Wavelet based approach for posture transition estimation using a waist worn accelerometer

Niranjan Bidargaddi, Lasse Klingbeil, Antti Sarela, Justin Boyle, Vivian Cheung, Catherine Yelland, Mohanraj Karunanithi, Len Gray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Citations (Scopus)

Abstract

The ability to rise from a chair is considered to be important to achieve functional independence and quality of life. This sit-to-stand task is also a good indicator to assess condition of patients with chronic diseases. We developed a wavelet based algorithm for detecting and calculating the durations of sit-to-stand and stand-to-sit transitions from the signal vector magnitude of the measured acceleration signal. The algorithm was tested on waist worn accelerometer data collected from young subjects as well as geriatric patients. The test demonstrates that both transitions can be detected by using wavelet transformation applied to signal magnitude vector. Wavelet analysis produces an estimate of the transition pattern that can be used to calculate the transition duration that further gives clinically significant information on the patients condition. The method can be applied in a real life ambulatory monitoring system for assessing the condition of a patient living at home.

LanguageEnglish
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages1884-1887
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: 23 Aug 200726 Aug 2007

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
CountryFrance
CityLyon
Period23/08/0726/08/07

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Bidargaddi, N., Klingbeil, L., Sarela, A., Boyle, J., Cheung, V., Yelland, C., ... Gray, L. (2007). Wavelet based approach for posture transition estimation using a waist worn accelerometer. In 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 (pp. 1884-1887). [4352683] https://doi.org/10.1109/IEMBS.2007.4352683
Bidargaddi, Niranjan ; Klingbeil, Lasse ; Sarela, Antti ; Boyle, Justin ; Cheung, Vivian ; Yelland, Catherine ; Karunanithi, Mohanraj ; Gray, Len. / Wavelet based approach for posture transition estimation using a waist worn accelerometer. 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. pp. 1884-1887
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abstract = "The ability to rise from a chair is considered to be important to achieve functional independence and quality of life. This sit-to-stand task is also a good indicator to assess condition of patients with chronic diseases. We developed a wavelet based algorithm for detecting and calculating the durations of sit-to-stand and stand-to-sit transitions from the signal vector magnitude of the measured acceleration signal. The algorithm was tested on waist worn accelerometer data collected from young subjects as well as geriatric patients. The test demonstrates that both transitions can be detected by using wavelet transformation applied to signal magnitude vector. Wavelet analysis produces an estimate of the transition pattern that can be used to calculate the transition duration that further gives clinically significant information on the patients condition. The method can be applied in a real life ambulatory monitoring system for assessing the condition of a patient living at home.",
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Bidargaddi, N, Klingbeil, L, Sarela, A, Boyle, J, Cheung, V, Yelland, C, Karunanithi, M & Gray, L 2007, Wavelet based approach for posture transition estimation using a waist worn accelerometer. in 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07., 4352683, pp. 1884-1887, 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, France, 23/08/07. https://doi.org/10.1109/IEMBS.2007.4352683

Wavelet based approach for posture transition estimation using a waist worn accelerometer. / Bidargaddi, Niranjan; Klingbeil, Lasse; Sarela, Antti; Boyle, Justin; Cheung, Vivian; Yelland, Catherine; Karunanithi, Mohanraj; Gray, Len.

29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. p. 1884-1887 4352683.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Karunanithi, Mohanraj

AU - Gray, Len

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AB - The ability to rise from a chair is considered to be important to achieve functional independence and quality of life. This sit-to-stand task is also a good indicator to assess condition of patients with chronic diseases. We developed a wavelet based algorithm for detecting and calculating the durations of sit-to-stand and stand-to-sit transitions from the signal vector magnitude of the measured acceleration signal. The algorithm was tested on waist worn accelerometer data collected from young subjects as well as geriatric patients. The test demonstrates that both transitions can be detected by using wavelet transformation applied to signal magnitude vector. Wavelet analysis produces an estimate of the transition pattern that can be used to calculate the transition duration that further gives clinically significant information on the patients condition. The method can be applied in a real life ambulatory monitoring system for assessing the condition of a patient living at home.

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Bidargaddi N, Klingbeil L, Sarela A, Boyle J, Cheung V, Yelland C et al. Wavelet based approach for posture transition estimation using a waist worn accelerometer. In 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. p. 1884-1887. 4352683 https://doi.org/10.1109/IEMBS.2007.4352683