Novel Force Measurement System for Soft Tissue Balance in Total Knee Arthroplasty Based on Flexible Pressure Sensor Arrays

Wang, Fengxia; Wu, Zhiyong; Lin, Qihang; Chen, Tao; Kuang, Shaolong; Gan, Minfeng; Huang, Lixin; Sun, Lining

doi:10.1002/aisy.202100156

Cited by 5 publications

(2 citation statements)

References 46 publications

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“…Kuriyama et al omitted location from their sensor altogether and had a relatively small sensing area; however, they were able to have a good resolution (4.45 N–0.45 kg) [ 25 ]. Reference [ 26 ] had a maximum error of 2% for their load sensor; however, their sensor was only tested with loads below 1 kg (10 N), which was not the value of the load range during TKRs. Moreover, their sensor had an operation range between 0 and 5.1 kg (0–50 N), did not sense over the whole surface, and did not display the location.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements

Al-Nasser,

Noroozi,

Harvey

et al. 2024

Sensors

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Using tibial sensors in total knee replacements (TKRs) can enhance patient outcomes and reduce early revision surgeries, benefitting hospitals, the National Health Services (NHS), stakeholders, biomedical companies, surgeons, and patients. Having a sensor that is accurate, precise (over the whole surface), and includes a wide range of loads is important to the success of joint force tracking. This research aims to investigate the accuracy of a novel intraoperative load sensor for use in TKRs. This research used a self-developed load sensor and artificial intelligence (AI). The sensor is compatible with Zimmer’s Persona Knee System and adaptable to other knee systems. Accuracy and precision were assessed, comparing medial/lateral compartments inside/outside the sensing area and below/within the training load range. Five points were tested on both sides (medial and lateral), inside and outside of the sensing region, and with a range of loads. The average accuracy of the sensor was 83.41% and 84.63% for the load and location predictions, respectively. The highest accuracy, 99.20%, was recorded from inside the sensing area within the training load values, suggesting that expanding the training load range could enhance overall accuracy. The main outcomes were that (1) the load and location predictions were similar in accuracy and precision (p > 0.05) in both compartments, (2) the accuracy and precision of both predictions inside versus outside of the triangular sensing area were comparable (p > 0.05), and (3) there was a significant difference in the accuracy of load and location predictions (p < 0.05) when the load applied was below the training loading range. The intraoperative load sensor demonstrated good accuracy and precision over the whole surface and over a wide range of load values. Minor improvements to the software could greatly improve the results of the sensor. Having a reliable and robust sensor could greatly improve advancements in all joint surgeries.

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Section: Discussionmentioning

confidence: 99%

Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements

Al-Nasser,

Noroozi,

Harvey

et al. 2024

Sensors

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“…As an important alternative, hydrogel electronic skin, as an emerging and promising human-machine interface, is endowed with sensibility [7,8], flexibility [9], stretchability [10], comfortability [11,12], biocompatibility [13] and scalability [14]. Therefore, hydrogel electronic skin enables people to seamlessly connect with electronic devices to achieve unique human-machine interaction and shows broad application prospects in future health monitoring [15], personal electronic equipment [16], intelligent robots [17,18], wearable electronics [8,19], tissue engineering [20,21] and rehabilitation medicine [22,23].…”

Section: Introductionmentioning

confidence: 99%

Skin-Inspired Ultra-Tough Supramolecular Multifunctional Hydrogel Electronic Skin for Human–Machine Interaction

Chen

Liang

et al. 2023

Nano-Micro Lett.

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Multifunctional supramolecular ultra-tough bionic e-skin with unique durability for human–machine interaction in complex scenarios still remains challenging. Herein, we develop a skin-inspired ultra-tough e-skin with tunable mechanical properties by a physical cross-linking salting-freezing-thawing method. The gelling agent (β-Glycerophosphate sodium: Gp) induces the aggregation and binding of PVA molecular chains and thereby toughens them (stress up to 5.79 MPa, toughness up to 13.96 MJ m−3). Notably, due to molecular self-assembly, hydrogels can be fully recycled and reprocessed by direct heating (100 °C for a few seconds), and the tensile strength can still be maintained at about 100% after six recoveries. The hydrogel integrates transparency (> 60%), super toughness (up to 13.96 MJ m−3, bearing 1500 times of its own tensile weight), good antibacterial properties (E. coli and S. aureus), UV protection (Filtration: 80%–90%), high electrical conductivity (4.72 S m−1), anti-swelling and recyclability. The hydrogel can not only monitor daily physiological activities, but also be used for complex activities underwater and message encryption/decryption. We also used it to create a complete finger joint rehabilitation system with an interactive interface that dynamically presents the user’s health status. Our multifunctional electronic skin will have a profound impact on the future of new rehabilitation medical, human–machine interaction, VR/AR and the metaverse fields.

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A flexible pressure sensor based on electrospun fiber for gait monitoring in football training

Yan

2023

AIP Advances

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After football players receive high-intensity training, they often have muscle injuries. The development of a stretchable wearable sport sensor with high sensing performance will effectively solve this problem. In this work, we develop a flexible and stretchable pressure sensor based on graphene/ESTANE TPU nanofiber electrodes and the [C2OHMIM]Cl/ESTANE TPU nanofiber electrolyte. Owing to the microporous structure of electrospun film, the pressure sensor has the advantages of good air permeability and skin compatibility. The working mechanism of the pressure sensor is based on the supercapacitance sensing mechanism, which brings a wide detection range, high repeatability, high sensitivity, and fast response. Besides, the sensor installed at the knee can perform gait analysis, such as walking and running with the ball, in football. Furthermore, the sensor array developed can monitor the pressure distribution at the knee in football in real time. This research will promote the application of intelligent sports equipment in football training.

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Novel Force Measurement System for Soft Tissue Balance in Total Knee Arthroplasty Based on Flexible Pressure Sensor Arrays

Cited by 5 publications

References 46 publications

Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements

Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements

Skin-Inspired Ultra-Tough Supramolecular Multifunctional Hydrogel Electronic Skin for Human–Machine Interaction

A flexible pressure sensor based on electrospun fiber for gait monitoring in football training

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