Literature DB >> 33520949

Estimating Movement Smoothness From Inertial Measurement Units.

Alejandro Melendez-Calderon1,2,3, Camila Shirota4,5,6, Sivakumar Balasubramanian7.   

Abstract

Inertial measurement units (IMUs) are increasingly used to estimate movement quality and quantity to the infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, many of which assume that the translational and rotational kinematics measured by IMUs can be directly used with the smoothness measures spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the use of these measures on the kinematics measured by IMUs. We show that: (a) SPARC and LDLJ-V are valid measures of smoothness only when used with velocity; (b) SPARC and LDLJ-V applied on translational velocity reconstructed from IMU is highly error prone due to drift caused by integration of reconstruction errors; (c) SPARC can be applied directly on rotational velocities measured by a gyroscope, but LDLJ-V can be error prone. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A). We evaluate the performance of these measures using simulated and experimental data. We demonstrate that the accuracy of LDLJ-A depends on the time profile of IMU orientation reconstruction error. Finally, we provide recommendations for how to appropriately apply these measures in practice under different scenarios, and highlight various factors to be aware of when performing smoothness analysis using IMU data.
Copyright © 2021 Melendez-Calderon, Shirota and Balasubramanian.

Entities:  

Keywords:  SPARC; assessment; inertial measurement units; jerk; movement kinematics; movement smoothness

Year:  2021        PMID: 33520949      PMCID: PMC7841375          DOI: 10.3389/fbioe.2020.558771

Source DB:  PubMed          Journal:  Front Bioeng Biotechnol        ISSN: 2296-4185


  5 in total

1.  Detection of Horse Locomotion Modifications Due to Training with Inertial Measurement Units: A Proof-of-Concept.

Authors:  Benoît Pasquiet; Sophie Biau; Quentin Trébot; Jean-François Debril; François Durand; Laetitia Fradet
Journal:  Sensors (Basel)       Date:  2022-07-01       Impact factor: 3.847

2.  Motion Smoothness Metrics for Cannulation Skill Assessment: What Factors Matter?

Authors:  Simar Singh; Joe Bible; Zhanhe Liu; Ziyang Zhang; Ravikiran Singapogu
Journal:  Front Robot AI       Date:  2021-04-16

3.  Unsupervised IMU-based evaluation of at-home exercise programmes: a feasibility study.

Authors:  Dimitrios-Sokratis Komaris; Georgia Tarfali; Brendan O'Flynn; Salvatore Tedesco
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-02-19

4.  Movement Quality Parameters during Gait Assessed by a Single Accelerometer in Subjects with Osteoarthritis and Following Total Joint Arthroplasty.

Authors:  Jill Emmerzaal; Kristoff Corten; Rob van der Straaten; Liesbet De Baets; Sam Van Rossom; Annick Timmermans; Ilse Jonkers; Benedicte Vanwanseele
Journal:  Sensors (Basel)       Date:  2022-04-12       Impact factor: 3.847

5.  Smoothness of movement in idiopathic cervical dystonia.

Authors:  Antonio Caronni; Pietro Arcuri; Ilaria Carpinella; Alberto Marzegan; Tiziana Lencioni; Marina Ramella; Alessandro Crippa; Denise Anastasi; Marco Rabuffetti; Maurizio Ferrarin; Anna Castagna
Journal:  Sci Rep       Date:  2022-03-24       Impact factor: 4.996

  5 in total

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