On the development of a wireless motion capture sensor node for upper limb rehabilitation

Tsilomitrou, Ourania; Γκούντας, Κωνσταντίνος; Evangeliou, Nikolaos; Dermatas, Evangelos

doi:10.1109/codit.2019.8820559

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…The above combination of design requirements for a platform suitable to be deployed at large scale including etreatment is not met by existing solutions. Current state-ofthe-art researches like [13] and [14] limit their study to the upper and lower limbs respectively, with a device that is designed to examine one body part specifically. We design our sensor to fit any body part.…”

Section: Design Requirementsmentioning

confidence: 99%

Contactless Multi-Sensor Solution for E-Treatment of Musculoskeletal Disorders

et al. 2021

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This research has been supported by the NOMADe project of the EU Interreg Program France-Wallonie-Vlaanderen under grant agreement 4.7.360. We thank our colleagues in the NOMADe project and in particular Simoneau Emilie, Leteneur Sébastien and Gillet Christophe of the Polytechnic University (Valenciennes) for the constructive discussions and valuable inputs leading to adequate design requirements for the multi-sensor solution. We also appreciate the guidance from supportive physiotherapist Renaat Monteyne in the definition and carrying out of the validation.

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Section: Design Requirementsmentioning

confidence: 99%

Contactless Multi-Sensor Solution for E-Treatment of Musculoskeletal Disorders

et al. 2021

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“…The present work is an extension of our previous paper [29], where a custom-made sensor node was used for motion acquisition and 3D reconstruction of the upper limb segments movement. Here, the sensor fusion algorithm has been improved, in order to account for the relationship between the Euler angles' time rates of change and the angular velocity resolved in the body fixed frame, as is presented in [30].…”

Section: Motivation and Objectivesmentioning

confidence: 99%

“…The transformation from the raw gyroscope measurements with respect to the sensor body axis coordinate system to the fixed coordinate system is derived from the direction cosine matrix shown in Equation (4). This relation allowed to update the orientation of the upper limb link with time, improving also its accuracy, compared to the previous implementation [29], where we used the raw gyroscope measurements in the calculations. Using the raw measurements, we get the angular velocities with respect to the moving body frame and not the fixed 3-dimensional global frame that is defined.…”

Section: Sensor Fusion and Orientation Estimationmentioning

confidence: 99%

Wireless Motion Capture System for Upper Limb Rehabilitation

Tsilomitrou

Γκούντας

Evangeliou

et al. 2021

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This work is devoted to the presentation of a Wireless Sensor System implementation for upper limb rehabilitation to function as a complementary system for a patient’s progress supervision during rehabilitation exercises. A cost effective motion capture sensor node composed by a 9 Degrees-of-Freedom (DoF) Inertial Measurement Unit (IMU) is mounted on the patient’s upper limb segments and sends wirelessly the corresponding measured signals to a base station. The sensor orientation and the upper limb individual segments movement in 3-Dimensional (3D) space are derived by processing the sensors’ raw data. For the latter purpose, a biomechanical model which resembles that of a kinematic model of a robotic arm based on the Denavit-Hartenberg (DH) configuration is used to approximate in real time the upper limb movements. The joint angles of the upper limb model are estimated from the extracted sensor node’s orientation angles. The experimental results of a human performing common rehabilitation exercises using the proposed motion capture sensor node are compared with the ones using an off-the-shelf sensor. This comparison results to very low error rates with the root mean square error (RMSE) being about 0.02 m.

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On the development of a wireless motion capture sensor node for upper limb rehabilitation

Cited by 2 publications

References 16 publications

Contactless Multi-Sensor Solution for E-Treatment of Musculoskeletal Disorders

Contactless Multi-Sensor Solution for E-Treatment of Musculoskeletal Disorders

Wireless Motion Capture System for Upper Limb Rehabilitation

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