Position estimation through IMU based on detection of stable periods during gait
DOI:
https://doi.org/10.46502/issn.2710-995X/2021.5.03Keywords:
inertial measurement unit, stride length, gravity estimation, human gait.Abstract
This work is focused to estimate position for an application of stride length estimation in a gait process. The position estimation is made by detecting walk stability periods. To do that, inertial sensors, specifically, accelerometers and gyroscopes were used. The proposal was validated by working with simulation signals, in a process that allowed for using the same algorithm parameters in the work with true signals. The goal position, or stride length, was estimated with a satisfactory effectiveness. The effectiveness was computed as the average of the difference of the expected and the estimated position.
Downloads
Download data is not yet available.
References
Abyarjoo, F., Barreto, A., Cofino, J., & Ortega, F. R. (2015). Implementing a sensor fusion algorithm for 3D orientation detection with inertial/magnetic sensors. In Innovations and advances in computing, informatics, systems sciences, networking and engineering (págs. 305-310). Cham: Springer, doi:10.1007/978-3319-0677-5_4/
Awasthi, S., & Joshi, A. (febrero, 2015). MEMS accelerometer based system for motion analysis. 2nd International Conference on Electronics and Communication Systems (ICECS), (págs. 762-767). Coimbatore, India.
Chen, K., & Basset, D. J. (2005). The technology of accelerometry-based activity monitors: current and future. Med Sei Sports Exere, 37(11), 490-500.
Corder, K., Ekelund, U., Steele, R. M., Wareham, N. J., & Brage, S. (2008). Assessment of physical activity in youth. Journal of Applied Physiology, 105(3), 977-987.
Garcia, D., & Bueno, C. (2010). Desempeño Físico en adultos mayores sanos, del municipio Plaza de la Revolución. GeroInfo, 5(1).
Garcia, D., Morejon, S., De Dios, C., & Rodriguez, Z. (2018). Las pruebas de desempeño físico en el pronóstico de desenlaces adversos en los ancianos. MediSan, 22(6), 466-470.
Garcia, D., PIinera, J. A., Garcia., & Bueno, C. (2020). Estudio de la fuerza de agarre en adultos mayores del municipio Plaza de la Revolución. Revista Cubana Médica Deporte Cultura Física, 8(1), 1-13.
Gerety, M., Mulrow, C., Tuley, M., Hazuda, H., Lichetensein, M., & Bohannon, R. (1993). Development and validation of a physical performance instrument for the functionally impaired elderly: The Physical Disability Index (PDI). Journal of Gerontology Series A: Biomedical Sciences and Medical Sciences, 48(2), 33-38.
Gouwanda, D., & Senanayake, S. (2011). Periodical gait asymmetry assessment using real-time wireless gyroscopes gait monitoring system. J. Med. Eng. Technol., 35(8), 432- 440.
Hannik, J., Kautz, T., Pasluosta, C. F., Barth, J., Schulein, S., Gabmann, K., & Eskofier, B. (2017). Mobile stride length estimation with deep convolutional neural networks. IEEE journal of biomedical and health informatics, 22(2), 354-362.
Hemminki, S., Nurmi, P., & Tarkoma, S. (diciembre, 2014). Gravity and linear acceleration estimation on mobile devices. In Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, (págs. 50-59). London.
Kam, M., Zhu, X., & Kalata, P. (1997). Sensor fusion for mobile robot navigation. Proceedings of the IEEE, 85(1), 108-119.
Kavanagh, JJ, & Menz, H. B. (2008). Accelerometry: a technique for quantifying movement pattems dudng walking. Gait Posture, 28(1), 1-15.
Lee, C. Y., & Lee, J. J. (2002). Estimation of walking behavior using accelerometers in gait rehabilitation. International Journal of Human-friendly Welfare Robotic Systems, 3(2), 32-36.
Loredo Medina, R. (2011). Sistema de monitoreo de la marcha como apoyo al cuidado de adultos mayores. (Tesis de Maestría), Centro de Investigación Científica y de Educación Superior de Ensenada, Baja California. Recuperado el 19 de agosto de 2019, de https://cicese.repositorioinstitucional.mx/jspui/handle/1007/1547
Luinge, H. J., & Veltink, P. H. (2005). Measuring orientation of human body segments using miniature gyroscopes and accelerometers. Medical and Biological Engineering and computing, 43(2), 273-292.
Martin, E. (2011). Novel method for stride length estimation with body area network accelerometers. In 2011 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems, (págs. 79-82).
Menendez Alvarez, J. (2018). Desarrollo de un sistema electrónico experimental para la medición de variables físicas necesarias en la determinación de parámetros de marcha en ancianos. (Tesis en opción al título de ingeniero en Telecomunicaciones y Electrónica) Universidad Tecnológica De La Habana José Antonio Echeverría CUJAE. Cuba. Obtenido de https://scholar.google.es/scholar?cluster=1575214438424323267&hl=es&as_sdt=2005&sciodt=0,5
Najabi, B., Aminian, K., Loew, F., Blanc, Y., & Robert, P. A. (2002). Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly. IEEE Trans. Biomed. Eng., 49(8), 843-851.
Pang, J., & Sing, I. (Octubre 2011). Accelerometer Based Real-Time Remote Detection and Monitoring of Hand Motion. Proceedings of the World Congress of Engineering and Computer Science, (págs. 19-21). San Francisco, USA.
Pasciuto, I., Ligorio, G., Bergamini, E., & Vannozzi, G. (2015). How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy. Sensors, 15(9), 23983-24001.
Pedley, M. (2013). Tilt sensing using a three-axis accelerometer. Freescale semiconductor application note, 1, 1, 2012-2013.
Perry, J. (1992). Gait Analysis Normal and Pathological Function. USA: SLACK.
Peruzzi, A., Della, U., & Cereatti, A. (2011). Estimation of stride length in level walking using an inertial measurement unit attached to the foot: A validation of the zero velocity assumption during stance. Journal of Biomechanics, 44(10), 1991-1994.
Rantanen, T., Guralnik, J., Ferrucci, L., & Leveille, S. (1999). Coimpairments: strength and balance as predictors of severe walking disability. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences, 54(4), 172-176.
Sijobert, B., M., B., J., D., Pissard, R., Geny, C., & Coste, C. A. (2015). Implementation and validation of a stride length estimation algorithm, using a single basic inertial sensor on healthy subjects and patients suffering from Parinson's disease. Electronic Healthcare, 7, 704-714. doi:10.4236/health2015.76084
Vara Rodriguez, D. (2014). Sistemas para determinar la posición y orientación de herramientas quirúrgicas en operaciones de cirugía laparoscópica. (Tesis en opción al título de Ingeniería Electrónica Industrial y Automática) Escuela de Ingeniería de Industriales, Departamento de Ingeniería de Sistemay Automática, Mexico.
Varesano, F. (2011). Using Arduino for Tangible Human Computer Interaction. (Tesis de Maestría), Universidad de Torino, Departamento de Informática, Italia.
Vela Pena, R. (2016). Sistema de Detección de Movimientos Basado en Sensores Inerciales Integrados. (Tesis de maestría), Instituto Politécnico Nacional, Centrode Investigación e Innovación Tecnológica, México.
Vistronica. (s.f.). Vistronica, Tienda virtual de electrónica. Recuperado el 27 de 8 de 2019, de https://www.vistronica.com/imu/
Awasthi, S., & Joshi, A. (febrero, 2015). MEMS accelerometer based system for motion analysis. 2nd International Conference on Electronics and Communication Systems (ICECS), (págs. 762-767). Coimbatore, India.
Chen, K., & Basset, D. J. (2005). The technology of accelerometry-based activity monitors: current and future. Med Sei Sports Exere, 37(11), 490-500.
Corder, K., Ekelund, U., Steele, R. M., Wareham, N. J., & Brage, S. (2008). Assessment of physical activity in youth. Journal of Applied Physiology, 105(3), 977-987.
Garcia, D., & Bueno, C. (2010). Desempeño Físico en adultos mayores sanos, del municipio Plaza de la Revolución. GeroInfo, 5(1).
Garcia, D., Morejon, S., De Dios, C., & Rodriguez, Z. (2018). Las pruebas de desempeño físico en el pronóstico de desenlaces adversos en los ancianos. MediSan, 22(6), 466-470.
Garcia, D., PIinera, J. A., Garcia., & Bueno, C. (2020). Estudio de la fuerza de agarre en adultos mayores del municipio Plaza de la Revolución. Revista Cubana Médica Deporte Cultura Física, 8(1), 1-13.
Gerety, M., Mulrow, C., Tuley, M., Hazuda, H., Lichetensein, M., & Bohannon, R. (1993). Development and validation of a physical performance instrument for the functionally impaired elderly: The Physical Disability Index (PDI). Journal of Gerontology Series A: Biomedical Sciences and Medical Sciences, 48(2), 33-38.
Gouwanda, D., & Senanayake, S. (2011). Periodical gait asymmetry assessment using real-time wireless gyroscopes gait monitoring system. J. Med. Eng. Technol., 35(8), 432- 440.
Hannik, J., Kautz, T., Pasluosta, C. F., Barth, J., Schulein, S., Gabmann, K., & Eskofier, B. (2017). Mobile stride length estimation with deep convolutional neural networks. IEEE journal of biomedical and health informatics, 22(2), 354-362.
Hemminki, S., Nurmi, P., & Tarkoma, S. (diciembre, 2014). Gravity and linear acceleration estimation on mobile devices. In Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, (págs. 50-59). London.
Kam, M., Zhu, X., & Kalata, P. (1997). Sensor fusion for mobile robot navigation. Proceedings of the IEEE, 85(1), 108-119.
Kavanagh, JJ, & Menz, H. B. (2008). Accelerometry: a technique for quantifying movement pattems dudng walking. Gait Posture, 28(1), 1-15.
Lee, C. Y., & Lee, J. J. (2002). Estimation of walking behavior using accelerometers in gait rehabilitation. International Journal of Human-friendly Welfare Robotic Systems, 3(2), 32-36.
Loredo Medina, R. (2011). Sistema de monitoreo de la marcha como apoyo al cuidado de adultos mayores. (Tesis de Maestría), Centro de Investigación Científica y de Educación Superior de Ensenada, Baja California. Recuperado el 19 de agosto de 2019, de https://cicese.repositorioinstitucional.mx/jspui/handle/1007/1547
Luinge, H. J., & Veltink, P. H. (2005). Measuring orientation of human body segments using miniature gyroscopes and accelerometers. Medical and Biological Engineering and computing, 43(2), 273-292.
Martin, E. (2011). Novel method for stride length estimation with body area network accelerometers. In 2011 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems, (págs. 79-82).
Menendez Alvarez, J. (2018). Desarrollo de un sistema electrónico experimental para la medición de variables físicas necesarias en la determinación de parámetros de marcha en ancianos. (Tesis en opción al título de ingeniero en Telecomunicaciones y Electrónica) Universidad Tecnológica De La Habana José Antonio Echeverría CUJAE. Cuba. Obtenido de https://scholar.google.es/scholar?cluster=1575214438424323267&hl=es&as_sdt=2005&sciodt=0,5
Najabi, B., Aminian, K., Loew, F., Blanc, Y., & Robert, P. A. (2002). Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly. IEEE Trans. Biomed. Eng., 49(8), 843-851.
Pang, J., & Sing, I. (Octubre 2011). Accelerometer Based Real-Time Remote Detection and Monitoring of Hand Motion. Proceedings of the World Congress of Engineering and Computer Science, (págs. 19-21). San Francisco, USA.
Pasciuto, I., Ligorio, G., Bergamini, E., & Vannozzi, G. (2015). How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy. Sensors, 15(9), 23983-24001.
Pedley, M. (2013). Tilt sensing using a three-axis accelerometer. Freescale semiconductor application note, 1, 1, 2012-2013.
Perry, J. (1992). Gait Analysis Normal and Pathological Function. USA: SLACK.
Peruzzi, A., Della, U., & Cereatti, A. (2011). Estimation of stride length in level walking using an inertial measurement unit attached to the foot: A validation of the zero velocity assumption during stance. Journal of Biomechanics, 44(10), 1991-1994.
Rantanen, T., Guralnik, J., Ferrucci, L., & Leveille, S. (1999). Coimpairments: strength and balance as predictors of severe walking disability. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences, 54(4), 172-176.
Sijobert, B., M., B., J., D., Pissard, R., Geny, C., & Coste, C. A. (2015). Implementation and validation of a stride length estimation algorithm, using a single basic inertial sensor on healthy subjects and patients suffering from Parinson's disease. Electronic Healthcare, 7, 704-714. doi:10.4236/health2015.76084
Vara Rodriguez, D. (2014). Sistemas para determinar la posición y orientación de herramientas quirúrgicas en operaciones de cirugía laparoscópica. (Tesis en opción al título de Ingeniería Electrónica Industrial y Automática) Escuela de Ingeniería de Industriales, Departamento de Ingeniería de Sistemay Automática, Mexico.
Varesano, F. (2011). Using Arduino for Tangible Human Computer Interaction. (Tesis de Maestría), Universidad de Torino, Departamento de Informática, Italia.
Vela Pena, R. (2016). Sistema de Detección de Movimientos Basado en Sensores Inerciales Integrados. (Tesis de maestría), Instituto Politécnico Nacional, Centrode Investigación e Innovación Tecnológica, México.
Vistronica. (s.f.). Vistronica, Tienda virtual de electrónica. Recuperado el 27 de 8 de 2019, de https://www.vistronica.com/imu/
Published
2021-11-23
How to Cite
Pérez Molinet, A., Hernándes Montero, F. E., Arencibia Castellanos, G., & Rodriguez, J. R. (2021). Position estimation through IMU based on detection of stable periods during gait. Orange Journal, 3(5), 16–29. https://doi.org/10.46502/issn.2710-995X/2021.5.03
Issue
Section
Artículos
