Fast and precise natural running measure using Physilog® sensors.

The only reliable and validated analysis of running technique with or without a treadmill: perfect for rapid in-store shoe selection and coaching.

  • Easy-to-use and rapid results

    One button to start the sensor, intuitive tablet interface with color coded reports that reference Gait Up’s population database.

  • 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.

  • Foot strike parameters

    Analyze running spatio-temporal parameters, including: cadence, pronation angle, strike angle, contact time, and symmetry. In addition to color codes, side-by-side comparison reports help visualize the effects of equipment or training.

  • Take it everywhere

    On or off the treadmill, let the runner do what’s natural. Included transport wallet for convenient use in the field.

  • “With Physilog, you can measure running in natural conditions, so that you can choose the appropriate footwear and the correct technique.”

    Prof. Grégoire Millet, Sport Sciences

  • In-shop shoe fitting based on running technique
  • Valorize in-shop vendor advice and service

2 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

Application for Android tablet

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


  • 2x rubber clips
  • 2x elastic straps
  • 2x USB cables
  • 1x tablet
  • 1x transport case
  • Accurate Estimation of Running Temporal Parameters Using Foot-worn Inertial Sensors. Falbriard et al, 2018
  • Contact time and foot strike angles estimation using foot-worn inertial sensors in running. Falbriard et al, 2017
  • Foot-worn inertial sensors assessment of the temporal events and contact time during running. Falbriard et al, 2017
  • Putting Together First-and Third-Person Approaches for Sport Activity Analysis: The Case of Ultra-Trail Runners’ Performance Analysis. Hauw et al, 2017
  • Running Mechanics During the World’s Most Challenging Mountain Ultra-MarathonMariani et al, 2015
  • Analysis of running using shoe sensors and EMG, application to the study of people after hip resurfacing. Mariani et al, 2012

Find the complete list of publications on our Science Page.