Ben Dali, Omar ; Sellami, Youssef ; Zhukov, Sergey ; Seggern, Heinz von ; Schäfer, Niklas ; Latsch, Bastian ; Sessler, Gerhard M. ; Beckerle, Philipp ; Kupnik, Mario (2022)
Ultrasensitive and low-cost insole for gait analysis using piezoelectrets.
IEEE SENSORS 2022. Dallas, TX, USA (30.10.-02.11.2022)
doi: 10.1109/SENSORS52175.2022.9967198
Konferenzveröffentlichung, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
The emerging need of wearable healthcare monitoring systems for e.g. predicting cognitive decline, necessitates practical requirements such as high sensor sensitivity and low fabrication costs. In this work, we present an ultrasensitive piezoelectric insole using 3D-printed flexible piezoelectret with a readout circuit that sends measurement data via WiFi. The insole is printed using pure polypropylene filament and consists of eight independent sensors, each with a piezoelectric d 33 coefficient of approximately 2000 pC/N. The active part of the insole is protected using a 3D-printed polylactic acid cover that features eight defined embossments on the bottom part, which focus the force on the sensors and act as overload protection against excessive stress. In addition to determining the gait pattern, an accelerometer is implemented to measure kinematic parameters and validate the sensor output signals. The combination of the high sensitivity of the sensors and the kinematic movement of the foot, opens new perspectives regarding diagnosis possibilities through gait analysis.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2022 |
Autor(en): | Ben Dali, Omar ; Sellami, Youssef ; Zhukov, Sergey ; Seggern, Heinz von ; Schäfer, Niklas ; Latsch, Bastian ; Sessler, Gerhard M. ; Beckerle, Philipp ; Kupnik, Mario |
Art des Eintrags: | Bibliographie |
Titel: | Ultrasensitive and low-cost insole for gait analysis using piezoelectrets |
Sprache: | Englisch |
Publikationsjahr: | 2022 |
Ort: | Piscataway, NJ |
Verlag: | IEEE |
Buchtitel: | 2022 IEEE SENSORS Proceedings |
Kollation: | 4 Seiten |
Veranstaltungstitel: | IEEE SENSORS 2022 |
Veranstaltungsort: | Dallas, TX, USA |
Veranstaltungsdatum: | 30.10.-02.11.2022 |
DOI: | 10.1109/SENSORS52175.2022.9967198 |
Zugehörige Links: | |
Kurzbeschreibung (Abstract): | The emerging need of wearable healthcare monitoring systems for e.g. predicting cognitive decline, necessitates practical requirements such as high sensor sensitivity and low fabrication costs. In this work, we present an ultrasensitive piezoelectric insole using 3D-printed flexible piezoelectret with a readout circuit that sends measurement data via WiFi. The insole is printed using pure polypropylene filament and consists of eight independent sensors, each with a piezoelectric d 33 coefficient of approximately 2000 pC/N. The active part of the insole is protected using a 3D-printed polylactic acid cover that features eight defined embossments on the bottom part, which focus the force on the sensors and act as overload protection against excessive stress. In addition to determining the gait pattern, an accelerometer is implemented to measure kinematic parameters and validate the sensor output signals. The combination of the high sensitivity of the sensors and the kinematic movement of the foot, opens new perspectives regarding diagnosis possibilities through gait analysis. |
Freie Schlagworte: | Fabrication, Sensitivity, Costs, Force, Kinematics, Medical services, Wireless fidelity, Ferroelectret, piezoelectret, 3D printing, gait analysis |
Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 621.3 Elektrotechnik, Elektronik |
Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Mess- und Sensortechnik |
Hinterlegungsdatum: | 13 Mai 2024 08:54 |
Letzte Änderung: | 13 Mai 2024 08:55 |
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Ultrasensitive and low-cost insole for gait analysis using piezoelectrets. (deposited 03 Mai 2024 12:32)
- Ultrasensitive and low-cost insole for gait analysis using piezoelectrets. (deposited 13 Mai 2024 08:54) [Gegenwärtig angezeigt]
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