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Gait Analysis

Simple and accurate gait analysis with Physilog® sensors.

Objective measurement of 25 spatio-temporal gait parameters in as little as 1 minute for clinical routine and research.

  • 25 outcome parameters in PDF or XLS

    Gait spatio-temporal parameters including speed, variability, symmetry and toe clearance with color code for interpretation. Check out a sample report.

  • Easy-to-use mobile App, Mac and PC

    One button to start the sensor, intuitive user interface and reports, with options to discard initiation and turn cycles.

  • Automatic alignment and calibration

    Our algorithm auto-calibrates every test. Use the provided clip or elastic strap to securely fasten Physilog® below the ankle, and that’s it.

  • Scientifically validated accuracy

    Validated against lab gold standards on various populations including Older adults, Parkinson’s disease, Cerebral palsy and Stroke. Check out the publications on our Science Page.

  • “We use Gait Up for teaching purposes and in clinical research protocols.

    It allows us to easily measure gait outside of the lab.”

    L. Allet, Physiotherapist

  • Pre/post treatment evaluation in routine
  • Objective fall risk & motor symptom assessment in clinical routine
  • Provide feedback to the patient
  • Teach classes in biomechanics and physiotherapy

2x Physilog® 5 motion sensors worn on the foot

  • Wireless data transfer to companion mobile application
  • USB data transfer for desktop software
  • Access raw data with the onboard SD card and our free Research Toolkit

Gait Analysis mobile and desktop software

Application for Android tablet (designed for routine)

  • Generate standard reports
  • Generate side-by-side comparison reports
  • Requires WiFi or 3G/4G data connection

Desktop software for Mac/Windows (designed for research)

  • Generate standard reports
  • Cycle-by-cycle data in XLS
  • Run directly from USB key (no internet required)

Accessories

  • 2x rubber clips
  • 2x elastic straps
  • 2x USB cables
  • 1x transport case

Studies

Find the complete list of publications on our Science Page.

  • Gait analysis using shoe-worn inertial sensors: how is foot clearance related to walking speed? Aminian et al, 2014
  • Spatio-temporal gait analysis in children with cerebral palsy using foot-worn inertial sensors. Bourgeois et al, 2014
  • Gait and foot clearance parameters obtained using shoe-worn inertial sensors in a large-population sample of older adults. Dadashi et al, 2013
  • On-shoe wearable sensors for gait and turning assessment of patients with Parkinson’s disease. Mariani et al, 2013
  • Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors. Mariani et al, 2013
  • The Relationship Between Fear Of Falling And Foot Clearance In Older People. Rochat et al, 2012
  • Heel and toe clearance estimation for gait analysis using wireless inertial sensors. Mariani et al, 2012

For more publications, find the whole list under our Science Page.