Calibration-free gait assessment by foot-worn inertial sensors

dc.contributor.authorLaidig, Daniel
dc.contributor.authorJocham, Andreas J.
dc.contributor.authorGuggenberger, Bernhard
dc.contributor.authorAdamer, Klemens
dc.contributor.authorFischer, Michael
dc.contributor.authorSeel, Thomas
dc.date.accessioned2022-01-17T13:51:39Z
dc.date.available2022-01-17T13:51:39Z
dc.date.issued2021-11-04
dc.description.abstractWalking is a central activity of daily life, and there is an increasing demand for objective measurement-based gait assessment. In contrast to stationary systems, wearable inertial measurement units (IMUs) have the potential to enable non-restrictive and accurate gait assessment in daily life. We propose a set of algorithms that uses the measurements of two foot-worn IMUs to determine major spatiotemporal gait parameters that are essential for clinical gait assessment: durations of five gait phases for each side as well as stride length, walking speed, and cadence. Compared to many existing methods, the proposed algorithms neither require magnetometers nor a precise mounting of the sensor or dedicated calibration movements. They are therefore suitable for unsupervised use by non-experts in indoor as well as outdoor environments. While previously proposed methods are rarely validated in pathological gait, we evaluate the accuracy of the proposed algorithms on a very broad dataset consisting of 215 trials and three different subject groups walking on a treadmill: healthy subjects (n = 39), walking at three different speeds, as well as orthopedic (n = 62) and neurological (n = 36) patients, walking at a self-selected speed. The results show a very strong correlation of all gait parameters (Pearson's r between 0.83 and 0.99, p < 0.01) between the IMU system and the reference system. The mean absolute difference (MAD) is 1.4 % for the gait phase durations, 1.7 cm for the stride length, 0.04 km/h for the walking speed, and 0.7 steps/min for the cadence. We show that the proposed methods achieve high accuracy not only for a large range of walking speeds but also in pathological gait as it occurs in orthopedic and neurological diseases. In contrast to all previous research, we present calibration-free methods for the estimation of gait phases and spatiotemporal parameters and validate them in a large number of patients with different pathologies. The proposed methods lay the foundation for ubiquitous unsupervised gait assessment in daily-life environments.en
dc.description.sponsorshipDFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berlinen
dc.identifier.eissn2673-253X
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/16138
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-14912
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc610 Medizin und Gesundheitde
dc.subject.otherinertial sensorsen
dc.subject.otherIMUen
dc.subject.otherhuman motion analysisen
dc.subject.othergait analysisen
dc.subject.othergait assessmenten
dc.subject.othergait phasesen
dc.subject.otherrehabilitationen
dc.subject.otherwalkingen
dc.titleCalibration-free gait assessment by foot-worn inertial sensorsen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber736418en
dcterms.bibliographicCitation.doi10.3389/fdgth.2021.736418en
dcterms.bibliographicCitation.journaltitleFrontiers in Digital Healthen
dcterms.bibliographicCitation.originalpublishernameFrontiersen
dcterms.bibliographicCitation.originalpublisherplaceLausanneen
dcterms.bibliographicCitation.volume3en
tub.accessrights.dnbfreeen
tub.affiliationFak. 4 Elektrotechnik und Informatik>Inst. Energie- und Automatisierungstechnik>FG Regelungssystemede
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.groupFG Regelungssystemede
tub.affiliation.instituteInst. Energie- und Automatisierungstechnikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen
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