Novel approach to dynamic knee laxity measurement using capacitive strain gauges

Zens, Martin; Niemeyer, Philipp; Bernstein, Anke; Feucht, Matthias J.; Kühle, Jan; Südkamp, Norbert P.; Woias, Peter; Mayr, H. O.

doi:10.1007/s00167-015-3771-9

Cited by 12 publications

(18 citation statements)

References 26 publications

(34 reference statements)

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“…To obtain information about both static and dynamic laxities and taking into account the degrees of freedom of the knee joint and the stressing tests, the “smart” brace was based on a knee brace equipped with three stretch sensors and two wearable IMUs, as shown in Figure 1 . Starting from the analysis of literature [ 23 , 24 ], the insertions of the stretch sensors and the positions of the IMUs was defined according to the hypotheses of acquiring both rotational and displacement information during the Lachman, drawer, and pivot shift tests. The block diagram of the smart brace and the data collection system is shown in Figure 2 .…”

Section: Smart Brace Designmentioning

confidence: 99%

“…When relaxed, the sensors have a nominal resistance of 1400 Ω. The stretch sensors were securely sewn to the brace and were positioned in order to recognize the key components of knee laxity with the minimum number of strain sensors and according to a recent study [ 23 ]. Referring to Figure 3 , Stretch Sensor 1 addresses medial-lateral translation, Stretch Sensor 2 the internal-external rotation, and Stretch Sensor 3 the anterior and posterior translation.…”

Section: Smart Brace Designmentioning

confidence: 99%

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Smart Brace for Static and Dynamic Knee Laxity Measurement

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et al. 2022

Sensors

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Every year in Europe more than 500 thousand injuries that involve the anterior cruciate ligament (ACL) are diagnosed. The ACL is one of the main restraints within the human knee, focused on stabilizing the joint and controlling the relative movement between the tibia and femur under mechanical stress (i.e., laxity). Ligament laxity measurement is clinically valuable for diagnosing ACL injury and comparing possible outcomes of surgical procedures. In general, knee laxity assessment is manually performed and provides information to clinicians which is mainly subjective. Only recently quantitative assessment of knee laxity through instrumental approaches has been introduced and become a fundamental asset in clinical practice. However, the current solutions provide only partial information about either static or dynamic laxity. To support a multiparametric approach using a single device, an innovative smart knee brace for knee laxity evaluation was developed. Equipped with stretchable strain sensors and inertial measurement units (IMUs), the wearable system was designed to provide quantitative information concerning the drawer, Lachman, and pivot shift tests. We specifically characterized IMUs by using a reference sensor. Applying the Bland–Altman method, the limit of agreement was found to be less than 0.06 m/s2 for the accelerometer, 0.06 rad/s for the gyroscope and 0.08 μT for the magnetometer. By using an appropriate characterizing setup, the average gauge factor of the three strain sensors was 2.169. Finally, we realized a pilot study to compare the outcomes with a marker-based optoelectronic stereophotogrammetric system to verify the validity of the designed system. The preliminary findings for the capability of the system to discriminate possible ACL lesions are encouraging; in fact, the smart brace could be an effective support for an objective and quantitative diagnosis of ACL tear by supporting the simultaneous assessment of both rotational and translational laxity. To obtain reliable information about the real effectiveness of the system, further clinical validation is necessary.

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Section: Smart Brace Designmentioning

confidence: 99%

Section: Smart Brace Designmentioning

confidence: 99%

Smart Brace for Static and Dynamic Knee Laxity Measurement

Bellitti

Borghetti

Lopomo

et al. 2022

Sensors

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“…Nevertheless, capacitive sensors have been successfully made using conductive silicone for measuring pressure and shear stresses simultaneously at the stump-socket interface of lower-limb amputees (Laszczak et al, 2015(Laszczak et al, , 2016. Conductive fabrics have been used by Andreas Tairych (2017) to create multiple capacitive stretch sensors requiring only one channel for measurement; Atalay et al (2017) used conductive stretch fabric as the electrodes sandwiching a silicone dielectric for a customizable strain sensor for human motion tracking; Kappel et al (2012) developed a strain sensor based on a dielectric electro-active polymer (DEAP) that acts as an elastic capacitive material, strainable in one direction for measuring in-shoe navicular drop during gait; Zens et al (2015) used a complex layering of non-conductive PDMS and conductive PDMS made using carbon black particles as a novel approach to dynamic knee laxity measurement (Fassler and Majidi, 2013;Zens et al, 2015) produced soft-matter capacitors and inductors from microchannels of liquid-phase gallium-indium-tin alloy (galinstan) embedded in Ecoflex 00-30.…”

Section: Capacitive Strain Sensingmentioning

confidence: 99%

A Deep Learning Approach to Non-linearity in Wearable Stretch Sensors

et al. 2019

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There is a growing need for flexible stretch sensors to monitor real time stress and strain in wearable technology. However, developing stretch sensors with linear responses is difficult due to viscoelastic and strain rate dependent effects. Instead of trying to engineer the perfect linear sensor we take a deep learning approach which can cope with non-linearity and yet still deliver reliable results. We present a general method for calibrating highly hysteretic resistive stretch sensors. We show results for textile and elastomeric stretch sensors however we believe the method is directly applicable to any physical choice of sensor material and fabrication, and easily adaptable to other sensing methods, such as those based on capacitance. Our algorithm does not require any a priori knowledge of the physical attributes or geometry of the sensor to be calibrated, which is a key advantage as stretchable sensors are generally applicable to highly complex geometries with integrated electronics requiring bespoke manufacture. The method involves three-stages. The first stage requires a calibration step in which the strain of the sensor material is measured using a webcam while the electrical response is measured via a set of arduino-based electronics. During this data collection stage, the strain is applied manually by pulling the sensor over a range of strains and strain rates corresponding to the realistic in-use strain and strain rates. The correlated data between electrical resistance and measured strain and strain rate are stored. In the second stage the data is passed to a Long Short Term Memory Neural Network (LSTM) which is trained using part of the data set. The ability of the LSTM to predict the strain state given a stream of unseen electrical resistance data is then assessed and the maximum errors established. In the third stage the sensor is removed from the webcam calibration set-up and embedded in the wearable application where the live stream of electrical resistance is the only measure of strain-this corresponds to the proposed use case. Highly accurate stretch topology mapping is achieved for the three commercially available flexible sensor materials tested.

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“…Resistive sensors exhibit high sensitivity, but they show large hysteresis and non-linear electromechanical responses, whereas the capacitive type exhibits small hysteresis, and high repeatability and stretchability [7][8][9][10]. The capacitive approach has been successfully proven on the research level, and a sensor was characterized for the ACL in [4]: The measurements obtained with the methods currently used in the clinic are not repeatable for the diagnosis of knee laxity [11][12][13] and are strongly influenced by the experience of the physician [14][15][16][17]. In [4], the sensor applied over the knee translates the length changes that the skin exhibits during a bone-to-bone displacement into a capacitance variation.…”

Section: Introductionmentioning

confidence: 99%

Batch Fabrication of a Polydimethylsiloxane Based Stretchable Capacitive Strain Gauge Sensor for Orthopedics

et al. 2022

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Polymer-based capacitive strain gauges are a novel and promising concept for measuring large displacements and strains in various applications. These novel sensors allow for high strain, well above the maximum values achieved with state-of-the-art strain gauges (Typ. 1%). In recent years, a lot of interest in this technology has existed in orthopedics, where the sensors have been used to measure knee laxity caused by a tear of the anterior cruciate ligament (ACL), and for other ligament injuries. The validation of this technology in the field has a very low level of maturity, as no fast, reproducible, and reliable manufacturing process which allows mass production of sensors with low cost exists. For this reason, in this paper, a new approach for the fabrication of polymer-based capacitive strain gauges is proposed, using polydimethylsiloxane (PDMS) as base material. It allows (1) the fast manufacturing of sensor batches with reproducible geometry, (2) includes a fabrication step for embedding rigid electrical contacts on the sensors, and (3) is designed to produce sensor batches in which the size, the number, and the position of the sensors can be adapted to the patient’s anatomy. In the paper, the process repeatability and the robustness of the design are successfully proven. After 1000 large-strain elongation cycles, in the form of accelerated testing caused much higher strains than in the above-mentioned clinical scenario, the sensor’s electrical contacts remained in place and the functionalities were unaltered. Moreover, the prototype of a patient customizable patch, embedding multiple sensors, was produced.

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Novel approach to dynamic knee laxity measurement using capacitive strain gauges

Abstract: PDMS strain gauges are capable of measuring bone-to-bone displacements on the skin. We present an experimental in vitro study using an artificial knee test rig to simulate knee joint laxities and display the feasibility of our novel measurement approach.

Cited by 12 publications

References 26 publications

Smart Brace for Static and Dynamic Knee Laxity Measurement

Smart Brace for Static and Dynamic Knee Laxity Measurement

A Deep Learning Approach to Non-linearity in Wearable Stretch Sensors

Batch Fabrication of a Polydimethylsiloxane Based Stretchable Capacitive Strain Gauge Sensor for Orthopedics

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