Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson
Los tres volúmenes previos de Ingeniería y Salud han reportado resultados en la investigación de las posibilidades de uso de dispositivos no especializados, más propios de los juegos electrónicos, como herramientas de captura de movimientos capaces de producir datos cuantitativos que faciliten la ev...
- Autores:
-
García Peña, Melissa
Herrán Sánchez, Carlos Alfonso
Ordoñez Burbano, Jonatan
Urcuqui López, Christian Camilo
Navarro Cadavid, Andrés
- Tipo de recurso:
- Book
- Fecha de publicación:
- 2023
- Institución:
- Universidad ICESI
- Repositorio:
- Repositorio ICESI
- Idioma:
- spa
- OAI Identifier:
- oai:repository.icesi.edu.co:10906/130436
- Palabra clave:
- Parkinson Disease
Early Diagnosis
Medical Informatics Application
Parkinson Disease
Early Diagnosis
Medical Informatics Application
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| dc.title.eng.fl_str_mv |
Advances in the application of engineering to the assessment of people with Parkinson’s disease. |
| title |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| spellingShingle |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson Parkinson Disease Early Diagnosis Medical Informatics Application Parkinson Disease Early Diagnosis Medical Informatics Application |
| title_short |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| title_full |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| title_fullStr |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| title_full_unstemmed |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| title_sort |
Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de Parkinson |
| dc.creator.fl_str_mv |
García Peña, Melissa Herrán Sánchez, Carlos Alfonso Ordoñez Burbano, Jonatan Urcuqui López, Christian Camilo Navarro Cadavid, Andrés |
| dc.contributor.author.none.fl_str_mv |
García Peña, Melissa Herrán Sánchez, Carlos Alfonso Ordoñez Burbano, Jonatan Urcuqui López, Christian Camilo Navarro Cadavid, Andrés |
| dc.subject.proposal.spa.fl_str_mv |
Parkinson Disease Early Diagnosis Medical Informatics Application |
| topic |
Parkinson Disease Early Diagnosis Medical Informatics Application Parkinson Disease Early Diagnosis Medical Informatics Application |
| dc.subject.proposal.eng.fl_str_mv |
Parkinson Disease Early Diagnosis Medical Informatics Application |
| description |
Los tres volúmenes previos de Ingeniería y Salud han reportado resultados en la investigación de las posibilidades de uso de dispositivos no especializados, más propios de los juegos electrónicos, como herramientas de captura de movimientos capaces de producir datos cuantitativos que faciliten la evaluación clínica que realizan los profesionales de la salud para el diagnóstico y monitoreo de la evolución de la enfermedad de Parkinson. Este cuarto volumen sigue esa línea, en él se reportan dos temas: el primero, la constatación cuantitativa de la relación que existe entre las extremidades —inferiores y superiores— de las personas que padecen Parkinson, con lo que se abre una ruta para la exploración de esta relación que sirve de base para el concepto de inferencia causal; el segundo, el diseño de una herramienta que le permite al personal médico manejar la información técnica que arrojan las pruebas de marcha realizadas con e-motion, el sistema desarrollado por los proyectos previamente reportados, sin necesidad del apoyo de ingenieros, con lo que se reducen tanto los tiempos de entrega de datos útiles como los costos asociados a esta tarea. |
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T. A. L. Wren, C. Lening, S. A. Rethlefsen, and R. M. Kay, “Impact of gait analysis on correction of excessive hip internal rotation in ambulatory children with cerebral palsy: A randomized controlled trial,” Dev. Med. Child Neurol., vol. 55, no. 10, pp. 919–925, 2013, doi: 10.1111/dmcn.12184. B. Munoz, Y. J. Castano-Pino, J. David Arango Paredes, and A. Na - varro, “Automated gait analysis using a kinect camera and wavelets,” 2018 IEEE 20th Int. Conf. e-Health Networking, Appl. Serv. Heal. 2018, pp. 1–5, 2018, doi: 10.1109/HealthCom.2018.8531161. “GAITRite | World Leader in Temporospatial Gait Analysis.” ht - tps://www.gaitrite.com/ (accessed Apr. 18, 2021). “Vicon | Award Winning Motion Capture Systems.” https://www. vicon.com/ (accessed Apr. 18, 2021). J. D. Mejia-Trujillo et al., “KinectTM and Intel RealSenseTM D435 comparison: a preliminary study for motion analysis,” 2019 IEEE Int. Conf. E-Health Networking, Appl. Serv. Heal. 2019, no. Octo - ber, pp. 3–7, 2019, doi: 10.1109/HealthCom46333.2019.9009433. J. A. Albert, V. Owolabi, A. Gebel, C. M. Brahms, U. Granacher, and B. Arnrich, “Evaluation of the pose tracking performance of the azure kinect and kinect v2 for gait analysis in comparison with a gold standard: A pilot study,” Sensors (Switzerland), vol. 20, no. 18, pp. 1–22, 2020, doi: 10.3390/s20185104. A. Muro-de-la-Herran, B. García-Zapirain, and A. Méndez-Zorrilla, “Gait analysis methods: An overview of wearable and non-wearable systems, highlighting clinical applications,” Sensors (Switzerland), vol. 14, no. 2, pp. 3362–3394, 2014, doi: 10.3390/s140203362. R. A. Noble and R. White, “Visualisation of gait analysis data,” Proc. Int. Conf. Inf. Vis., vol. 2005, pp. 247–252, 2005, doi: 10.1109/ IV.2005.139. “Kinect - Windows app development.” https://developer.microsoft. com/en-us/windows/kinect/ (accessed Apr. 18, 2021). A. P. Rocha, H. Choupina, J. M. Fernandes, M. J. Rosas, R. Vaz, and J. P. S. Cunha, “Parkinson’s disease assessment based on gait analy - sis using an innovative RGB-D camera system,” 2014 36th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBC 2014, pp. 3126–3129, 2014, doi: 10.1109/EMBC.2014.6944285. J. D. Arango Paredes, B. Muñoz, W. Agredo, Y. Ariza-Araújo, J. L. Orozco, and A. Navarro, “A reliability assessment softwa - re using Kinect to complement the clinical evaluation of Parkin - son’s disease,” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, vol. 2015-Novem, pp. 6860–6863, 2015, doi: 10.1109/ EMBC.2015.7319969. M. Unser and A. Aldroubi, “A review of wavelets in biomedical applications,” Proc. IEEE, vol. 84, no. 4, pp. 626–638, 1996, doi: 10.1109/5.488704. T. Chau, “A review of analytical techniques for gait data. Part 2: Neural network and wavelet methods,” Gait Posture, vol. 13, no. 2, pp. 102–120, 2001, doi: 10.1016/S0966-6362(00)00095-3. K. Aminian, B. Najafi, C. Büla, P. F. Leyvraz, and P. Robert, “Spa - tio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes,” J. Biomech., vol. 35, no. 5, pp. 689– 699, 2002, doi: 10.1016/S0021-9290(02)00008-8. “Parallel Computing Toolbox - MATLAB.” https://www.mathwor - ks.com/products/parallel-computing.html (accessed May 17, 2022). A. Marowka, “On parallel software engineering education using python,” Educ. Inf. Technol., vol. 23, no. 1, pp. 357–372, 2018, doi: 10.1007/s10639-017-9607-0. B.-C. Wang, “DIGITAL SIGNAL PROCESSING TECHNIQUES AND APPLICATIONS IN RADAR IMAGE PROCESSING.” “Wavelet Transforms - an overview | ScienceDirect Topics.” ht - tps://www.sciencedirect.com/topics/mathematics/wavelet-trans - forms (accessed May 09, 2021). “Algoritmo para detección de vibraciones anormales en maquina - rias utilizando la transformada wavelet.” https://www.researchgate. net/publication/37613214_Algoritmo_para_deteccion_de_vibra - ciones_anormales_en_maquinarias_utilizando_la_transformada_ wavelet (accessed May 09, 2021). J. O. Smith III, Continuous wavelt transform, in Spectral audio signal processing', W3K Publishing, 2011. https://ccrma.stanford. edu/~jos/sasp/Continuous_Wavelet_Transform.html M. J. Lai, “Popular wavelet families and filters and their use,” in Computational Complexity: Theory, Techniques, and Applications, vol. 9781461418009, Springer New York, 2012, pp. 2168–2225. S. Zope-Chaudhari, P. Venkatachalam, and K. M. Buddhiraju, “As - sessment of distortion in watermarked geospatial vector data using different wavelets,” Geo-Spatial Inf. Sci., vol. 18, no. 2–3, pp. 124– 133, Jul. 2015, doi: 10.1080/10095020.2015.1071064. Y. J. Castaño, A. Navarro, J. D. Arango, B. E. Muñoz, J. L. Orozco, and J. Valderrama, “Gait and arm swing analysis measurements for patients diagnosed with Parkinson’s disease, using digital signal pro - cessing and Kinect,” CEUR Workshop Proc., vol. 2178, pp. 71–74, 2018. S. H. Roosta, “Parallel Processing and Parallel Algorithms,” Parallel Process. Parallel Algorithms, 2000, doi: 10.1007/978-1-4612-1220-1. M. I. Capel, A. J. Tomeu, and A. G. Salguero, “Teaching concu - rrent and parallel programming by patterns: An interactive ICT approach,” J. Parallel Distrib. Comput., vol. 105, pp. 42–52, Jul. 2017, doi: 10.1016/J.JPDC.2017.01.010. A. Igor Anatolyevich Kalmykov, Konstantin Aleksandrovich Katkov, Naumenko Daniil Olegovich and A. V. M. Bronislavovich Sarkisov, “Parallel modular technologies in digital signal processing,” J. Chem. Inf. Model., vol. 53, no. 9, pp. 1689–1699, 2013. C. J. Hughes, “Single-instruction multiple-data execution,” Syn - th. Lect. Comput. Archit., vol. 32, pp. 1–121, 2015, doi: 10.2200/ S00647ED1V01Y201505CAC032. C. Shih-Lin Chien, L. Shinn-Zong, L. Chung-Chao, H. Yu-Loong, L. Chi-Wei, Ch. Shin-Yuan, “The efficacy of quantitative gait analy - sis by the GAITRite system in evaluation of parkinsonian bradyki - nesia,”Parkinson and related Disorders, Vol. 12, No. 7, pp. 438-442; 2006. https://doi.org/10.1016/j.parkreldis.2006.04.004 A. Pfister, A. M. West, S, Bronner, J. A. Noah, “Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analy - sis,” J Med Eng Technol, Vol. 38, No. 5, pp. 274, 280; 2014. doi: 10.3109/03091902.2014.909540. J. Camilo and V. Correa, “Design and Implementation of a Portable Device for Real Time Analysis of Speech of People with Parkinson’s Disease,” 2013. A. Procházka, O. Vyšata, M. Vališ, O. Tupa, M. Schätz, and V. Ma - rík, “Bayesian classification and analysis of gait disorders using ima - ge and depth sensors of Microsoft Kinect,” Digit. Signal Process. A Rev. J., vol. 47, pp. 169–177, 2015, doi: 10.1016/j.dsp.2015.05.011. O. Tupa et al., “Motion tracking and gait feature estimation for re - cognising Parkinson’s disease using MS Kinect,” Biomed. Eng. Onli - ne, vol. 14, no. 1, pp. 1–20, 2015, doi: 10.1186/s12938-015-0092-7. S. van der Walt, J. I. Schönberger, J. Nunez-Iglesias, F. Boulogne, J. D. Warner, N. Yager, E. Gouillart, T. Yu, & The Scikit-Image Con - tributors, “Scikit-image: image processing in Python, PeerJ 2:e453; 2014. https://doi.org/10.7717/peerj.453 N. B. Ruparelia, “Software development lifecycle models,” ACM SIGSOFT Softw. Eng. Notes, vol. 35, no. 3, pp. 8–13, May 2010, doi: 10.1145/1764810.1764814. M. Naveenkumar and S. Domnic, “Vector Quantization based Pairwise Joint Distance Maps (VQ-PJDM) for 3D Action Recog - nition,” Procedia Comput. Sci., vol. 133, pp. 27–36, 2018, doi: 10.1016/J.PROCS.2018.07.005. T. W. Ng, T. L. Tay, and S. W. Khor, “Iris recognition using ra - pid Haar wavelet decomposition,” ICSPS 2010 - Proc. 2010 2nd Int. Conf. Signal Process. Syst., vol. 1, 2010, doi: 10.1109/ ICSPS.2010.5555246. N. Ahmadi, N. Ahmadi, and M. Nilashi, “Iris Texture Recognition based on Multilevel 2-D Haar Wavelet Decomposition and Ham - ming Distance Approach,” J. Soft Comput. Decis. Support Syst., vol. 5, no. 3, pp. 16–20, Jun. 2018, Accessed: May 16, 2022. [Online]. Available: http://jscdss.com/index.php/files/article/view/168. J. M. Redondo and F. Ortin, “A Comprehensive Evaluation of Com - mon Python Implementations,” IEEE Softw., vol. 32, no. 4, pp. 76– 84, Jul. 2015, doi: 10.1109/MS.2014.104. R. Md Saad, M. Z. Ahmad, M. S. Abu, and M. S. Jusoh, “Hamming distance method with subjective and objective weights for personnel selection,” Sci. World J., vol. 2014, 2014, doi: 10.1155/2014/865495. M. Norouzi, D. J. Fleet, and R. Salakhutdinov, “Hamming distance metric learning,” Adv. Neural Inf. Process. Syst., vol. 2, pp. 1061– 1069, 2012. P. Schober and L. A. Schwarte, “Correlation coefficients: Appro - priate use and interpretation,” Anesth. Analg., vol. 126, no. 5, pp. 1763–1768, 2018, doi: 10.1213/ANE.0000000000002864. M. Ousmer, J. Vanderdonckt, and S. Buraga, “An ontology for reasoning on body-based gestures,” Proc. ACM SIGCHI Symp. Eng. Interact. Comput. Syst. EICS 2019, Jun. 2019, doi: 10.1145/3319499.3328238. V. F. Pacheco, “Microservice Patterns and Best Practices : Explore patterns like CQRS and event sourcing to create scalable, maintai - nable, and testable microservices.,” p. 357, 2018. A. J. Fernández-García, L. Iribarne, A. Corral, J. Criado, and J. Z. Wang, “A microservice-based architecture for enhancing the user experience in cross-device distributed mashup UIs with multiple forms of interaction,” Univers. Access Inf. Soc., vol. 18, no. 4, pp. 747–770, Nov. 2019, doi: 10.1007/S10209-017-0606-0. E. Stratmann, J. Ousterhout, and S. Madan, “Integrating Long Po - lling with an MVC Web Framework.” T. Fadhilah Iskandar, M. Lubis, T. Fabrianti Kusumasari, and A. Ridho Lubis, “Comparison between client-side and server-side ren - dering in the web development,” IOP Conf. Ser. Mater. Sci. Eng., vol. 801, no. 1, 2020, doi: 10.1088/1757-899X/801/1/012136. “React – A JavaScript library for building user interfaces.” https:// en.reactjs.org/ (accessed Nov. 25, 2021). |
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García Peña, Melissad65f1f41-0784-4638-a663-628e8f4641c9-1Herrán Sánchez, Carlos Alfonso45d375f0-93b6-42a2-aa8e-d859695970be-1Ordoñez Burbano, Jonatan64fff9a3-34b2-4a59-98ff-1710fab08350-1Urcuqui López, Christian Camilo4f9f5cee-ba65-4777-a38b-a7e7123a61a6600Navarro Cadavid, Andrés8f076de0-dec0-4a2b-a0ef-b8c8fef2d3f4600Cali de Lat: 03 24 00 N degrees minutes Lat: 3.4000 decimal degrees Long: 076 30 00 W degrees minutes Long: -76.5000 decimal degrees.2025-08-12T19:28:16Z2025-08-12T19:28:16Z2023-03-019786287630062https://hdl.handle.net/10906/130436https://doi.org/10.18046/EUI/iys.4.2023instname:Universidad Icesireponame:Biblioteca Digitalrepourl:https://repository.icesi.edu.co/Los tres volúmenes previos de Ingeniería y Salud han reportado resultados en la investigación de las posibilidades de uso de dispositivos no especializados, más propios de los juegos electrónicos, como herramientas de captura de movimientos capaces de producir datos cuantitativos que faciliten la evaluación clínica que realizan los profesionales de la salud para el diagnóstico y monitoreo de la evolución de la enfermedad de Parkinson. Este cuarto volumen sigue esa línea, en él se reportan dos temas: el primero, la constatación cuantitativa de la relación que existe entre las extremidades —inferiores y superiores— de las personas que padecen Parkinson, con lo que se abre una ruta para la exploración de esta relación que sirve de base para el concepto de inferencia causal; el segundo, el diseño de una herramienta que le permite al personal médico manejar la información técnica que arrojan las pruebas de marcha realizadas con e-motion, el sistema desarrollado por los proyectos previamente reportados, sin necesidad del apoyo de ingenieros, con lo que se reducen tanto los tiempos de entrega de datos útiles como los costos asociados a esta tarea.The three previous volumes of Engineering and Health have reported research results on the possibilities of using non-specialized devices, more typical of electronic games, as motion capture tools capable of producing quantitative data that facilitate clinical evaluation by health professionals for the diagnosis and monitoring of Parkinson's disease evolution. This fourth volume follows that line, reporting on two topics: the first, the quantitative verification of the relationship between the lower and upper extremities of people with Parkinson's, which opens a path for the exploration of this relationship serving as a basis for the concept of causal inference; the second, the design of a tool that allows medical personnel to manage the technical information yielded by gait tests performed with e-motion, the system developed by previously reported projects, without the need for engineer support, thereby reducing both the useful data delivery times and the costs associated with this task.Nota del editor -- Presentación -- Modelo que relaciona datos provenientes de las extremidades de un paciente con posible diagnóstico de la enfermedad de Parkinson -- 1. Introducción -- 2. Marco teórico -- 3. Estado del arte -- 4. Método -- 5. La investigación -- 6. Hallazgos -- conclusiones y trabajo futuro -- 7. Referencias -- Índice de tablas -- Índice de figuras -- Anexo 1. Exploración del dataset -- Anexo 2. Diccionario de variables de balanceo de brazos y marcha -- Software automatizado para análisis de marcha que usa Kinect v1 y wavelets como complemento a la evaluación clínica de la enfermedad de Parkinson -- 1. Introducción -- 2. Marco teórico -- 3. Estado del arte -- 4. Metodología -- 5. Resultados -- 6. Discusión -- 7. Conclusiones y trabajo futuro -- 8. Referencias -- Índice de tablas -- Índice de figuras116 páginasDigitalapplication/pdfspaUniversidad IcesiSantiago de caliEL AUTOR, expresa que la obra objeto de la presente autorización es original y la elaboró sin quebrantar ni suplantar los derechos de autor de terceros, y de tal forma, la obra es de su exclusiva autoría y tiene la titularidad sobre éste. PARÁGRAFO: en caso de queja o acción por parte de un tercero referente a los derechos de autor sobre el artículo, folleto o libro en cuestión, EL AUTOR, asumirá la responsabilidad total, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos, la Universidad Icesi actúa como un tercero de buena fe. Esta autorización, permite a la Universidad Icesi, de forma indefinida, para que en los términos establecidos en la Ley 23 de 1982, la Ley 44 de 1993, leyes y jurisprudencia vigente al respecto, haga publicación de este con fines educativos Toda persona que consulte ya sea la biblioteca o en medio electrónico podrá copiar apartes del texto citando siempre la fuentes, es decir el título del trabajo y el autor.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://purl.org/coar/access_right/c_abf2Avances en la aplicación de la ingeniería a la valoración de personas con la enfermedad de ParkinsonAdvances in the application of engineering to the assessment of people with Parkinson’s disease.bookhttp://purl.org/coar/resource_type/c_2f33Libroinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/bookTodo PúblicoParkinson DiseaseEarly DiagnosisMedical Informatics ApplicationParkinson DiseaseEarly DiagnosisMedical Informatics ApplicationT. A. L. Wren, C. Lening, S. A. Rethlefsen, and R. M. Kay, “Impact of gait analysis on correction of excessive hip internal rotation in ambulatory children with cerebral palsy: A randomized controlled trial,” Dev. Med. Child Neurol., vol. 55, no. 10, pp. 919–925, 2013, doi: 10.1111/dmcn.12184.B. Munoz, Y. J. Castano-Pino, J. David Arango Paredes, and A. Na - varro, “Automated gait analysis using a kinect camera and wavelets,” 2018 IEEE 20th Int. Conf. e-Health Networking, Appl. Serv. Heal. 2018, pp. 1–5, 2018, doi: 10.1109/HealthCom.2018.8531161.“GAITRite | World Leader in Temporospatial Gait Analysis.” ht - tps://www.gaitrite.com/ (accessed Apr. 18, 2021).“Vicon | Award Winning Motion Capture Systems.” https://www. vicon.com/ (accessed Apr. 18, 2021).J. D. Mejia-Trujillo et al., “KinectTM and Intel RealSenseTM D435 comparison: a preliminary study for motion analysis,” 2019 IEEE Int. Conf. E-Health Networking, Appl. Serv. Heal. 2019, no. Octo - ber, pp. 3–7, 2019, doi: 10.1109/HealthCom46333.2019.9009433.J. A. Albert, V. Owolabi, A. Gebel, C. M. Brahms, U. Granacher, and B. Arnrich, “Evaluation of the pose tracking performance of the azure kinect and kinect v2 for gait analysis in comparison with a gold standard: A pilot study,” Sensors (Switzerland), vol. 20, no. 18, pp. 1–22, 2020, doi: 10.3390/s20185104.A. Muro-de-la-Herran, B. García-Zapirain, and A. Méndez-Zorrilla, “Gait analysis methods: An overview of wearable and non-wearable systems, highlighting clinical applications,” Sensors (Switzerland), vol. 14, no. 2, pp. 3362–3394, 2014, doi: 10.3390/s140203362.R. A. Noble and R. White, “Visualisation of gait analysis data,” Proc. Int. Conf. Inf. Vis., vol. 2005, pp. 247–252, 2005, doi: 10.1109/ IV.2005.139.“Kinect - Windows app development.” https://developer.microsoft. com/en-us/windows/kinect/ (accessed Apr. 18, 2021).A. P. Rocha, H. Choupina, J. M. Fernandes, M. J. Rosas, R. Vaz, and J. P. S. Cunha, “Parkinson’s disease assessment based on gait analy - sis using an innovative RGB-D camera system,” 2014 36th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBC 2014, pp. 3126–3129, 2014, doi: 10.1109/EMBC.2014.6944285.J. D. Arango Paredes, B. Muñoz, W. Agredo, Y. Ariza-Araújo, J. L. Orozco, and A. Navarro, “A reliability assessment softwa - re using Kinect to complement the clinical evaluation of Parkin - son’s disease,” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, vol. 2015-Novem, pp. 6860–6863, 2015, doi: 10.1109/ EMBC.2015.7319969.M. Unser and A. Aldroubi, “A review of wavelets in biomedical applications,” Proc. IEEE, vol. 84, no. 4, pp. 626–638, 1996, doi: 10.1109/5.488704.T. Chau, “A review of analytical techniques for gait data. Part 2: Neural network and wavelet methods,” Gait Posture, vol. 13, no. 2, pp. 102–120, 2001, doi: 10.1016/S0966-6362(00)00095-3.K. Aminian, B. Najafi, C. Büla, P. F. Leyvraz, and P. Robert, “Spa - tio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes,” J. Biomech., vol. 35, no. 5, pp. 689– 699, 2002, doi: 10.1016/S0021-9290(02)00008-8.“Parallel Computing Toolbox - MATLAB.” https://www.mathwor - ks.com/products/parallel-computing.html (accessed May 17, 2022).A. Marowka, “On parallel software engineering education using python,” Educ. Inf. Technol., vol. 23, no. 1, pp. 357–372, 2018, doi: 10.1007/s10639-017-9607-0.B.-C. Wang, “DIGITAL SIGNAL PROCESSING TECHNIQUES AND APPLICATIONS IN RADAR IMAGE PROCESSING.”“Wavelet Transforms - an overview | ScienceDirect Topics.” ht - tps://www.sciencedirect.com/topics/mathematics/wavelet-trans - forms (accessed May 09, 2021).“Algoritmo para detección de vibraciones anormales en maquina - rias utilizando la transformada wavelet.” https://www.researchgate. net/publication/37613214_Algoritmo_para_deteccion_de_vibra - ciones_anormales_en_maquinarias_utilizando_la_transformada_ wavelet (accessed May 09, 2021).J. O. Smith III, Continuous wavelt transform, in Spectral audio signal processing', W3K Publishing, 2011. https://ccrma.stanford. edu/~jos/sasp/Continuous_Wavelet_Transform.htmlM. J. Lai, “Popular wavelet families and filters and their use,” in Computational Complexity: Theory, Techniques, and Applications, vol. 9781461418009, Springer New York, 2012, pp. 2168–2225.S. Zope-Chaudhari, P. Venkatachalam, and K. M. Buddhiraju, “As - sessment of distortion in watermarked geospatial vector data using different wavelets,” Geo-Spatial Inf. Sci., vol. 18, no. 2–3, pp. 124– 133, Jul. 2015, doi: 10.1080/10095020.2015.1071064.Y. J. Castaño, A. Navarro, J. D. Arango, B. E. Muñoz, J. L. Orozco, and J. Valderrama, “Gait and arm swing analysis measurements for patients diagnosed with Parkinson’s disease, using digital signal pro - cessing and Kinect,” CEUR Workshop Proc., vol. 2178, pp. 71–74, 2018.S. H. Roosta, “Parallel Processing and Parallel Algorithms,” Parallel Process. Parallel Algorithms, 2000, doi: 10.1007/978-1-4612-1220-1.M. I. Capel, A. J. Tomeu, and A. G. Salguero, “Teaching concu - rrent and parallel programming by patterns: An interactive ICT approach,” J. Parallel Distrib. Comput., vol. 105, pp. 42–52, Jul. 2017, doi: 10.1016/J.JPDC.2017.01.010.A. Igor Anatolyevich Kalmykov, Konstantin Aleksandrovich Katkov, Naumenko Daniil Olegovich and A. V. M. Bronislavovich Sarkisov, “Parallel modular technologies in digital signal processing,” J. Chem. Inf. Model., vol. 53, no. 9, pp. 1689–1699, 2013.C. J. Hughes, “Single-instruction multiple-data execution,” Syn - th. Lect. Comput. Archit., vol. 32, pp. 1–121, 2015, doi: 10.2200/ S00647ED1V01Y201505CAC032.C. Shih-Lin Chien, L. Shinn-Zong, L. Chung-Chao, H. Yu-Loong, L. Chi-Wei, Ch. Shin-Yuan, “The efficacy of quantitative gait analy - sis by the GAITRite system in evaluation of parkinsonian bradyki - nesia,”Parkinson and related Disorders, Vol. 12, No. 7, pp. 438-442; 2006. https://doi.org/10.1016/j.parkreldis.2006.04.004A. Pfister, A. M. West, S, Bronner, J. A. Noah, “Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analy - sis,” J Med Eng Technol, Vol. 38, No. 5, pp. 274, 280; 2014. doi: 10.3109/03091902.2014.909540.J. Camilo and V. Correa, “Design and Implementation of a Portable Device for Real Time Analysis of Speech of People with Parkinson’s Disease,” 2013.A. Procházka, O. Vyšata, M. Vališ, O. Tupa, M. Schätz, and V. Ma - rík, “Bayesian classification and analysis of gait disorders using ima - ge and depth sensors of Microsoft Kinect,” Digit. Signal Process. A Rev. J., vol. 47, pp. 169–177, 2015, doi: 10.1016/j.dsp.2015.05.011.O. Tupa et al., “Motion tracking and gait feature estimation for re - cognising Parkinson’s disease using MS Kinect,” Biomed. Eng. Onli - ne, vol. 14, no. 1, pp. 1–20, 2015, doi: 10.1186/s12938-015-0092-7.S. van der Walt, J. I. Schönberger, J. Nunez-Iglesias, F. Boulogne, J. D. Warner, N. Yager, E. Gouillart, T. Yu, & The Scikit-Image Con - tributors, “Scikit-image: image processing in Python, PeerJ 2:e453; 2014. https://doi.org/10.7717/peerj.453N. B. Ruparelia, “Software development lifecycle models,” ACM SIGSOFT Softw. Eng. Notes, vol. 35, no. 3, pp. 8–13, May 2010, doi: 10.1145/1764810.1764814.M. Naveenkumar and S. Domnic, “Vector Quantization based Pairwise Joint Distance Maps (VQ-PJDM) for 3D Action Recog - nition,” Procedia Comput. Sci., vol. 133, pp. 27–36, 2018, doi: 10.1016/J.PROCS.2018.07.005.T. W. Ng, T. L. Tay, and S. W. Khor, “Iris recognition using ra - pid Haar wavelet decomposition,” ICSPS 2010 - Proc. 2010 2nd Int. Conf. Signal Process. Syst., vol. 1, 2010, doi: 10.1109/ ICSPS.2010.5555246.N. Ahmadi, N. Ahmadi, and M. Nilashi, “Iris Texture Recognition based on Multilevel 2-D Haar Wavelet Decomposition and Ham - ming Distance Approach,” J. Soft Comput. Decis. Support Syst., vol. 5, no. 3, pp. 16–20, Jun. 2018, Accessed: May 16, 2022. [Online]. Available: http://jscdss.com/index.php/files/article/view/168.J. M. Redondo and F. Ortin, “A Comprehensive Evaluation of Com - mon Python Implementations,” IEEE Softw., vol. 32, no. 4, pp. 76– 84, Jul. 2015, doi: 10.1109/MS.2014.104.R. Md Saad, M. Z. Ahmad, M. S. Abu, and M. S. Jusoh, “Hamming distance method with subjective and objective weights for personnel selection,” Sci. World J., vol. 2014, 2014, doi: 10.1155/2014/865495.M. Norouzi, D. J. Fleet, and R. Salakhutdinov, “Hamming distance metric learning,” Adv. Neural Inf. Process. Syst., vol. 2, pp. 1061– 1069, 2012.P. Schober and L. A. Schwarte, “Correlation coefficients: Appro - priate use and interpretation,” Anesth. Analg., vol. 126, no. 5, pp. 1763–1768, 2018, doi: 10.1213/ANE.0000000000002864.M. Ousmer, J. Vanderdonckt, and S. Buraga, “An ontology for reasoning on body-based gestures,” Proc. ACM SIGCHI Symp. Eng. Interact. Comput. Syst. EICS 2019, Jun. 2019, doi: 10.1145/3319499.3328238.V. F. Pacheco, “Microservice Patterns and Best Practices : Explore patterns like CQRS and event sourcing to create scalable, maintai - nable, and testable microservices.,” p. 357, 2018.A. J. Fernández-García, L. Iribarne, A. Corral, J. Criado, and J. Z. Wang, “A microservice-based architecture for enhancing the user experience in cross-device distributed mashup UIs with multiple forms of interaction,” Univers. Access Inf. Soc., vol. 18, no. 4, pp. 747–770, Nov. 2019, doi: 10.1007/S10209-017-0606-0.E. Stratmann, J. Ousterhout, and S. Madan, “Integrating Long Po - lling with an MVC Web Framework.”T. Fadhilah Iskandar, M. Lubis, T. Fabrianti Kusumasari, and A. Ridho Lubis, “Comparison between client-side and server-side ren - dering in the web development,” IOP Conf. Ser. Mater. Sci. Eng., vol. 801, no. 1, 2020, doi: 10.1088/1757-899X/801/1/012136.“React – A JavaScript library for building user interfaces.” https:// en.reactjs.org/ (accessed Nov. 25, 2021).ORIGINALgarcia_paramentro_parkinson_2023.pdfgarcia_paramentro_parkinson_2023.pdfapplication/pdf5972331https://repository.icesi.edu.co/bitstreams/31a913af-0421-4f12-ae15-7f223bf08140/downloadb71ae0ef9eb9b8afc97480006f5fd3b3MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8899https://repository.icesi.edu.co/bitstreams/e45b1b22-2315-40a1-b868-82c2508a8c52/download3b6ce8e9e36c89875e8cf39962fe8920MD52LICENSElicense.txtlicense.txttext/plain1748https://repository.icesi.edu.co/bitstreams/0f67e492-7f82-4878-9d90-f757d27ac307/downloadbb9bdc0b3349e4284e09149f943790b4MD5310906/130436oai:repository.icesi.edu.co:10906/1304362025-08-12 14:28:17.996http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internationalopen.accesshttps://repository.icesi.edu.coBiblioteca Digital - Universidad Icesiadquisicion-bib@listas.icesi.edu.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 |