Calibration-free gait assessment by foot-worn inertial sensors
| dc.contributor.author | Laidig, Daniel | |
| dc.contributor.author | Jocham, Andreas J. | |
| dc.contributor.author | Guggenberger, Bernhard | |
| dc.contributor.author | Adamer, Klemens | |
| dc.contributor.author | Fischer, Michael | |
| dc.contributor.author | Seel, Thomas | |
| dc.date.accessioned | 2022-01-17T13:51:39Z | |
| dc.date.available | 2022-01-17T13:51:39Z | |
| dc.date.issued | 2021-11-04 | |
| dc.description.abstract | Walking 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.sponsorship | DFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berlin | en |
| dc.identifier.eissn | 2673-253X | |
| dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/16138 | |
| dc.identifier.uri | http://dx.doi.org/10.14279/depositonce-14912 | |
| dc.language.iso | en | en |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject.ddc | 610 Medizin und Gesundheit | de |
| dc.subject.other | inertial sensors | en |
| dc.subject.other | IMU | en |
| dc.subject.other | human motion analysis | en |
| dc.subject.other | gait analysis | en |
| dc.subject.other | gait assessment | en |
| dc.subject.other | gait phases | en |
| dc.subject.other | rehabilitation | en |
| dc.subject.other | walking | en |
| dc.title | Calibration-free gait assessment by foot-worn inertial sensors | en |
| dc.type | Article | en |
| dc.type.version | publishedVersion | en |
| dcterms.bibliographicCitation.articlenumber | 736418 | en |
| dcterms.bibliographicCitation.doi | 10.3389/fdgth.2021.736418 | en |
| dcterms.bibliographicCitation.journaltitle | Frontiers in Digital Health | en |
| dcterms.bibliographicCitation.originalpublishername | Frontiers | en |
| dcterms.bibliographicCitation.originalpublisherplace | Lausanne | en |
| dcterms.bibliographicCitation.volume | 3 | en |
| tub.accessrights.dnb | free | en |
| tub.affiliation | Fak. 4 Elektrotechnik und Informatik::Inst. Energie- und Automatisierungstechnik::FG Regelungssysteme | de |
| tub.affiliation.faculty | Fak. 4 Elektrotechnik und Informatik | de |
| tub.affiliation.group | FG Regelungssysteme | de |
| tub.affiliation.institute | Inst. Energie- und Automatisierungstechnik | de |
| tub.publisher.universityorinstitution | Technische Universität Berlin | en |