Validity of using tri-axial accelerometers to measure human movement - Part II: Step counts at a wide range of gait velocities

Emma Fortune, Vipul Lugade, Melissa (Missy) M. Morrow, Kenton R Kaufman

Research output: Contribution to journalArticle

67 Citations (Scopus)

Abstract

A subject-specific step counting method with a high accuracy level at all walking speeds is needed to assess the functional level of impaired patients. The study aim was to validate step counts and cadence calculations from acceleration data by comparison to video data during dynamic activity. Custom-built activity monitors, each containing one tri-axial accelerometer, were placed on the ankles, thigh, and waist of 11 healthy adults. ICC values were greater than 0.98 for video inter-rater reliability of all step counts. The activity monitoring system (AMS) algorithm demonstrated a median (interquartile range; IQR) agreement of 92% (8%) with visual observations during walking/jogging trials at gait velocities ranging from 0.1 to 4.8 m/s, while FitBits (ankle and waist), and a Nike Fuelband (wrist) demonstrated agreements of 92% (36%), 93% (22%), and 33% (35%), respectively. The algorithm results demonstrated high median (IQR) step detection sensitivity (95% (2%)), positive predictive value (PPV) (99% (1%)), and agreement (97% (3%)) during a laboratory-based simulated free-living protocol. The algorithm also showed high median (IQR) sensitivity, PPV, and agreement identifying walking steps (91% (5%), 98% (4%), and 96% (5%)), jogging steps (97% (6%), 100% (1%), and 95% (6%)), and less than 3% mean error in cadence calculations.

Original languageEnglish (US)
Pages (from-to)659-669
Number of pages11
JournalMedical Engineering and Physics
Volume36
Issue number6
DOIs
StatePublished - 2014

Fingerprint

Gait
Accelerometers
Jogging
Ankle
Walking
Thigh
Wrist
Monitoring

Keywords

  • Accelerometer
  • Body-worn sensors
  • Gait velocity
  • Step detection

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biophysics
  • Medicine(all)

Cite this

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title = "Validity of using tri-axial accelerometers to measure human movement - Part II: Step counts at a wide range of gait velocities",
abstract = "A subject-specific step counting method with a high accuracy level at all walking speeds is needed to assess the functional level of impaired patients. The study aim was to validate step counts and cadence calculations from acceleration data by comparison to video data during dynamic activity. Custom-built activity monitors, each containing one tri-axial accelerometer, were placed on the ankles, thigh, and waist of 11 healthy adults. ICC values were greater than 0.98 for video inter-rater reliability of all step counts. The activity monitoring system (AMS) algorithm demonstrated a median (interquartile range; IQR) agreement of 92{\%} (8{\%}) with visual observations during walking/jogging trials at gait velocities ranging from 0.1 to 4.8 m/s, while FitBits (ankle and waist), and a Nike Fuelband (wrist) demonstrated agreements of 92{\%} (36{\%}), 93{\%} (22{\%}), and 33{\%} (35{\%}), respectively. The algorithm results demonstrated high median (IQR) step detection sensitivity (95{\%} (2{\%})), positive predictive value (PPV) (99{\%} (1{\%})), and agreement (97{\%} (3{\%})) during a laboratory-based simulated free-living protocol. The algorithm also showed high median (IQR) sensitivity, PPV, and agreement identifying walking steps (91{\%} (5{\%}), 98{\%} (4{\%}), and 96{\%} (5{\%})), jogging steps (97{\%} (6{\%}), 100{\%} (1{\%}), and 95{\%} (6{\%})), and less than 3{\%} mean error in cadence calculations.",
keywords = "Accelerometer, Body-worn sensors, Gait velocity, Step detection",
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