title: An Evaluation of Commercial Pedometers for Monitoring Slow Walking Speed Populations.
abstract: Pedometers are considered desirable devices for monitoring physical activity. Two population groups of interest include patients having undergone surgery in the lower extremities or who are otherwise weakened through disease, medical treatment, or surgery procedures, as well as the slow walking senior population. For these population groups, pedometers must be able to perform reliably and accurately at slow walking speeds. The objectives of this study were to evaluate the step count accuracy of three commercially available pedometers, the Yamax (Tokyo, Japan) Digi-Walker(®) SW-200 (YM), the Omron (Kyoto, Japan) HJ-720 (OM), and the Fitbit (San Francisco, CA) Zip (FB), at slow walking speeds, specifically at 1, 2, and 3 km/h, and to raise awareness of the necessity of focusing research on step-counting devices and algorithms for slow walking populations.
  
  
  
  Fourteen participants 29.93 ±4.93 years of age were requested to walk on a treadmill at the three specified speeds, in four trials of 100 steps each. The devices were worn by the participants on the waist belt. The pedometer counts were recorded, and the error percentage was calculated.
  
  
  
  The error rate of all three evaluated pedometers decreased with the increase of speed: at 1 km/h the error rates varied from 87.11% (YM) to 95.98% (FB), at 2 km/h the error rates varied from 17.27% (FB) to 46.46% (YM), and at 3 km/h the error rates varied from 22.46% (YM) to a slight overcount of 0.70% (FB).
  
  
  
  It was observed that all the evaluated devices have high error rates at 1 km/h and mixed error rates at 2 km/h, and at 3 km/h the error rates are the smallest of the three assessed speeds, with the OM and the FB having a slight overcount. These results show that research on pedometers' software and hardware should focus more on accurate step detection at slow walking speeds.
authors.affiliation: 1 Section of ECE, Department of Engineering, Aarhus University , Aarhus, Denmark .
authors.forename: Femina H A
authors.initials: FH
authors.lastname: Beevi
authors.affiliation: 2 Algorithm Center, University of Minho , Guimarães, Portugal .
authors.forename: Jorge
authors.initials: J
authors.lastname: Miranda
authors.affiliation: 1 Section of ECE, Department of Engineering, Aarhus University , Aarhus, Denmark .
authors.forename: Christian F
authors.initials: CF
authors.lastname: Pedersen
authors.affiliation: 1 Section of ECE, Department of Engineering, Aarhus University , Aarhus, Denmark .
authors.forename: Stefan
authors.initials: S
authors.lastname: Wagner
mesh_terms: D056044:Actigraphy / Q000295:instrumentation* / Q000592:standards*; D000328:Adult; D005080:Exercise Test; D005260:Female; D006801:Humans; D008297:Male; D000072797:Walking Speed
keywords: e-health; home health monitoring; rehabilitation; sensor technology; telehealth