The motivation of patients enrolled in physical rehabilitation programs may significantly contribute to ultimate outcomes.

Robotic rehabilitation affords a significantly higher number of repetitions per treatment session keeping patients motivated. This approach consists of a robotic device being used as an interface to a computer game. This virtual environment enhances patient’s attention, turning physical effort to an engaging activity.

Since robotic devices are coupled to computers and sensors, there comes up the ability to store and analyze the motor behavior of patients during sessions for the detection of potential patterns related to particular pathologies. However, despite of this rich potential of data analysis, a lack of such practices is still quite noticeable, and is just starting to be filled, as more related work, concerning data, arise.

This project encompasses Data Science and Knowledge Discoery strategies over the performance of patients enrolled in physical rehabilitation programs, under the rehabilitation robotics paradigm. Check the video below for an overview of the pilot project, or check the publications section for specific details.

Publications

C. B. Moretti, D. J. Edwards, T. Hamilton, M. Cortes, A. R. Peltz, J. L. Chang,; A. C. B. Delbem, B. T. Volpe and H. I. Krebs, “Robotic Kinematic measures of the arm in chronic Stroke: part 1 - Motor Recovery patterns from tDCS preceding intensive training”. Bioelectronic Medicine, v. 7, p. 20, 2021.

C. B. Moretti, T. Hamilton, D. J. Edwards, A. R. Peltz, J. L. Chang, M. Cortes, A. C. B. Delbem, B. T. Volpe and H. I. Krebs, “Robotic Kinematic measures of the arm in chronic Stroke: part 2 - strong correlation with clinical outcome measures”. Bioelectronic Medicine, v. 7, p. 21, 2021.

C. B. Moretti, A. C. B. Delbem and H. I. Krebs, “Human-Robot Interaction: Kinematic and Kinetic Data Analysis Framework,” 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), New York City, 2020, p. 235.

C. B. Moretti, R. C. Joaquim, T. T. Terranova, L. R. Battistella, S. Mazzoleni and G. A. P. Caurin, “Knowledge Discovery strategy over patient performance data towards the extraction of hemiparesis-inherent features: A case study,” 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), Singapore, 2016, pp. 717-722.

C. B. Moretti, R. C. Joaquim, G. A. P. Caurin, H. I. Krebs and J. Martins, “Knowledge discovery, rehabilitation robotics, and serious games: Examining training data,” 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, Sao Paulo, 2014, pp. 567-572.

Moretti, C. B. (2016). Análise de grandezas cinemáticas e dinâmicas inerentes à hemiparesia através da descoberta de conhecimento em bases de dados. Master’s Dissertation, Escola de Engenharia de São Carlos, University of São Paulo, São Carlos.