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Assessment of Sit-to-Stand Transfers during Daily Life Using an Accelerometer on the Lower Back.

Lukas Adamowicz1, F Isik Karahanoglu1, Christopher Cicalo1

  • 1Pfizer, Inc., Cambridge, MA 02139, USA.

Sensors (Basel, Switzerland)
|November 24, 2020
PubMed
Summary

A new algorithm using a single lower back accelerometer can accurately detect sit-to-stand transfers in daily life. This technology enables reliable, long-term monitoring of functional mobility for various age groups and individuals with Parkinson's disease.

Keywords:
accelerometeralgorithmfree-livingsit-to-standwearable technology

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Wearable Sensors

Background:

  • Sit-to-stand (STS) transfers are crucial for functional mobility.
  • Current STS detection methods often require multiple sensors or lab-based assessments.
  • Objective, long-term monitoring of STS transfers in daily life is needed.

Purpose of the Study:

  • To develop and validate a novel wavelet-based algorithm for detecting STS transfers using a single lower back accelerometer.
  • To assess the algorithm's performance in detecting age-related differences and the impact of monitoring duration in free-living conditions.
  • To compare the algorithm's performance against existing commercial and published methods.

Main Methods:

  • A wavelet-based algorithm was developed for STS transfer detection from lower back accelerometer data.
  • The algorithm was validated in laboratory settings with healthy adults (younger and older) and individuals with Parkinson's disease (PwPD).
  • The algorithm was applied to data collected during free-living conditions to analyze STS transfer features.

Main Results:

  • The proposed algorithm demonstrated high precision, outperforming a commercial system and a previously published algorithm in both healthy adults and PwPD.
  • Features extracted from free-living STS transfers effectively detected age-related group differences with higher significance than lab-based data.
  • Simulations indicated that 3 days of monitoring is sufficient for reliable measurement of STS transfer features.

Conclusions:

  • A single lower back accelerometer with the proposed algorithm enables feasible, objective, and long-term monitoring of STS transfers during daily life.
  • The developed algorithm offers a promising tool for assessing functional mobility and its changes over time.
  • Further validation in diverse patient populations is recommended to evaluate algorithm performance and feature reliability.