**Marco Rabuffetti \*, Giovanni Marco Scalera and Maurizio Ferrarin**

IRCCS Fondazione Don Carlo Gnocchi, Milano 20121, Italy; gscalera@dongnocchi.it (G.M.S.); mferrarin@dongnocchi.it (M.F.)

**\*** Correspondence: mrabuffetti@dongnocchi.it; Tel.: +39-02-40308-544

Received: 16 November 2018; Accepted: 18 January 2019; Published: 26 January 2019

**Abstract:** The regularity of pseudo-periodic human movements, including locomotion, can be assessed by autocorrelation analysis of measurements using inertial sensors. Though sensors are generally placed on the trunk or pelvis, movement regularity can be assessed at any body location. Pathological factors are expected to reduce regularity either globally or on specific anatomical subparts. However, other non-pathological factors, including gait strategy (walking and running) and speed, modulate locomotion regularity, thus potentially confounding the identification of the pathological factor. The present study's objectives were (1) to define a multi-sensor method based on the autocorrelation analysis of the acceleration module (norm of the acceleration vector) to quantify regularity; (2) to conduct an experimental study on healthy adult subjects to quantify the effect on movement regularity of gait strategy (walking and running at the same velocity), gait speed (four speeds, lower three for walking, upper two for running), and sensor location (on four different body parts). Twenty-five healthy adults participated and four triaxial accelerometers were located on the seventh cervical vertebra (C7), pelvis, wrist, and ankle. The results showed that increasing velocity was associated with increasing regularity only for walking, while no difference in regularity was observed between walking and running. Regularity was generally highest at C7 and ankle, and lowest at the wrist. These data confirm and complement previous literature on regularity assessed on the trunk, and will support future analyses on individuals or groups with specific pathologies affecting locomotor functions.

**Keywords:** wearable/inertial sensors; accelerometer; regularity; variability; human; motion; locomotion; autocorrelation
