Assessment of walking features from foot inertial sensing

By Angelo Maria Sabatini, C. Martelloni, S. Scapellato, F. Cavallo. IEEE Transactions on Biomedical Engineering, 2005

674 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Endocrinology, Diabetes and Metabolism

View Paper: https://www.semanticscholar.org/paper/47919a3088cd5a571515065ebc68307b51fef40e

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In Biomedical Engineering

In Endocrinology, Diabetes and Metabolism

Citations in the corpus

Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing (2006, background): “In our recent work on foot inertial sensing for estimating temporo-spatial parameters of gait [21], [24], it is shown that limitations in the sampling frequency can be tolerated down to 25–50 Hz, provided that strap-down integrals can be reliably reset once in a gait cycle [21]; we also demonstrate…”
Ambulatory Position and Orientation Tracking Fusing Magnetic and Inertial Sensing (2007, methodology): “An estimate in the horizontal plane with respect to a known starting point can also be made by means of a gait phase detector, a step counter or by processing signals from inertial sensors on the feet [24], [25],”
Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention. (2014, background): “Simple systems involving a single accelerometer or a foot switch have been used to detect various spatiotemporal parameters such as step count, stride length, cadence, and walking speed [8–11], while more complex systems have been created with arrays of accelerometers, gyroscopes, and magnetometers ”
Accelerometry: a technique for quantifying movement patterns during walking. (2008, background): “[16] Thigh and tibia Willemsen et al.”
Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers (2010, background): “gyros has fostered several research reports, where they are used for applications in gait analysis, either alone or in combination with accelerometers [24,25].”
3D gait assessment in young and elderly subjects using foot-worn inertial sensors. (2010, methodology): “Compared to other inertial-based gait analysis system (Aminian et al., 2002; Salarian et al., 2004; Sabatini et al., 2005; Schepers et al., 2007), similar or slightly better accuracy and precision was obtained for SL and SV.”
Estimating Three-Dimensional Orientation of Human Body Parts by Inertial/Magnetic Sensing (2011, background): “Simplifying assumptions are quite common in applications to gait analysis [65].”
Assessment and Classification of Early-Stage Multiple Sclerosis With Inertial Sensors: Comparison Against Clinical Measures of Disease State (2015, background): “Recent research has investigated the use of inertial sensors for quantitative evaluation of gait [9], [10] and to quantify movement in the TUG test [10], [11].”
Inertial Sensor-Based Gait Recognition: A Review (2015, methodology): “) [15], detection of gait phases [5] or kinematic parameters (joint angle measurement) [4,16] either expressed implicitly by applying special feature extraction techniques.”