Abstract
Currently, kinesiologists who study the posture of people during walking rely on spreadsheets and visual posture assessment. Some technologies make it possible to include sensors in people's bodies to identify their movements. Today, artificial intelligence is supporting many medical processes. In this sense, our proposal focuses on developing software based on Computer Vision and Artificial Intelligence. The software is deployed in a robust architecture based on microservices to support the process of image analysis with high concurrency. This software assists specialists in the analysis and measurements of lower extremity angles and distances during gait. On this occasion, we are working with a local medical center, specialists in caring for high-performance athletes. One of its crucial kinesiology care activities is the performance of kinematic gait analysis.
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References
Shortliffe, E.H., Blois†, M.S.: the computer meets medicine and biology: emergence of a discipline. In: Shortliffe, E.H., Cimino, J.J. (eds.) Biomedical Informatics: Computer Applications in Health Care and Biomedicine, pp. 3–45. Springer, New York (2006)
Pavez, R., Diaz, J., Arango-Lopez, J., Ahumada, D., Mendez-Sandoval, C., Moreira, F.: Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders. Neural Comput. Appl., 1–12 (2021)
Whittle, M.W.: Gait Analysis: An Introduction. Butterworth-Heinemann (2014)
Zahradka, N., Verma, K., Behboodi, A., Bodt, B., Wright, H., Lee, S.C.K.: An evaluation of three kinematic methods for gait event detection compared to the kinetic-based “gold standard.” Sensors 20 (2020). https://doi.org/10.3390/s20185272
Barker, S., Craik, R., Freedman, W., Herrmann, N., Hillstrom, H.: Accuracy, reliability, and validity of a spatiotemporal gait analysis system. Med. Eng. Phys. 28, 460–467 (2006)
Puig-Diví, A., Escalona-Marfil, C., Padullés-Riu, J.M., Busquets, A., Padullés-Chando, X., Marcos-Ruiz, D.: Validity and reliability of the Kinovea program in obtaining angles and distances using coordinates in 4 perspectives. PLoS One. 14, e0216448 (2019)
D’Antonio, E., Taborri, J., Mileti, I., Rossi, S., Patane, F.: Validation of a 3D markerless system for gait analysis based on OpenPose and two RGB webcams. IEEE Sens. J. 21, 17064–17075 (2021)
Domingues, M. de F., et al.: Wearable devices for remote physical rehabilitation using a fabry-perot optical fiber sensor: Ankle Joint Kinematic. IEEE Access. 8, 109866–109875 (2020)
Celik, Y., Stuart, S., Woo, W.L., Sejdic, E., Godfrey, A.: Multi-modal gait: a wearable, algorithm and data fusion approach for clinical and free-living assessment. Inf. Fusion. 78, 57–70 (2022)
Chow, D.H.K., Tremblay, L., Lam, C.Y., Yeung, A.W.Y., Cheng, W.H.W., Tse, P.T.W.: Comparison between accelerometer and gyroscope in predicting level-ground running kinematics by treadmill running kinematics using a single wearable sensor. Sensors. 21, 4633 (2021)
Seifert, A.-K., Grimmer, M., Zoubir, A.M.: Doppler radar for the extraction of biomechanical parameters in gait analysis. IEEE J. Biomed. Health Inform. 25, 547–558 (2021)
Sakamoto, K., Tsujioka, C., Sasaki, M., Miyashita, T., Kitano, M., Kudo, S.: Validity and reproducibility of foot motion analysis using a stretch strain sensor. Gait Posture. 86, 180–185 (2021)
Weygers, I., et al.: Drift-free inertial sensor-based joint kinematics for long-term arbitrary movements. IEEE Sens. J. 20, 7969–7979 (2020)
Funding
This work was supported by the FCT – Fundação para a Ciência e a Tecnologia, I.P. [Project UIDB/05105/2020].
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Córdova, M., Díaz, J., Arango-López, J., Ahumada, D., Moreira, F. (2022). Towards Automatic Gait Analysis from an IT Perspective: A Kinesiology Case. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 470. Springer, Cham. https://doi.org/10.1007/978-3-031-04829-6_36
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DOI: https://doi.org/10.1007/978-3-031-04829-6_36
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