Επιστημονική Δημοσίευση από το Φ.Ι.Α. στο Διεθνές Συνέδριο SEEDA-CECNSM 2022

Στα πλαίσια του 7ου διεθνούς συνεδρίου “South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2022)” που έλαβε χώρα στις 23-25 Σεπτεμβρίου 2022 στο Επιστημονικό & Τεχνολογικό Πάρκο Ηπείρου, Ιωάννινα, Ελλάδα, συνεγράφη, απεστάλη, έγινε αποδεκτή και παρουσιάστηκε με επιτυχία από την Πανεπιστημιακή Κλινική Φυσικής Ιατρικής και Αποκατάστασης (Φ.Ι.Α.), η επιστημονική δημοσίευση με τίτλο “Variations of pressure data from insoles in normal population during the 10meter walking test and an appropriate parameters’ extraction algorithm: a pilot study”. Παρακάτω καταγράφετε η περίληψη (abstract) της δημοσίευσης και ένας σύνδεσμος (url) όπου βρίσκεται διαθέσιμη online.

  • Abstract: Our objective was to explore variations of pressure data from insole pressure sensors after a walking session and to produce an algorithm which extracts spatiotemporal gait parameters in close real time. In this study we performed a 10-meter stand up and walking test on 25 normal individuals. All subjects were walking at their comfortable speed during the test. The subjects were wearing in-soles equipped with 9 pressure sensors on each foot (the W-inshoe system by Medicapteurs). The W-inshoe system is simple, relatively cheap and reliable. System’s software is quite outdated, has multiple bugs and does not produce the appropriate numerical gait parameters, so we developed an algorithm to process the raw data from the insoles using MATLAB. The developed algorithm can successfully process the pressure data, remove noise, and produce the appropriate gait parameters accurately. Using the algorithm on our sampling pool, we procured the following results: Average peak pressure range was 644 to 1555 gram force (average: 1000gf, average stance period range was 0.64 to 0.85 seconds (average: 0. 76s) and double support period range was 0.17 to 22s (average: 0. 18s). Even though there were only 9 sensors in every insole, the data were sufficient to develop the algorithm. In the future, the algorithm could be used on a cloud-based application to extract pressure and spatiotemporal gait parameters from a simple and reliable insole system.
  • URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9932942&isnumber=9932894

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