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doi:10.22028/D291-39100
Titel: | Effects of age, body height, body weight, body mass index and handgrip strength on the trajectory of the plantar pressure stance-phase curve of the gait cycle |
VerfasserIn: | Wolff, Christian Steinheimer, Patrick Warmerdam, Elke Dahmen, Tim Slusallek, Philipp Schlinkmann, Christian Chen, Fei Orth, Marcel Pohlemann, Tim Ganse, Bergita |
Sprache: | Englisch |
Titel: | Frontiers in Bioengineering and Biotechnology |
Bandnummer: | 11 |
Verlag/Plattform: | Frontiers |
Erscheinungsjahr: | 2023 |
Freie Schlagwörter: | gait motion analysis ground reaction (forces) ageing obesity insoles handgrip strengh smart healthcare |
DDC-Sachgruppe: | 610 Medizin, Gesundheit |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
Abstract: | The analysis of gait patterns and plantar pressure distributions via insoles is increasingly used to monitor patients and treatment progress, such as recovery after surgeries. Despite the popularity of pedography, also known as baropodography, characteristic effects of anthropometric and other individual parameters on the trajectory of the stance phase curve of the gait cycle have not been previously reported. We hypothesized characteristic changes of age, body height, body weight, body mass index and handgrip strength on the plantar pressure curve trajectory during gait in healthy participants. Thirty-seven healthy women and men with an average age of 43.65 ± 17.59 years were fitted with Moticon OpenGO insoles equipped with 16 pressure sensors each. Data were recorded at a frequency of 100 Hz during walking at 4 km/h on a level treadmill for 1 minute. Data were processed via a custom-made step detection algorithm. The loading and unloading slopes as well as force extrema-based parameters were computed and characteristic correlations with the targeted parameters were identified via multiple linear regression analysis. Age showed a negative correlation with the mean loading slope. Body height correlated with Fmeanload and the loading slope. Body weight and the body mass index correlated with all analyzed parameters, except the loading slope. In addition, handgrip strength correlated with changes in the second half of the stance phase and did not affect the first half, which is likely due to stronger kick-off. However, only up to 46% of the variability can be explained by age, body weight, height, body mass index and hand grip strength. Thus, further factors must affect the trajectory of the gait cycle curve that were not considered in the present analysis. In conclusion, all analyzed measures affect the trajectory of the stance phase curve. When analyzing insole data, it might be useful to correct for the factors that were identified by using the regression coefficients presented in this paper. |
DOI der Erstveröffentlichung: | 10.3389/fbioe.2023.1110099 |
URL der Erstveröffentlichung: | https://www.frontiersin.org/articles/10.3389/fbioe.2023.1110099 |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-391002 hdl:20.500.11880/35256 http://dx.doi.org/10.22028/D291-39100 |
ISSN: | 2296-4185 |
Datum des Eintrags: | 21-Feb-2023 |
Bezeichnung des in Beziehung stehenden Objekts: | Supplementary Material |
In Beziehung stehendes Objekt: | https://www.frontiersin.org/articles/file/downloadfile/1110099_supplementary-materials_datasheets_1_xlsx/octet-stream/Data%20Sheet%201.XLSX/1/1110099 |
Fakultät: | M - Medizinische Fakultät MI - Fakultät für Mathematik und Informatik |
Fachrichtung: | M - Chirurgie MI - Informatik |
Professur: | M - Prof. Dr. med. Bergita Ganse M - Prof. Dr. Tim Pohlemann MI - Prof. Dr. Philipp Slusallek |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Dateien zu diesem Datensatz:
Datei | Beschreibung | Größe | Format | |
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fbioe-11-1110099.pdf | 1,07 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons