Literature DB >> 33430138

Prediction of Motion Intentions as a Novel Method of Upper Limb Rehabilitation Support.

Bogusz Lewandowski1, Sławomir Wudarczyk1, Przemysław Sperzyński1, Jacek Bałchanowski1.   

Abstract

This article is devoted to the novel method of upper limb rehabilitation support using a dedicated mechatronic system. The mechatronic rehabilitation system's main advantages are the repeatability of the process and the ability to measure key features and the progress of the therapy. In addition, the assisted therapy standard is the same for each patient. The new method proposed in this article is based on the prediction of the patient's intentions, understood as the intentions to perform a movement that would be not normally possible due to the patient's limited motor functions. Determining those intentions is realized based on a comparative analysis of measured kinematic (range of motion, angular velocities, and accelerations) and dynamic parameter values, as well as external loads resulting from the interaction of patients. Appropriate procedures were implemented in the control system, for which verification was conducted via experiments. The aim of the research in the article was to examine whether it is possible to sense the movement intentions of a patient during exercises, using only measured load parameters and kinematic parameters of the movement. In this study, the construction of a mechatronic system prototype equipped with sensory grip to measure the external loads, control algorithms, and the description of experimental studies were presented. The experimental studies of the mechanism were aimed at the verification of the proper operation of the system and were not a clinical trial.

Entities:  

Keywords:  data acquisition; mechatronics; rehabilitation support; sensors

Mesh:

Year:  2021        PMID: 33430138      PMCID: PMC7827685          DOI: 10.3390/s21020410

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  14 in total

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3.  Upper limb muscle forces during a simple reach-to-grasp movement: a comparative study.

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4.  Overview of clinical trials with MIT-MANUS: a robot-aided neuro-rehabilitation facility.

Authors:  H I Krebs; N Hogan; B T Volpe; M L Aisen; L Edelstein; C Diels
Journal:  Technol Health Care       Date:  1999       Impact factor: 1.285

5.  The Present and Future of Robotic Technology in Rehabilitation.

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Journal:  Curr Phys Med Rehabil Rep       Date:  2016-11-19

6.  The Upper Limb Motion Deviation Index: A new comprehensive index of upper limb motion pathology.

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Journal:  Acta Bioeng Biomech       Date:  2017       Impact factor: 1.073

7.  Identification of Object Dynamics Using Hand Worn Motion and Force Sensors.

Authors:  Henk G Kortier; H Martin Schepers; Peter H Veltink
Journal:  Sensors (Basel)       Date:  2016-11-26       Impact factor: 3.576

8.  Three Dimensional Upper Limb Joint Kinetics of a Golf Swing with Measured Internal Grip Force.

Authors:  Hyeob Choi; Sukyung Park
Journal:  Sensors (Basel)       Date:  2020-06-30       Impact factor: 3.576

9.  A Tangible Solution for Hand Motion Tracking in Clinical Applications.

Authors:  Christina Salchow-Hömmen; Leonie Callies; Daniel Laidig; Markus Valtin; Thomas Schauer; Thomas Seel
Journal:  Sensors (Basel)       Date:  2019-01-08       Impact factor: 3.576

10.  Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation.

Authors:  Bor-Shing Lin; I-Jung Lee; Shu-Yu Yang; Yi-Chiang Lo; Junghsi Lee; Jean-Lon Chen
Journal:  Sensors (Basel)       Date:  2018-05-13       Impact factor: 3.847

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  1 in total

1.  Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson's Disease.

Authors:  Alfonso Maria Ponsiglione; Carlo Ricciardi; Francesco Amato; Mario Cesarelli; Giuseppe Cesarelli; Giovanni D'Addio
Journal:  Sensors (Basel)       Date:  2022-02-22       Impact factor: 3.576

  1 in total

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