An Energy-Saving Algorithm for Energy Expenditure Estimation with a Smartphone Sensor Based Approach: a Contribution to the Mobility Measurement in e-Health

Abstract : This paper introduces a predictive function for total energy expenditure (TEE) estimation of the current life using the embedded smartphone accelerometer sensor. Our research encompasses definition of an energy-saving function without any hypothesis on its initial relative position. Six 25-year-old highly graduate participants wore a smartphone in a front pants pocket and a valid Armband device for a day of a desk job. The performance of the proposed function is estimated by using our smartphone application and evaluated by comparing TEE given by the function with TEE of Armband device. The mean gap of TEE between our function and Armband was less than 15%. This work is a preliminary step forward definition of a new predictive function well tuned for representative French population. Our work is now directed on validation on a larger population sample.
Document type :
Reports
Complete list of metadatas

Cited literature [13 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01158743
Contributor : Archive Ouverte Prodinra <>
Submitted on : Monday, June 1, 2015 - 8:09:57 PM
Last modification on : Friday, August 30, 2019 - 2:50:02 PM
Long-term archiving on: Tuesday, September 15, 2015 - 9:17:48 AM

File

IntelliLife_V0_20150518_{D6CBC...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01158743, version 1
  • PRODINRA : 305388

Collections

Citation

Martine Duclos, Gérard Fleury, Romain Guidoux, Philippe Lacomme, Pierre-Henri Manenq, et al.. An Energy-Saving Algorithm for Energy Expenditure Estimation with a Smartphone Sensor Based Approach: a Contribution to the Mobility Measurement in e-Health. [Rapport de recherche] auto-saisine. 2015, 4 p. ⟨hal-01158743⟩

Share

Metrics

Record views

451

Files downloads

261