Knee Joint Angle Measuring Portable Embedded System based on Inertial Measurement Units for Gait Analysis
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P. Medina Gonzí¡lez, “Evaluación de parí¡metros cinemí¡ticos de marcha confortable y mí¡xima en adultos mayores ví¡lidos chilenos,” Fisioterapia, vol. 38, no. 6, pp. 286-294, Nov. 2016.
A. Guzik and M. Drużbicki, “Application of the Gait Deviation Index in the analysis of post-stroke hemiparetic gait,” J. Biomech., vol. 99, Jan. 2020.
K. P. Correa, G. F. Devetak, S. K. Martello, J. C. de Almeida, A. C. Pauleto, and E. F. Manffra, “Reliability and Minimum Detectable Change of the Gait Deviation Index (GDI) in post-stroke patients,” Gait Posture, vol. 53, pp. 29-34, Mar. 2017.
F. O. Barroso et al., “Combining muscle synergies and biomechanical analysis to assess gait in stroke patients,” J. Biomech., vol. 63, pp. 98-103, Oct. 2017.
C. C. Bassile and S. M. Hayes, “Gait Awareness,” in Stroke Rehabilitation, Elsevier, 2016, pp. 194-223.
B. J. Darter and J. B. Webster, Principles of Normal and Pathologic Gait. Elsevier Inc., 2019.
C. Duraffourg, X. Bonnet, B. Dauriac, and H. Pillet, “Real time estimation of the pose of a lower limb prosthesis from a single shank mounted IMU,” Sensors (Switzerland), vol. 19, no. 13, Jul. 2019.
A. Phinyomark, S. T. Osis, and R. Ferber, “Analysis Of Big Data In Running Biomechanics: Application of Multivariate Analysis And Machine Learning Methods,” 2016.
L. V Calderita, J. P. Bandera, P. Bustos, and A. Skiadopoulos, “Model-based reinforcement of kinect depth data for human motion capture applications,” Sensors (Switzerland), vol. 13, no. 7, pp. 8835-8855, 2013.
M. Abid, N. Mezghani, and A. Mitiche, “Knee joint biomechanical gait data classification for knee pathology assessment: A literature review,” Applied Bionics and Biomechanics, vol. 2019. Hindawi Limited, 2019.
K. Yasuda, Y. Hayashi, A. Tawara, and H. Iwata, “Development of a vibratory cueing system using an implicit method to increase walking speed in patients with stroke: a proof-of-concept study,” ROBOMECH J., vol. 7, no. 1, Dec. 2020.
R. S. Calabrí² et al., “Walking on the Moon: A randomized clinical trial on the role of lower body positive pressure treadmill training in post-stroke gait impairment,” J. Adv. Res., vol. 21, pp. 15-24, Mar. 2020.
D. Buongiorno, I. Bortone, G. D. Cascarano, G. F. Trotta, A. Brunetti, and V. Bevilacqua, “A low-cost vision system based on the analysis of motor features for recognition and severity rating of Parkinson’s Disease,” BMC Med. Inform. Decis. Mak., vol. 19, no. 9, 2019.
D. Slijepcevic et al., “Automatic Classification of Functional Gait Disorders,” IEEE J. Biomed. Heal. Informatics, vol. 22, no. 5, pp. 1653-1661, Sep. 2018.
M. Eltoukhy, C. Kuenze, J. Oh, S. Wooten, and J. Signorile, “Kinect-based assessment of lower limb kinematics and dynamic postural control during the star excursion balance test,” Gait Posture, vol. 58, pp. 421-427, 2017.
E. van der Kruk and M. M. Reijne, “Accuracy of human motion capture systems for sport applications; state-of-the-art review,” Eur. J. Sport Sci., vol. 18, no. 6, pp. 806-819, Jul. 2018.
M. T. Parks, Z. Wang, and K. C. Siu, “Current Low-Cost Video-Based Motion Analysis Options for Clinical Rehabilitation: A Systematic Review,” Physical Therapy, vol. 99, no. 10. Oxford University Press, pp. 1405-1425, 28-Oct-2019.
A. Filippeschi, N. Schmitz, M. Miezal, G. Bleser, E. Ruffaldi, and D. Stricker, “Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion,” Sensors, vol. 17, no. 6, p. 1257, Jun. 2017.
A. Clapí©s, í€. Pardo, O. Pujol Vila, and S. Escalera, “Action detection fusing multiple Kinects and a WIMU: an application to in-home assistive technology for the elderly,” Mach. Vis. Appl., vol. 29, no. 5, pp. 765-788, 2018.
S. Zihajehzadeh and E. J. Park, “A Novel Biomechanical Model-Aided IMU/UWB Fusion for Magnetometer-Free Lower Body Motion Capture,” IEEE Trans. Syst. Man, Cybern. Syst., vol. 47, no. 6, pp. 927-938, Jun. 2017.
J. H. Zhang, B. Y. He, X. S. Yang, and W. A. Zhang, “A Review on Wearable Inertial Sensor Based Human Motion Tracking,” Zidonghua Xuebao/Acta Automatica Sinica, vol. 45, no. 8. Science Press, pp. 1439-1454, 01-Aug-2019.
R. Kumarasiri, A. Niroshan, Z. Lantra, T. Madusanka, C. U. S. Edussooriya, and R. Rodrigo, “Gait Analysis Using RGBD Sensors,” in 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018, 2018, pp. 460-465.
P. Plantard, H. P. Hubert, and F. Multon, “Filtered pose graph for efficient kinect pose reconstruction,” Multimed. Tools Appl., vol. 76, no. 3, pp. 4291-4312, 2017.
A. Mobini, S. Behzadipour, and M. S. Foumani, “Hand acceleration measurement by Kinect for rehabilitation applications,” Sci. Iran., vol. 24, no. 1, pp. 191-201, 2017.
A. Muraszkowski et al., “Integration of motion capture data acquisition with multibody dynamic simulation software for nordic walking gait analysys,” in Lecture Notes in Mechanical Engineering, Pleiades Publishing, 2019, pp. 510-517.
Martin, D. I. H. Putri, Riyanto, and C. Machbub, “Gait Controllers on Humanoid Robot Using Kalman Filter and PD Controller,” in 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018, 2018, pp. 36-41.
D. S. Nair, G. Jagadanand, and S. George, “Sensorless direct torque-controlled BLDC motor drive with Kalman filter algorithm,” in IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 2017, pp. 2160-2165.
V. N. Megharjun and V. Talasila, “A Kalman Filter based Full Body Gait Measurement System,” in 2018 IEEE 3rd International Conference on Circuits, Control, Communication and Computing, I4C 2018, 2018.
M. Abdelhady, A. J. Van Den Bogert, and D. Simon, “A High-Fidelity Wearable System for Measuring Lower-Limb Kinetics and Kinematics,” IEEE Sens. J., vol. 19, no. 24, pp. 12482-12493, Dec. 2019.
M. Ye, C. Yang, V. Stankovic, L. Stankovic, and S. Cheng, “Gait phase classification for in-home gait assessment,” in 2017 IEEE International Conference on Multimedia and Expo (ICME), 2017, pp. 1524-1529.
D. Mayorca-Torres, H. Guerrero-Chapal, J. Mejía-Manzano, D. Lopez-Mesa, D. H. Peluffo-Ordoñez, and J. A. Salazar-Castro, “Multi-target tracking for sperm motility measurement using the kalman filter and JPDAF: Preliminary results,” RISTI - Rev. Iber. Sist. e Tecnol. Inf., vol. 2019, no. E22, pp. 282-294, 2019.
H. Tannous et al., “A new multi-sensor fusion scheme to improve the accuracy of knee flexion kinematics for functional rehabilitation movements,” Sensors (Switzerland), vol. 16, no. 11, 2016.
I. T. Gatt, T. Allen, and J. Wheat, “Accuracy and repeatability of wrist joint angles in boxing using an electromagnetic tracking system,” Sport. Eng., vol. 23, no. 1, Dec. 2020.
L. Brosseau et al., “Intra- and intertester reliability and criterion validity of the parallelogram and universal goniometers for measuring maximum active knee flexion and extension of patients with knee restrictions,” Arch. Phys. Med. Rehabil., vol. 82, no. 3, pp. 396-402, Mar. 2001.
A. P. Quixadí¡, A. N. Onodera, N. Peña, J. G. V. Miranda, and K. N. Sí¡, “Validity And Reliability Of Free Software For Bidimentional Gait Analysis,” Rev. Pesqui. em Fisioter., vol. 7, no. 4, pp. 548-557, Nov. 2017.
Y. Shang, X. Sun, X. Yang, X. Wang, and Q. Yu, “A camera calibration method for large field optical measurement,” Optik (Stuttg)., vol. 124, no. 24, pp. 6553-6558, Dec. 2013.
M. Qi, B. Zhang, Y. Xu, H. Xin, and G. Cheng, “Linear camera calibration by single image based on distortion correction,” in ACM International Conference Proceeding Series, 2018, pp. 21-25.
K. H. Eom, S. J. Lee, Y. S. Kyung, C. W. Lee, M. C. Kim, and K. K. Jung, “Improved kalman filter method for measurement noise reduction in multi sensor RFID systems,” Sensors, vol. 11, no. 11, pp. 10266-10282, Nov. 2011.
D. Mayorca-Torres, J. C. Caicedo-Eraso, and D. H. Peluffo-Ordoñez, “Method for the Improvement of Knee Angle Accuracy Based on Kinect and IMU: Preliminary Results,” 2019, pp. 184-199.
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