Design and test of a MEMS strain-sensing device for monitoring artificial knee implants

Hasenkamp, Willyan; Thevenaz, Nicolas; Villard, J.; Bertsch, Arnaud; Arami, Arash; Aminian, Kamiar; Terrier, Alexandre; Renaud, Philippe

doi:10.1007/s10544-013-9770-z

Cited by 14 publications

(20 citation statements)

References 17 publications

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“…the remote powering, wireless communication, analogue front-end, force sensors, and packaging are in progress [18], [26]- [28]. Considering the smaller size, lower power consumption and the silicon technology compatibility of the proposed solution, it would promote the fabrication of a smart capsule, including also the necessary electronics, to be integrated into the polyethylene inserts of the commercially-available knee prostheses of different types for in-vivo post-operative monitoring of the patients.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Locally Linear Neuro-Fuzzy Estimate of the Prosthetic Knee Angle and Its Validation in a Robotic Simulator

2015

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Abstract-In this work we presented a low-power magnetic measurement system based on only two Hall-effect elements and a permanent magnet integrated into a smart knee prosthesis to accurately measure knee flexion-extension. The smart prosthesis was affixed in a robotic knee simulator that provides the squat movements, and also replicates different patterns of recorded gait from subjects. The squat movements were used to build linear and locally linear neuro-fuzzy estimators to translate the magnetic measurements into knee flexion angle. The simulated gait patterns then used to validate the models. The locally linear neuro-fuzzy estimator showed a clear benefit comparing to the linear regression models, by sequentially splitting the measurement space into subregions and find local fuzzy models for each region. The obtained RMS errors on test data were lower than 1.3° for the neuro-fuzzy estimates representing smaller than 3% of range of rotation. The result was compared with the estimates from a previously-designed configuration of three 2-D anisotropic magnetoresistive (AMR) sensors which tested in mentioned setup. We showed that by using the neurofuzzy model for two Hall-effect elements, similar performance to the AMR-based estimator can be obtained while the power consumption can be reduced more than three folds.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Locally Linear Neuro-Fuzzy Estimate of the Prosthetic Knee Angle and Its Validation in a Robotic Simulator

2015

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“…Although previous attempts have been made at designing implantable monitoring systems [5]- [8], many are only usable during the surgical process or require modifications to the existing implant architecture [9]. In this paper, amorphous magnetostrictive ribbons were integrated into UHMWPE as [14].…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Measurement of Stress Levels in Knee Implants Using a Magnetic-Based Detection Method

2016

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A knee replacement surgery (arthroplasty) has become prevalent worldwide and has a high success rate over the short to medium term. In some cases, especially over the longer term, implant degradation can develop due to the deterioration of the ultra-high molecular weight polyethylene (UHMWPE) tibial insert. Unfortunately, there are no satisfactory techniques currently available for assessing implant integrity and predicting failure. This paper describes a possible solution to this problem by using a non-invasive, electromagnetic method for monitoring implant integrity. This approach utilizes the magnetoelastic property of amorphous ribbon, which when stressed causes an inductance change in a nearby magnetizing winding. Amorphous ribbons encased in UHMWPE disks, to simulate a knee insert, were subjected to varying tensile stresses under an applied ac magnetic field. A correlation between total circuit impedance and applied stress was observed. The results obtained demonstrate that the proposed sensor has sufficient sensitivity for measuring typical stress levels associated with the axial forces in tibial inserts.

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“…When force sensors are assembled in the insert, whether magnetic [ 11 ] or piezoresistive [ 12 ], strong nonlinearities are observed due to the viscoelastic behavior of the polyethylene. Sensors assembled directly onto the UHMWPE are typically subject to creep and hysteresis.…”

Section: Introductionmentioning

confidence: 99%

“…Sensors assembled directly onto the UHMWPE are typically subject to creep and hysteresis. The sensor described in [ 12 ] uses similar technology to the one presented here and is subject to a high creep behavior that limits its usability. This particular sensor measured the transverse strain due to force in the condyle and is directly glued in a cut insert.…”

Section: Introductionmentioning

confidence: 99%

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Enclosed Electronic System for Force Measurements in Knee Implants

Forchelet

Simoncini

Arami

et al. 2014

Sensors

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Total knee arthroplasty is a widely performed surgical technique. Soft tissue force balancing during the operation relies strongly on the experience of the surgeon in equilibrating tension in the collateral ligaments. Little information on the forces in the implanted prosthesis is available during surgery and post-operative treatment. This paper presents the design, fabrication and testing of an instrumented insert performing force measurements in a knee prosthesis. The insert contains a closed structure composed of printed circuit boards and incorporates a microfabricated polyimide thin-film piezoresistive strain sensor for each condylar compartment. The sensor is tested in a mechanical knee simulator that mimics in-vivo conditions. For characterization purposes, static and dynamic load patterns are applied to the instrumented insert. Results show that the sensors are able to measure forces up to 1.5 times body weight with a sensitivity fitting the requirements for the proposed use. Dynamic testing of the insert shows a good tracking of slow and fast changing forces in the knee prosthesis by the sensors.

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Design and test of a MEMS strain-sensing device for monitoring artificial knee implants

Cited by 14 publications

References 17 publications

Locally Linear Neuro-Fuzzy Estimate of the Prosthetic Knee Angle and Its Validation in a Robotic Simulator

Locally Linear Neuro-Fuzzy Estimate of the Prosthetic Knee Angle and Its Validation in a Robotic Simulator

Non-Invasive Measurement of Stress Levels in Knee Implants Using a Magnetic-Based Detection Method

Enclosed Electronic System for Force Measurements in Knee Implants

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