Faculty Publications

Now showing 1 - 3 of 3

Detection of Gait Abnormalities caused by Neurological Disorders
(Institute of Electrical and Electronics Engineers Inc., 2020) Goyal, D.; Jerripothula, K.; Mittal, A.
In this paper, we leverage gait to potentially detect some of the important neurological disorders, namely Parkinson's disease, Diplegia, Hemiplegia, and Huntington's Chorea. Persons with these neurological disorders often have a very abnormal gait, which motivates us to target gait for their potential detection. Some of the abnormalities involve the circumduction of legs, forward-bending, involuntary movements, etc. To detect such abnormalities in gait, we develop gait features from the key-points of the human pose, namely shoulders, elbows, hips, knees, ankles, etc. To evaluate the effectiveness of our gait features in detecting the abnormalities related to these diseases, we build a synthetic video dataset of persons mimicking the gait of persons with such disorders, considering the difficulty in finding a sufficient number of people with these disorders. We name it NeuroSynGait video dataset. Experiments demonstrated that our gait features were indeed successful in detecting these abnormalities. Â© 2020 IEEE.
Computational assessment on the impact of collagen fiber orientation in cartilages on healthy and arthritic knee kinetics/kinematics
(Elsevier Ltd, 2023) Raju, V.; Koorata, P.K.
Background: The inhomogeneous distribution of collagen fiber in cartilage can substantially influence the knee kinematics. This becomes vital for understanding the mechanical response of soft tissues, and cartilage deterioration including osteoarthritis (OA). Though the conventional computational models consider geometrical heterogeneity along with fiber reinforcements in the cartilage model as material heterogeneity, the influence of fiber orientation on knee kinetics and kinematics is not fully explored. This work examines how the collagen fiber orientation in the cartilage affects the healthy (intact knee) and arthritic knee response over multiple gait activities like running and walking. Methods: A 3D finite element knee joint model is used to compute the articular cartilage response during the gait cycle. A fiber-reinforced porous hyper elastic (FRPHE) material is used to model the soft tissue. A split-line pattern is used to implement the fiber orientation in femoral and tibial cartilage. Four distinct intact cartilage models and three OA models are simulated to assess the impact of the orientation of collagen fibers in a depth wise direction. The cartilage models with fibers oriented in parallel, perpendicular, and inclined to the articular surface are investigated for multiple knee kinematics and kinetics. Findings: The comparison of models with fiber orientation parallel to articulating surface for walking and running gait has the highest elastic stress and fluid pressure compared with inclined and perpendicular fiber-oriented models. Also, the maximum contact pressure is observed to be higher in the case of intact models during the walking cycle than for OA models. In contrast, the maximum contact pressure is higher during running in OA models than in intact models. Additionally, parallel-oriented models produce higher maximum stresses and fluid pressure for walking and running gait than proximal-distal-oriented models. Interestingly, during the walking cycle, the maximum contact pressure with intact models is approximately three times higher than on OA models. In contrast, the OA models exhibit higher contact pressure during the running cycle. Interpretation: Overall, the study indicates that collagen orientation is crucial for tissue responsiveness. This investigation provides insights into the development of tailored implants. © 2023 IPEM
IMU-based segmental root mean square analysis of gait in individuals with cerebellar ataxia: a pilot cross-sectional study
(Nature Research, 2025) Mendonca, J.; Joshua, A.M.; Shetty, S.; Chemmangat, K.; Krishnan, S.; Kumar, K.V.; Misri, Z.; Pai, R.; Pai, S.
Cerebellar ataxia (CA) affects limb movement, balance, and gait. Subjective rating scales like Scale for the Assessment and Rating of Ataxia (SARA) may underestimate gait severity. Inertial measurement units (IMUs) offer an objective gait analysis. Impaired trunk control might compromise gait performance and stability in individuals with ataxia. This study quantified trunk kinematics and gait parameters using Root Mean Square (RMS) values, comparing CA to healthy individuals. Ten CA cases and twenty healthy controls were recruited. Six IMU sensors positioned at anatomical landmarks recorded data via two ESP32 microcontrollers using Wi-Fi. Participants walked a 10-meter path at a self-selected pace. RMS mean linear and angular velocity and angular deviation were calculated. Individuals with CA showed decreased mediolateral linear acceleration at the left shoulder (p = 0.001) and an increased vertical linear acceleration at the right ankle (p = 0.015), left shoulder (p = 0.028), and back (p = 0.019). Total angular velocity was lower at the right shoulder (p = 0.017), left shoulder (p = 0.005), back (p = 0.002), and both ankles (right: p = 0.001; left: p = 0.001). The correlation between IMU-derived features and SARA-gait score in the CA group was not statistically significant (all p > 0.05), except for the right shoulder’s mediolateral angular velocity (p = 0.046). Both ankle segments’ angular deviations (right: p = 0.001; left: p = 0.006) were reduced. The CA group revealed reduced RMS linear and angular velocities. IMU-based trunk and gait analysis provides a more objective method that would help in planning targeted rehabilitation treatments. Trial registration: The study was approved by the Institutional Ethics Committee (IEC), Kasturba Medical College, Mangalore, Manipal Academy of Higher Education (IEC KMC MLR 12/2023/483) on 21st December 2023 and the Clinical Trial Registration (CTRI/2024/07/070614) on July 15th, 2024. © The Author(s) 2025.

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