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PhysiRun Lab

Bring your analysis one step further!

Fast and precise natural running measure using Physilog® sensors.
For the first time, it is possible to obtain a science-grade measure of runners out of the lab. Get a precise stride-by-stride biomechanical analysis on a full marathon in 3 minutes.

  • Easy-to-use and rapid results

    One button to start the sensor. Get a precise stride-by-stride biomechanical analysis on a full marathon in 3 minutes.

  • 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.

  • Standalone recording 

    Collect your data and analyse it later. You can now record up to 4 hours.

  • Detailed cycle-by-cycle analysis

    Do your own statistics

  • Foot strike parameters

    Analyze running spatio-temporal parameters, including: cadence, pronation angle, strike angle, contact time, and symmetry.

  • Take it everywhere

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

  • Coaching follow-up to measure progress
  • Convenient tool for scientific research and sports medicine
  • Teach classes in biomechanics and running science

2 Physilog® 5 motion sensors worn on the foot

  • USB data transfer for desktop software with PhysiRun Lab
  • Access raw data with the onboard SD card and our free Research Toolkit

PhysiRun Lab for Mac/Windows

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

Accessories

  • 1 PhysiRun Lab Software (unlimited license)
  • 2 Physilog®5 sensors (9 grams,waterproof)
  • 1 Smart watch
  • 2 Rubber clips
  • 2 elastic straps
  • 2 USB cables
  • 1 Smart watch
  • 1 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.