Design and Simulation of a Passive Absorber to Reduce Measured Postural Tremor Signal.


Journal

Journal of biomechanical engineering
ISSN: 1528-8951
Titre abrégé: J Biomech Eng
Pays: United States
ID NLM: 7909584

Informations de publication

Date de publication:
01 09 2022
Historique:
received: 04 01 2021
pubmed: 4 3 2022
medline: 2 4 2022
entrez: 3 3 2022
Statut: ppublish

Résumé

Tremor is a semirhythmic oscillatory movement of a body part caused by alternating simultaneous contractions of an antagonistic muscle group. Medical and surgical treatments used to reduce the symptoms of involuntary tremor can cause negative side effects. This study examined the ability of passive vibration absorbers in reducing the amplitude of postural tremor (PT). Inertial measurement unit (IMU) was used to record PT signals at the forearm and hand of a patient. IMU signal was used to excite an upper limb modeled to represent the flexion-extension vibrational motion at the joints. Equations of motion were solved numerically to obtain a response that fits the measured tremor signal. Passive tuned mass damper (TMD) was modeled as a cantilever beam and a screw placed along its length, at a position reflecting its operational frequency. Natural frequency of the TMD was derived for different mass positions and validated numerically and experimentally. Modal damping ratio of the TMD, for each mass position, was also estimated. Mass position and damping coefficient of the TMD were optimized depending on the minimization in the power spectral density (PSD) of angular displacement amplitude at the wrist joint. Optimized three-TMD system of 28.64 g total effective mass with the estimated modal damping ratio reduced 83.1% of the PSD of the angular displacement amplitude. This study showed the performance ability of a lightweight passive absorber in controlling the involuntary tremor of a system excited by the measured tremor signal of a patient.

Identifiants

pubmed: 35237796
pii: 1137927
doi: 10.1115/1.4053998
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2022 by ASME.

Auteurs

Sarah Gebai (S)

Lab Navier, Univ Gustave Eiffel, ENPC, CNRS, Marne-la-Vallée F-77447, France; Structure Dynamics and Materials and LIBRA Research Groups, Department of Mechanical Engineering, International University of Beirut, Mazraa, Beirut 146404, Lebanon.

Gwendal Cumunel (G)

Lab Navier, Univ Gustave Eiffel, ENPC, CNRS, Marne-la-Vallée F-77447, France.

Mohammad Hammoud (M)

Structure Dynamics and Materials and LIBRA Research Groups, Department of Mechanical Engineering, International University of Beirut, Mazraa, Beirut 146404, Lebanon; School of Engineering, Lebanese International University LIU,Bekaa 146404, Lebanon.

Gilles Foret (G)

Lab Navier, Univ Gustave Eiffel, ENPC, CNRS, Marne-la-Vallée F-77447, France.

Emmanuel Roze (E)

Faculté de Médecine de Sorbonne Université, UMR S 1127, Inserm U 1127, UMR CNRS 7225, Institut du Cerveau et de la Moëlle épinière, Paris F-75013, France; Département de Neurologie, Hôpital Pitié-Salpêtrière, AP-HP, Paris F-75651, France.

Elodie Hainque (E)

Faculté de Médecine de Sorbonne Université, UMR S 1127, Inserm U 1127, UMR CNRS 7225, Institut du Cerveau et de la Moëlle épinière, Paris F-75013, France; Département de Neurologie, Hôpital Pitié-Salpêtrière, AP-HP, Paris F-75651, France.

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Classifications MeSH