Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Classification of mild and severe adolescent idiopathic scoliosis (AIS) from healthy subjects via a supervised learning model based on electromyogram and ground reaction force data during gait

Sikidar Arnab, Vidyasagar Koyyana Eshwar Chandra, Gupta Manish, Garg Bhavuk, Kalyanasundaram Dinesh

Biocybernetics and Biomedical Engineering

2022

Vol. 42, no. 3

870--887

At early stages, adolescent idiopathic scoliosis (AIS) is quite hard to be distinguished from healthy (HC) subjects by the naked eye. AIS demands multiple corrective surgeries when detected later, thereby causing significant physical and psychological trauma as no mathematical models exist for the classification of mild AIS (MS) (20° < Cobb’s angle < 40°) from HC, we propose a k-nearest neighbour (kNN) method based model. In this work, we collected both the EMG and GRF data from nine severe AIS (SS), three MS and four female HC during gait. Delayed muscle activation in Erector spinatus Iliocostalis, Gluteus Medius and Gastrocnemius lateralis was observed in SS compared to HC. However, no such distinction was noticed between MS and HC motivating for a mathematical model. Eighteen time-domain and nine frequency-domain features were computed from the EMG data of 14 lower extremity muscles, while five time-domain features were calculated from GRF data during gait. Out of all the features computed for each subject, the principal component analysis (PCA) yielded 15 principal components that coupled both time and frequency domains (TFD). Further, the kNN model classified SS, MS and HC from each other by these 15 TFD features. The model was trained and validated using 32 and 21 EMG and GRF data datasets during gait, respectively. The classification and validation accuracy of 90.6% and 85.7% were obtained among SS, MS and HC. The proposed model is capable of early detection of AIS and can be used by medical professionals to plan treatments and corrective measures.

A cadaveric study on the rate of strain-dependent behaviour of human anterior cruciate ligament

Marieswaran M., Sikidar Arnab, Rana Abhishek, Singh Dilpreet, Mansoori Nasim, Lalwani Sanjeev, Kalyanasundaram Dinesh

Acta of Bioengineering and Biomechanics

2021

Vol. 23, no. 1

45--57

Purpose: Failure of anterior cruciate ligament often occurs in young sports personnel hampering their career. Such ACL ruptures are quite prevalent in sports such as soccer during dynamic loading which occurs at more than one rate of loading. In this work, a structural constitutive equation has been used to predict the forces acting on ACL for different rates of loading. Methods: Ligaments with distal femur and proximal tibia were subjected to tensile loading to avoid crushing of tissue ends and slipping at higher rates of strain. Custom designed cylindrical grippers were fabricated to clamp the distal femur and proximal tibial bony sections. To estimate parameters for the model, eighteen fresh cadaveric femur-ACL-tibia complex (FATC) samples were experimented on by pure tensile loading at three orders of rates of strain viz., 0.003, 0.03, and 0.3 s–1. The experimental force-elongation data was used to obtain parameters for De-Vita and Slaughter’s equation. The model was validated with additional tensile experiments. Results: Statistical analysis demonstrated failure stress, Young’s modulus and volumetric strain energy to vary significantly as a function of rate of strain. Midsection failure was observed only in samples tested at 0.03 s–1. Femoral or tibial insertion failure were observed in all other experiments irrespective of rate of strain. Conclusion: Human FATC samples were tensile tested to failure at three rates of strain using custom-designed cylindrical grippers. A structural model was used to model the data for the ACL behaviour in the linear region of loading to predict ligament behaviour during dynamic activities in live subjects.