Literature DB >> 25420266

Quantitative assessment of upper limb motion in neurorehabilitation utilizing inertial sensors.

Lu Bai, Matthew G Pepper, Yong Yan, Sarah K Spurgeon, Mohamed Sakel, Malcolm Phillips.   

Abstract

Two inertial sensor systems were developed for 3-D tracking of upper limb movement. One utilizes four sensors and a kinematic model to track the positions of all four upper limb segments/joints and the other uses one sensor and a dead reckoning algorithm to track a single upper limb segment/joint. Initial evaluation indicates that the system using the kinematic model is able to track orientation to 1 degree and position to within 0.1 cm over a distance of 10 cm. The dead reckoning system combined with the "zero velocity update" correction can reduce errors introduced through double integration of errors in the estimate in offsets of the acceleration from several meters to 0.8% of the total movement distance. Preliminary evaluation of the systems has been carried out on ten healthy volunteers and the kinematic system has also been evaluated on one patient undergoing neurorehabilitation over a period of ten weeks. The initial evaluation of the two systems also shows that they can monitor dynamic information of joint rotation and position and assess rehabilitation process in an objective way, providing additional clinical insight into the rehabilitation process.

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Year:  2014        PMID: 25420266     DOI: 10.1109/TNSRE.2014.2369740

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  6 in total

1.  Measuring upper limb function in children with hemiparesis with 3D inertial sensors.

Authors:  Christopher J Newman; Roselyn Bruchez; Sylvie Roches; Marine Jequier Gygax; Cyntia Duc; Farzin Dadashi; Fabien Massé; Kamiar Aminian
Journal:  Childs Nerv Syst       Date:  2017-08-25       Impact factor: 1.475

2.  Validity and reliability of inertial sensors for elbow and wrist range of motion assessment.

Authors:  Vanina Costa; Óscar Ramírez; Abraham Otero; Daniel Muñoz-García; Sandra Uribarri; Rafael Raya
Journal:  PeerJ       Date:  2020-08-11       Impact factor: 2.984

Review 3.  Inertial Sensor Technology for Elite Swimming Performance Analysis: A Systematic Review.

Authors:  Robert Mooney; Gavin Corley; Alan Godfrey; Leo R Quinlan; Gearóid ÓLaighin
Journal:  Sensors (Basel)       Date:  2015-12-25       Impact factor: 3.576

4.  A Pilot Study of Individual Muscle Force Prediction during Elbow Flexion and Extension in the Neurorehabilitation Field.

Authors:  Jiateng Hou; Yingfei Sun; Lixin Sun; Bingyu Pan; Zhipei Huang; Jiankang Wu; Zhiqiang Zhang
Journal:  Sensors (Basel)       Date:  2016-11-29       Impact factor: 3.576

5.  Characterizing Human Box-Lifting Behavior Using Wearable Inertial Motion Sensors.

Authors:  Steven D Hlucny; Domen Novak
Journal:  Sensors (Basel)       Date:  2020-04-18       Impact factor: 3.576

6.  Wearable systems for shoulder kinematics assessment: a systematic review.

Authors:  Arianna Carnevale; Umile Giuseppe Longo; Emiliano Schena; Carlo Massaroni; Daniela Lo Presti; Alessandra Berton; Vincenzo Candela; Vincenzo Denaro
Journal:  BMC Musculoskelet Disord       Date:  2019-11-15       Impact factor: 2.362

  6 in total

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