Literature DB >> 27833057

25 years of lower limb joint kinematics by using inertial and magnetic sensors: A review of methodological approaches.

Pietro Picerno1.   

Abstract

Joint kinematics is typically limited to the laboratory environment, and the restricted volume of capture may vitiate the execution of the motor tasks under analysis. Conversely, clinicians often require the analysis of motor acts in non-standard environments and for long periods of time, such as in ambulatory settings or during daily life activities. The miniaturisation of motion sensors and electronic components, generally associated with wireless communications technology, has opened up a new perspective: movement analysis can be carried out outside the laboratory and at a relatively lower cost. Wearable inertial measurement units (embedding 3D accelerometers and gyroscopes), eventually associated with magnetometers, allow one to estimate segment orientation and joint angular kinematics by exploiting the laws governing the motion of a rotating rigid body. The first study which formalised the problem of the estimate of joint kinematics using inertial sensors dates back to 1990. Since then, a variety of methods have been presented over the past 25 years for the estimate of 2D and 3D joint kinematics by using inertial and magnetic sensors. The aim of the present review is to describe these approaches from a purely methodological point of view to provide the reader with a comprehensive understanding of all the instrumental, computational and methodological issues related to the estimate of joint kinematics when using such sensor technology. Copyright Â
© 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Accelerometers; Gyroscopes; Joint kinematics; Methodological approach; Wearable inertial sensors

Mesh:

Year:  2016        PMID: 27833057     DOI: 10.1016/j.gaitpost.2016.11.008

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  41 in total

1.  An engineer's perspective on the mechanisms and applications of wearable inertial sensors.

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2.  Functional calibration does not improve the concurrent validity of magneto-inertial wearable sensor-based thorax and lumbar angle measurements when compared with retro-reflective motion capture.

Authors:  Daniel S Cottam; Amity C Campbell; Paul C Davey; Peter Kent; Bruce C Elliott; Jacqueline A Alderson
Journal:  Med Biol Eng Comput       Date:  2021-09-16       Impact factor: 2.602

3.  Recent Machine Learning Progress in Lower Limb Running Biomechanics With Wearable Technology: A Systematic Review.

Authors:  Liangliang Xiang; Alan Wang; Yaodong Gu; Liang Zhao; Vickie Shim; Justin Fernandez
Journal:  Front Neurorobot       Date:  2022-06-02       Impact factor: 3.493

Review 4.  The Evolution of Personalized Behavioral Intervention Technology: Will It Change How We Measure or Deliver Rehabilitation?

Authors:  Bruce H Dobkin; Andrew K Dorsch
Journal:  Stroke       Date:  2017-07-05       Impact factor: 7.914

5.  Estimation of 3D Body Center of Mass Acceleration and Instantaneous Velocity from a Wearable Inertial Sensor Network in Transfemoral Amputee Gait: A Case Study.

Authors:  Emeline Simonetti; Elena Bergamini; Giuseppe Vannozzi; Joseph Bascou; Hélène Pillet
Journal:  Sensors (Basel)       Date:  2021-04-30       Impact factor: 3.576

6.  Barriers to the Adoption of Wearable Sensors in the Workplace: A Survey of Occupational Safety and Health Professionals.

Authors:  Mark C Schall; Richard F Sesek; Lora A Cavuoto
Journal:  Hum Factors       Date:  2018-01-10       Impact factor: 3.598

7.  A New Proxy Measurement Algorithm with Application to the Estimation of Vertical Ground Reaction Forces Using Wearable Sensors.

Authors:  Yuzhu Guo; Fabio Storm; Yifan Zhao; Stephen A Billings; Aleksandar Pavic; Claudia Mazzà; Ling-Zhong Guo
Journal:  Sensors (Basel)       Date:  2017-09-22       Impact factor: 3.576

8.  EquiMoves: A Wireless Networked Inertial Measurement System for Objective Examination of Horse Gait.

Authors:  Stephan Bosch; Filipe Serra Bragança; Mihai Marin-Perianu; Raluca Marin-Perianu; Berend Jan van der Zwaag; John Voskamp; Willem Back; René van Weeren; Paul Havinga
Journal:  Sensors (Basel)       Date:  2018-03-13       Impact factor: 3.576

9.  A public dataset of running biomechanics and the effects of running speed on lower extremity kinematics and kinetics.

Authors:  Reginaldo K Fukuchi; Claudiane A Fukuchi; Marcos Duarte
Journal:  PeerJ       Date:  2017-05-09       Impact factor: 2.984

10.  Inertial Measurement Units for Clinical Movement Analysis: Reliability and Concurrent Validity.

Authors:  Mohammad Al-Amri; Kevin Nicholas; Kate Button; Valerie Sparkes; Liba Sheeran; Jennifer L Davies
Journal:  Sensors (Basel)       Date:  2018-02-28       Impact factor: 3.576

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