UPA Perpustakaan Universitas Jember

An oscillator-based smooth real-time estimate of gait phase for wearable roboticsv

Nicola Vitiello - Personal Name
Virginia Ruiz Garate - Personal Name
Renaud Ronsse - Personal Name
Marco Cempini - Personal Name

Thispaperpresentsanovelmethodologyforestimating the gait phase of human walking through a simple sensory apparatus. Three subsystems are combined: a primaryphaseestimatorbasedonadaptiveoscillators,adesired gait event detector and a phase error compensator. The estimatedgaitphaseisexpectedtolinearlyincreasefrom0to2π rad in one strideand remain continuous also when transiting tothenextstride.Wedesignedtwoexperimentalscenariosto validate this gait phase estimator, namely treadmill walking at different speeds and free walking. In the case of treadmill walking, the maximum phase error at the desired gait events wasfoundtobe0.155rad,andthemaximumphasedifference between the end of the previous stride and beginning of the currentstridewas0.020rad.Inthefreewalkingtrials,phase
ThisisoneofseveralpaperspublishedinAutonomousRobotscomprising the “Special Issue on Assistive and Rehabilitation Robotics”.
Marco Cempini was with The BioRobotics Institute, Scuola Superiore Sant’Anna, 56025 Pisa, Italy when coauthoring this work.
Tingfang Yan and Andrea Parri contributed equally to this work. B Tingfang Yan t.yan@sssup.it
1 The BioRobotics Institute, Scuola Superiore Sant’Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera, PI, Italy 2 Institute of Mechanics, Materials, and Civil Engineering; Institute of Neuroscience; and Louvain Bionics, Université catholique de Louvain, Place du Levant, 2 bte L5.04.02, 1348 Louvain-la-Neuve, Belgium 3 Center for Bionic Medicine, Rehabilitation Institute of Chicago, 345 E Superior St, Chicago, IL 60610, USA 4 The Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA 5 Don Carlo Gnocchi Foundation, Florence, Via di Scandicci, 265, Florence, Italy
erroratthedesiredgaiteventwasneverlargerthan0.278rad. Ouralgorithmoutperformedagainsttwootherbenchmarked methods. The good performance of our gait phase estimator could provide consistent and ﬁnely tuned assistance for an exoskeleton designed to augment the mobility of patients.

EB00000003498K Available

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Real-time gait phase estimate
Adaptive oscillators
Wearable robotics
Phase error learning

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An oscillator-based smooth real-time estimate of gait phase for wearable robotics

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An oscillator-based smooth real-time estimate of gait phase for wearable roboticsv

Nicola Vitiello - Personal NameVirginia Ruiz Garate - Personal NameRenaud Ronsse - Personal NameMarco Cempini - Personal Name

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Nicola Vitiello - Personal Name
Virginia Ruiz Garate - Personal Name
Renaud Ronsse - Personal Name
Marco Cempini - Personal Name