Synchronized sensor insoles for clinical gait analysis in home-monitoring applications

Beitrag bei einer Tagung
(Konferenzbeitrag)


Details zur Publikation

Autorinnen und Autoren: Roth N, Martindale C, Gaßner H, Kohl Z, Klucken J, Eskofier B
Verlag: Walter de Gruyter GmbH
Jahr der Veröffentlichung: 2018
Band: 4
Heftnummer: 1
Seitenbereich: 433-437
ISSN: 2364-5504
Sprache: Englisch


Abstract

Wearable sensor systems are of increasing interest in clinical gait
analysis. However, little information about gait dynamics of patients
under free living conditions is available, due to the challenges of
integrating such systems unobtrusively into a patient’s everyday live.
To address this limitation, new, fully integrated low power sensor
insoles are proposed, to target applications particularly in
home-monitoring scenarios. The insoles combine inertial as well as
pressure sensors and feature wireless synchronization to acquire
biomechanical data of both feet with a mean timing offset of 15.0 μs.
The proposed system was evaluated on 15 patients with mild to severe
gait disorders against the GAITRite® system as reference.
Gait events based on the insoles’ pressure sensors were manually
extracted to calculate temporal gait features such as double support
time and double support. Compared to the reference system a mean error
of 0.06 s ±0.06 s and 3.89 % ±2.61 % was achieved,
respectively. The proposed insoles proved their ability to acquire
synchronized gait parameters and address the requirements for
home-monitoring scenarios, pushing the boundaries of clinical gait
analysis.


FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Eskofier, Björn Prof. Dr.
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Gaßner, Heiko Dr. phil.
Molekular-Neurologische Abteilung in der Neurologischen Klinik
Klucken, Jochen Prof. Dr.
Medizinische Fakultät
Kohl, Zacharias PD Dr.
Medizinische Fakultät
Martindale, Christine
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Roth, Nils
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)


Zitierweisen

APA:
Roth, N., Martindale, C., Gaßner, H., Kohl, Z., Klucken, J., & Eskofier, B. (2018). Synchronized sensor insoles for clinical gait analysis in home-monitoring applications. (pp. 433-437). Walter de Gruyter GmbH.

MLA:
Roth, Nils, et al. "Synchronized sensor insoles for clinical gait analysis in home-monitoring applications." Walter de Gruyter GmbH, 2018. 433-437.

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Zuletzt aktualisiert 2019-09-02 um 13:50

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