TUdatalib : Dataset for Event Detection in Gait Analysis from 3D-Printed Piezoelectric PLA-Based Insole on an Instrumented Treadmill

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dc.contributor.author	Latsch, Bastian
dc.contributor.author	Schäfer, Niklas
dc.contributor.author	Grimmer, Martin
dc.contributor.author	Ben Dali, Omar
dc.contributor.author	Mohseni, Omid
dc.contributor.author	Bleichner, Niklas
dc.contributor.author	Altmann, Alexander
dc.contributor.author	Schaumann, Stephan
dc.contributor.author	Wolf, Sebastian
dc.contributor.author	Seyfarth, Andre
dc.contributor.author	Beckerle, Philipp
dc.contributor.author	Kupnik, Mario
dc.date.accessioned	2024-03-05T13:02:33Z
dc.date.available	2024-03-05T13:02:33Z
dc.date.issued	2024
dc.identifier.uri	https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4152
dc.identifier.uri	https://doi.org/10.48328/tudatalib-1360
dc.description	In the experiment, one test person wearing a ferroelectret insole in the right shoe walks on an instrumented treadmill. The dataset contains data from four ferroelectret sensors in the insole and vertical ground reaction forces (GRF) from an instrumented treadmill across five different walking speeds. The ferroelectret insole data are filtered and given in Volt. The GRF treadmill data from the right side are filtered and given in Newton. The data are segmented into steps from one heel strike to the same foot's following heel strike and normalized into 1000 data points per step. Each row contains one step with 1000 columns. The amount of steps/rows depends on the walking speed: 74 for slowest v050, 124 for fastest v150. Please find the full description in the corresponding publication, full instructions for usage in the README.md file. Copyright of thumbnail image 2024, IEEE.	en
dc.language.iso	en	en
dc.relation	IsSupplementTo;DOI;10.1109/JSEN.2024.3416847	en
dc.relation	IsReferencedBy;DOI;10.1109/JSEN.2024.3416847	en
dc.rights	Creative Commons Attribution 4.0
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	smart insole	en
dc.subject	gait analysis	en
dc.subject	human locomotion	en
dc.subject	piezoelectric sensor	en
dc.subject	ferroelectret	en
dc.subject	gait event detection	en
dc.subject	sensor characterization	en
dc.subject.classification	4.41-01 Automatisierungstechnik, Mechatronik, Regelungssysteme, Intelligente Technische Systeme, Robotik	de_DE
dc.subject.classification	4.41-02 Messsysteme	de_DE
dc.subject.classification	4.41-05 Arbeitswissenschaft, Ergonomie, Mensch-Maschine-Systeme	de_DE
dc.subject.classification	4.41-06 Biomedizinische Systemtechnik	de_DE
dc.subject.classification	4.42-01 Elektronische Halbleiter, Bauelemente und Schaltungen, Integrierte Systeme, Sensorik, Theoretische Elektrotechnik	de_DE
dc.subject.ddc	621.3
dc.subject.ddc	620
dc.title	Dataset for Event Detection in Gait Analysis from 3D-Printed Piezoelectric PLA-Based Insole on an Instrumented Treadmill	en
dc.type	Dataset	en
dc.type	Software	en
tud.project	DFG \| GRK2761 \| TP_Kupnik_GRK_2761	de_DE
tud.project	DFG \| GRK 2761 \| TP_Beckerle_GRK_2761	de_DE
tud.project	DFG \| GRK2761 \| TP_Seyfarth_GRK_2761	de_DE
tud.project	DFG \| GRK2761 \| TP_Heidelberg_GRK_27	de_DE
tud.unit	TUDa
tud.history.classification	Version=2020-2024;407-01 Automatisierungstechnik, Regelungssysteme, Robotik, Mechatronik, Cyber Physical Systems
tud.history.classification	Version=2020-2024;407-02 Messsysteme
tud.history.classification	Version=2020-2024;407-05 Arbeitswissenschaft, Ergonomie, Mensch-Maschine-Systeme
tud.history.classification	Version=2020-2024;407-06 Biomedizinische Systemtechnik
tud.history.classification	Version=2020-2024;408-01 Elektronische Halbleiter, Bauelemente und Schaltungen, Integrierte Systeme