancic, S., Lie, D.Y.: A real-time fall detection system using a wearable gait analysis sensor and a Support Vector Machine (SVM) classifier. In: 2015 8th International Conference on Mobile Computing and Ubiquitous Networking, ICMU 2015, pp. 66–67 (2015). https://doi.org/10.1109/ICMU.2015.7061032 Shibuya, N., Nukala, B.T., Rodriguez, A.I., Tsay, J., Nguyen, T.Q., Zupancic, S., Lie, D.Y.: A real-time fall detection system using a wearable gait analysis sensor and a Support Vector Machine (SVM) classifier. In: 2015 8th International Conference on Mobile Computing and Ubiquitous Networking, ICMU 2015, pp. 66–67 (2015). https://​doi.​org/​10.​1109/​ICMU.​2015.​7061032
Metadaten
Titel
Assistive Smart Cane (ASCane) for Fall Detection: First Advances
verfasst von
Pedro Mouta
Nuno Ferrete Ribeiro
Cristina P. Santos
Rui Moreira
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-31635-8_204