Accelerometer based human activities and posture recognition

Arun Babu, Kudakwashe Dube, Subhas Mukhopadhyay, Hemant Ghayvat, M. V. Jithin Kumar

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

The quantity of elderly people like to live in their homes, secluded, in their brilliant age is expanding exponentially. This is not a perfect path for an elderly individual to live. However, the urbanization and resultant change of the social and social conduct makes it a more regular event. Falls are a noteworthy reason for death and horribleness in more established grown-ups. In this way, it has turn into an opportune need to create mechanized look after the elderly. The first end, purpose of such fall computer looking-glass is to ready caregivers of the fall event, which can then start an earlier process. In the present study, we amplify the use of wearable inertial sensors for fall identification and information of human posture and activities, by creating and assessing the precision of a sensor framework for identifying the same. We found that our system could discover fall events and monitor human activities with at least 95% accuracy.

LanguageEnglish
Title of host publicationSAPIENCE 2016
Subtitle of host publicationProceedings of 2016 International Conference on Data Mining and Advanced Computing
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages367-373
Number of pages7
ISBN (Electronic)9781467385947
DOIs
Publication statusPublished - 25 Oct 2016
Externally publishedYes
Event2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016 - Ernakulam, India
Duration: 16 Mar 201618 Mar 2016

Other

Other2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016
CountryIndia
CityErnakulam
Period16/03/1618/03/16

Fingerprint

Accelerometers
Sensors
Glass

Keywords

  • fall detection
  • wearable sensors
  • accelerometer
  • posture recognition
  • human activities

Cite this

Babu, A., Dube, K., Mukhopadhyay, S., Ghayvat, H., & Jithin Kumar, M. V. (2016). Accelerometer based human activities and posture recognition. In SAPIENCE 2016: Proceedings of 2016 International Conference on Data Mining and Advanced Computing (pp. 367-373). [7684120] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SAPIENCE.2016.7684120
Babu, Arun ; Dube, Kudakwashe ; Mukhopadhyay, Subhas ; Ghayvat, Hemant ; Jithin Kumar, M. V. / Accelerometer based human activities and posture recognition. SAPIENCE 2016: Proceedings of 2016 International Conference on Data Mining and Advanced Computing. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2016. pp. 367-373
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Babu, A, Dube, K, Mukhopadhyay, S, Ghayvat, H & Jithin Kumar, MV 2016, Accelerometer based human activities and posture recognition. in SAPIENCE 2016: Proceedings of 2016 International Conference on Data Mining and Advanced Computing., 7684120, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 367-373, 2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016, Ernakulam, India, 16/03/16. https://doi.org/10.1109/SAPIENCE.2016.7684120

Accelerometer based human activities and posture recognition. / Babu, Arun; Dube, Kudakwashe; Mukhopadhyay, Subhas; Ghayvat, Hemant; Jithin Kumar, M. V.

SAPIENCE 2016: Proceedings of 2016 International Conference on Data Mining and Advanced Computing. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 367-373 7684120.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

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Babu A, Dube K, Mukhopadhyay S, Ghayvat H, Jithin Kumar MV. Accelerometer based human activities and posture recognition. In SAPIENCE 2016: Proceedings of 2016 International Conference on Data Mining and Advanced Computing. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 367-373. 7684120 https://doi.org/10.1109/SAPIENCE.2016.7684120