Rosaura Anaid Suárez-Santillán 1, Takamaru Saito 2, Marco Ceccarelli 2*
1 Institution Faculty of Health Sciences, Autonomous University of Tlaxcala, Mexico
Ciencias de la Salud Sur 11, Barrio de Guardia, 90750 Zacatelco, Tlax., México
2 Dept. of Industrial Engineering, University of Rome Tor Vergata, Italy
Via del Politecnico, 1 00133, Roma
* Corresponding author. E-mail: marco.ceccarelli@uniroma2.eu
Robotica & Management, Vol. 30, No. 1, pp. 26-31
DOI: https://doi.org/10.24193/rm.2025.1.4
Abstract: This paper presents a low-cost vision-based analysis of human walking, focusing on the evaluation using two motion capture technologies: Kinect and Inertial Measurement Units (IMU). The Kinect sensor provides a markerless, depth-based approach to motion tracking, while the IMU offers wearable motion sensing through accelerometers and gyroscopes. This integrated system improves analytical capabilities by capturing spatio-temporal gait parameters, supporting comprehensive biomechanical research. The proposed system highlights how the combination with results that can be used in the sensing devices of these technologies can offer valuable insight into human locomotion with low-cost efficient operation. A case of study is reported from laboratory experience to outline the characteristics and limits of the proposed system.
Keywords: Human Walking Analysis, Vision-Based Motion Capture, Wearable Sensors, Performance Evaluation.
References
[1] Vicon Homepage, https://www.vicon.com/hardware/ cameras/, last accessed 2025/01/20.
[2] Colyer, S.L., Evans, M., Cosker, D.P. et al.: A Review of the Evolution of Vision-Based Motion Analysis and the Integration of Advanced Computer Vision Methods Towards Developing a Markerless System. Sports Medicine – Open 4, 24, https://doi.org/10.1186/s40798-018-0139-y (2018).
[3] Bernal-Torres, M., Medellín-Castillo, H., González, J. C.: Development of a new low-cost computer vision system for human gait analysis: A case study. In: Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in Medicine. 237. 9544119231163634. 10.1177/09544119231163634 (2023).
[4] Ceccarelli, M., Avila Carrasco,C., Ottaviano, E.: Error analysis and experimental tests of CATRASYS (Cassino Tracking System), In: 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies, Nagoya, Japan, 2000, pp. 2371-2376 vol.4, doi: 10.1109/IECON.2000.972368 (2000).
[5] Varela, M.J., Ceccarelli, M., Flores P.: A kinematic characterization of human walking by using CaTraSys. In: Mechanism and Machine Theory, Vol.86, Pages 125-139, https://doi.org/10.1016/j.mechmachtheory.2014.12.006 (2015).
[6] Microsoft Homepage, Xbox 360 Kinect Sensor Manual. https://www.manualpdf.in/microsoft/xbox-360-kinect-sensor/manual, last accessed 2025/01/20.
[7] Intel Homepage, Intel-RealSense-D400-Series-Datasheet, https://cdrdv2-public.intel.com/841984/Intel-RealSense-D400-Series-Datasheet.pdf, last accessed 2025/01/20.
[8] Brambilla, C.: Azure Kinect Performance Evaluation for Human Motion and Upper Limb Biomechanical Analysis. In: HELIYON, 9, 1-31, doi:10.1016/j.heliyon.2023.e21606 (2023).
[9] Yee Vun, D.S., Bowers, R., McGarry, A., Vision-based motion capture for the gait analysis of neurodegenerative diseases: A review, In: Gait & Posture, Volume 112, Pages 95-107, ISSN 0966-6362, https://doi.org/10.1016/j.gaitpost.2024.04.029 (2024).
[10] Dimitrov, H., Bull, A.M.J., Farina, D.: High-density EMG, IMU, kinetic, and kinematic open-source data for comprehensive locomotion activities. In: Scientific Data. 10(1):789. doi: 10.1038/s41597-023-02679-x (2023).
[11] Voss, S., Joyce, J., Biskis, A., Parulekar, M., Armijo, N., Zampieri, C., Tracy, R., Palmer, A.S., Fefferman, M., Ouyang, B., Liu, Y., Berry-Kravis, E., O’Keefe, J.A.. Normative database of spatiotemporal gait parameters using inertial sensors in typically developing children and young adults. Gait Posture. 2020 Jul;80:206-213. doi: 10.1016/j.gaitpost.2020.05.010. Epub 2020 May 21. PMID: 32531757; PMCID: PMC7388584, (2020).
[12] BOSCH Sensortec Homepage, BMI160 Small, low power inertial measurement unit Datasheet. https://www.bosch-sensortec.com/media/boschsensortec/downloads/datasheets/bst-bmi160-ds000.pdf, last accessed 2025/01/20.
[13] OptiTrack Homepage, Motion Capture Cameras. https://optitrack.com/cameras/, last accessed 2025/01/20.
[14] OptiTrack Homepage, Version of Motive. https://optitrack.com/software/motive/pricing.html, last accessed 2025/01/20.