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Movement prediction using accelerometers in a human population

Author

Listed:
  • Luo Xiao
  • Bing He
  • Annemarie Koster
  • Paolo Caserotti
  • Brittney Lange-Maia
  • Nancy W. Glynn
  • Tamara B. Harris
  • Ciprian M. Crainiceanu

Abstract

type="main" xml:lang="en"> We introduce statistical methods for predicting the types of human activity at sub-second resolution using triaxial accelerometry data. The major innovation is that we use labeled activity data from some subjects to predict the activity labels of other subjects. To achieve this, we normalize the data across subjects by matching the standing up and lying down portions of triaxial accelerometry data. This is necessary to account for differences between the variability in the position of the device relative to gravity, which are induced by body shape and size as well as by the ambiguous definition of device placement. We also normalize the data at the device level to ensure that the magnitude of the signal at rest is similar across devices. After normalization we use overlapping movelets (segments of triaxial accelerometry time series) extracted from some of the subjects to predict the movement type of the other subjects. The problem was motivated by and is applied to a laboratory study of 20 older participants who performed different activities while wearing accelerometers at the hip. Prediction results based on other people's labeled dictionaries of activity performed almost as well as those obtained using their own labeled dictionaries. These findings indicate that prediction of activity types for data collected during natural activities of daily living may actually be possible.

Suggested Citation

  • Luo Xiao & Bing He & Annemarie Koster & Paolo Caserotti & Brittney Lange-Maia & Nancy W. Glynn & Tamara B. Harris & Ciprian M. Crainiceanu, 2016. "Movement prediction using accelerometers in a human population," Biometrics, The International Biometric Society, vol. 72(2), pages 513-524, June.
  • Handle: RePEc:bla:biomet:v:72:y:2016:i:2:p:513-524
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    Cited by:

    1. William F. Fadel & Jacek K. Urbanek & Steven R. Albertson & Xiaochun Li & Andrea K. Chomistek & Jaroslaw Harezlak, 2019. "Differentiating Between Walking and Stair Climbing Using Raw Accelerometry Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(2), pages 334-354, July.
    2. Marta Karas & Jiawei Bai & Marcin StrÄ…czkiewicz & Jaroslaw Harezlak & Nancy W. Glynn & Tamara Harris & Vadim Zipunnikov & Ciprian Crainiceanu & Jacek K. Urbanek, 2019. "Accelerometry Data in Health Research: Challenges and Opportunities," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(2), pages 210-237, July.

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