Measures of gait quality, such as symmetry and variability, are generally derived from assessments in a controlled (laboratory) environment. Within the MOVITA (MOve, VIsualize, TAylor) project we implemented a gait quality algorithm into our MoveMonitor analytics pipeline. This means that we can now derive gait quality measures from walking in daily-life. Gait quality metrics derived from daily-life walking are more representative than when derived from laboratory assessments. Also, daily-life measurements generate dozens, if not hundreds, of gait episodes which we can all analyse. The algorithm was developed by VU University Amsterdam and has proven itself extensively in fall risk research. It will now be tested in as a feedback tool after knee joint replacement with ultimate goal to reduce hospital visits.