Non-invasive Electroarthrography Measures Load-Induced Cartilage Streaming Potentials via Electrodes Placed on Skin Surrounding an Articular Joint

Machine learning-based bioimpedance assessment of knee osteoarthritis severity

This study proposes a multiclass model to classify the severity of knee osteoarthritis (KOA) using bioimpedance measurements. The experimental setup considered three types of measurements using eight electrodes: global impedance with adjacent pattern, global impedance with opposite pattern, and direct impedance measurement, which were taken using an electronic device proposed by authors and based on the Analog Devices AD5933 impedance converter. The study comprised 37 participants, 25 with healthy knees and 13 with three different degrees of KOA. All participants performed 20 repetitions of each of the following five tasks: (i) sitting with the knee bent, (ii) sitting with the knee extended, (iii) sitting and performing successive extensions and flexions of the knee, (iv) standing, and (v) walking. Data from the 15 experimental setups (3 types of measurements×5 exercises) were used to train a multiclass random forest. The training and validation cycle was repeated 100 times using random undersampling. At each of the 100 cycles, 80% of the data were used for training and the rest for testing. The results showed that the proposed approach achieved average sensitivities and specificities of 100% for the four KOA severity grades in the extension, cyclic, and gait tasks. This suggests that the proposed method can serve as a screening tool to determine which individuals should undergo x-rays or magnetic resonance imaging for further evaluation of KOA.

A new look at osteoarthritis: Threshold potentials and an analogy to hypocalcemia

Cartilage is a tissue that consist of very few cells embedded in a highly negatively charged extracellular matrix (ECM). This tissue is dealing with several electrical potentials which have been shown to control the production of ECM. Cartilage is present at joints and is constantly prone to degradation. Failing to repair the damage will result in the occurrence of osteoarthritis (OA). This perspective aims to link biophysical insights with biomolecular research in order to provide an alternative view on the possible causes of OA. Firstly, we hypothesize the existence of a threshold potential, which should be reached in order to initiate repair but if not met, unrepaired damage will evolve to OA. Measurements of the magnitude of this threshold electrical potential would be a helpful diagnostic tool. Secondly, since electrical potential alterations can induce chondrocytes to synthesize ECM, a cellular sensor must be present. We here propose an analogy to the hypocalcemia ‘unshielding’ situation to comprehend electrical potential generation and explore possible sensing mechanisms translating the electrical message into cellular responses. A better understanding of the cellular voltage sensors and down-stream signalling mechanisms may lead to the development of novel treatments for cartilage regeneration.