Validation of smartphone step count algorithm used in STARFISH smartphone application

Aleksandra Dybus, Lorna Paul, Sally Wyke, Stephen Brewster, Jason M.R. Gill, Andrew Ramsay, Evan Campbell

Research output: Contribution to journalArticle

82 Downloads (Pure)

Abstract

Background: Smartphone sensors are underutilised in rehabilitation.
OBJECTIVE: To validate the step count algorithm used in the STARFISH smartphone application.
Methods: 22 healthy adults (8 male, 14 female) walked on a treadmill for 5 minutes at 0.44, 0.67, 0.90 and 1.33 m·s-1. Each wore an activPALTM and four Samsung Galaxy S3TM smartphones, with the STARFISH application running, in: 1) a belt carrycase, 2) a trouser or skirt pocket), 3a) a handbag on shoulder for females or 3b) shirt pocket for males and 4) an upper arm strap.
Step counts of the STARFISH application and the activPALTM were compared at corresponding speeds and Bland-Altman statistics used to assess level of agreement (LOA).
Results: The LOA between the STARFISH application and activPALTM varied across the four speeds and positions, but improved as speed increased. The LOA ranged from 105–177% at 0.44 m·s-1; 50–98% at 0.67 m·s-1; 19–67% at 0.9 m·s-1 and 8–53% at 1.33 m·s-1. The best LOAs were at 1.33 m·s-1 in the shirt pocket (8%) and upper arm strap (12%) positions.
Conclusions: Step counts measured by the STARFISH smartphone application are valid in most body positions especially at walking speeds of 0.9 m·s-1 and above.
Original languageEnglish
Pages (from-to)1157-1162
Number of pages6
JournalTechnology and Health Care
Volume25
Issue number6
DOIs
Publication statusPublished - 4 Dec 2017

Keywords

  • smartphone app
  • algorithm

Fingerprint Dive into the research topics of 'Validation of smartphone step count algorithm used in STARFISH smartphone application'. Together they form a unique fingerprint.

Cite this