The Gaitprint: Identifying Individuals by Their Running Style

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 14; p. 3810
• Main Authors: Weich, Christian, M. Vieten, Manfred
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.07.2020; MDPI
• Subjects: Adult; Anaerobic threshold; Athletes; attractor method; Biometric Identification - methods; Efficiency; Female; Gait; Gait Analysis; human cyclic motion; Humans; individual locomotion; Male; Methods; Microelectromechanical systems; Middle Aged; Motion capture; Movement; Principal components analysis; recognition; Running; running quality; Sensors; Software; Germany; recognition; individual locomotion; running quality; attractor method; human cyclic motion
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20143810

Recognizing the characteristics of a well-developed running style is a central issue in athletic sub-disciplines. The development of portable micro-electro-mechanical-system (MEMS) sensors within the last decades has made it possible to accurately quantify movements. This paper introduces an analysis method, based on limit-cycle attractors, to identify subjects by their specific running style. The movement data of 30 athletes were collected over 20 min. in three running sessions to create an individual gaitprint. A recognition algorithm was applied to identify each single individual as compared to other participants. The analyses resulted in a detection rate of 99% with a false identification probability of 0.28%, which demonstrates a very sensitive method for the recognition of athletes based solely on their running style. Further, it can be seen that these differentiations can be described as individual modifications of a general running pattern inherent in all participants. These findings open new perspectives for the assessment of running style, motion in general, and a person’s identification, in, for example, the growing e-sports movement.