Characterizing Human Walking Dynamics Across Age: A Control Engineering Approach

Abstract: Introduction While various models and studies have investigated the simulation and theoretical description of human gait, previous research has not considered irregular situations such as slipping and tripping. However, understanding these situations could be crucial and provide insight into assessing dynamic balance, a factor that is closely linked to the risk of falling. The first step is to investigate the system under normal walking using a participant group that includes people who are particularly susceptible to an increased risk of falling, such as older adults or people with certain health conditions that have so far been neglected in the literature. Methods In this study a control engineering approach was used to estimate the parameters of the human gait system. A total of 42 subjects aged 18 to 78 years, with different body masses and walking speeds, were analyzed. Measurements were conducted on a treadmill with integrated force plates, while participants wore inertial measurement units (IMUs) at lumbar level and were filmed with cameras. Results The calculated spring-mass-damping model parameters, including stiffness (k) and damping (c), varied widely among participants, with stiffness ranging from 4.45 to 45.53 kN/m and damping from 0.26 to 2.13 kNs/m. Contrary to previous findings, no linear relationships were observed between stiffness or damping and velocity, age, or mass. Outliers were identified and related in a plausible way to visual inspection. Conclusion In conclusion, our study successfully characterized human walking during periodic excitation for a diverse participant group using a simple control engineering approach, yielding comparable results to previous studies. Our results pave the way for future investigations to analyze the response of an individual participant to irregular gait perturbations.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Characterizing Human Walking Dynamics Across Age: A Control Engineering Approach ; volume:10 ; number:4 ; year:2024 ; pages:236-239 ; extent:4 ; Current directions in biomedical engineering ; 10, Heft 4 (2024), 236-239 (gesamt 4)

Beteiligte, Orts- und Zeitangaben

• Urheber: Feld, Lea ; Hellmers, Sandra ; Schell-Majoor, Lena ; Koschate, Jessica ; Zieschang, Tania ; Kollmeier, Birger ; Hein, Andreas

Weitere Informationen

• DOI: 10.1515/cdbme-2024-2057
• URN: urn:nbn:de:101:1-2412181741297.391337222630
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:35 MESZ