A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation
Abstract Understanding the psychophysiological state during robot-aided rehabilitation is crucial for assessing the patient experience during treatments. This paper introduces a psychophysiological estimation approach using a Fuzzy Logic inference model to assess patients’ perception of robots durin...
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| Format: | Article |
| Language: | English |
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BMC
2024-11-01
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| Series: | Journal of NeuroEngineering and Rehabilitation |
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| Online Access: | https://doi.org/10.1186/s12984-024-01501-y |
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| author | Christian Tamantini Francesca Cordella Francesco Scotto di Luzio Clemente Lauretti Benedetta Campagnola Fabio Santacaterina Marco Bravi Federica Bressi Francesco Draicchio Sandra Miccinilli Loredana Zollo |
| author_facet | Christian Tamantini Francesca Cordella Francesco Scotto di Luzio Clemente Lauretti Benedetta Campagnola Fabio Santacaterina Marco Bravi Federica Bressi Francesco Draicchio Sandra Miccinilli Loredana Zollo |
| author_sort | Christian Tamantini |
| collection | DOAJ |
| description | Abstract Understanding the psychophysiological state during robot-aided rehabilitation is crucial for assessing the patient experience during treatments. This paper introduces a psychophysiological estimation approach using a Fuzzy Logic inference model to assess patients’ perception of robots during upper-limb robot-aided rehabilitation sessions. The patients were asked to perform nine cycles of 3D point-to-point trajectories toward different targets at varying heights with the assistance of an anthropomorphic robotic arm (i.e. KUKA LWR 4+). Physiological parameters, including galvanic skin response, heart rate, and respiration rate, were monitored across ten out of forty daily sessions. This data enabled the construction of an inference model to estimate patients’ perception states. Results expressed in terms of correlation coefficients between the patient state and the increasing number of sessions. Correlation coefficients showed statistically significant strong associations: a state of heightened engagement (formerly described as “Excited”) had $$\rho = -0.73$$ ρ = - 0.73 (p-value=0.01), and a more calm and resting state (namely “Relaxed” state) had $$\rho = 0.70$$ ρ = 0.70 (p-value=0.02) with the number of sessions completed. All patients had positive interaction with the robot, initially expressing curiosity and interest that gradually shifted to a more “Relaxed” state over time. |
| format | Article |
| id | doaj-art-f8657025fcc94f58ab46500089968dfc |
| institution | Kabale University |
| issn | 1743-0003 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of NeuroEngineering and Rehabilitation |
| spelling | doaj-art-f8657025fcc94f58ab46500089968dfc2024-11-10T12:11:37ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032024-11-0121111410.1186/s12984-024-01501-yA fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitationChristian Tamantini0Francesca Cordella1Francesco Scotto di Luzio2Clemente Lauretti3Benedetta Campagnola4Fabio Santacaterina5Marco Bravi6Federica Bressi7Francesco Draicchio8Sandra Miccinilli9Loredana Zollo10Research Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di RomaResearch Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di RomaResearch Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di RomaResearch Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di RomaUnit of Rehabilitation, Fondazione Policlinico Universitario Campus Bio-Medico di RomaUnit of Rehabilitation, Fondazione Policlinico Universitario Campus Bio-Medico di RomaUnit of Rehabilitation, Fondazione Policlinico Universitario Campus Bio-Medico di RomaUnit of Rehabilitation, Fondazione Policlinico Universitario Campus Bio-Medico di RomaDepartment of Occupational and Environmental Medicine, INAILUnit of Rehabilitation, Fondazione Policlinico Universitario Campus Bio-Medico di RomaResearch Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di RomaAbstract Understanding the psychophysiological state during robot-aided rehabilitation is crucial for assessing the patient experience during treatments. This paper introduces a psychophysiological estimation approach using a Fuzzy Logic inference model to assess patients’ perception of robots during upper-limb robot-aided rehabilitation sessions. The patients were asked to perform nine cycles of 3D point-to-point trajectories toward different targets at varying heights with the assistance of an anthropomorphic robotic arm (i.e. KUKA LWR 4+). Physiological parameters, including galvanic skin response, heart rate, and respiration rate, were monitored across ten out of forty daily sessions. This data enabled the construction of an inference model to estimate patients’ perception states. Results expressed in terms of correlation coefficients between the patient state and the increasing number of sessions. Correlation coefficients showed statistically significant strong associations: a state of heightened engagement (formerly described as “Excited”) had $$\rho = -0.73$$ ρ = - 0.73 (p-value=0.01), and a more calm and resting state (namely “Relaxed” state) had $$\rho = 0.70$$ ρ = 0.70 (p-value=0.02) with the number of sessions completed. All patients had positive interaction with the robot, initially expressing curiosity and interest that gradually shifted to a more “Relaxed” state over time.https://doi.org/10.1186/s12984-024-01501-yPsychophysiological estimationRobot-aided rehabilitationPhysiological monitoringFuzzy logic |
| spellingShingle | Christian Tamantini Francesca Cordella Francesco Scotto di Luzio Clemente Lauretti Benedetta Campagnola Fabio Santacaterina Marco Bravi Federica Bressi Francesco Draicchio Sandra Miccinilli Loredana Zollo A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation Journal of NeuroEngineering and Rehabilitation Psychophysiological estimation Robot-aided rehabilitation Physiological monitoring Fuzzy logic |
| title | A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation |
| title_full | A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation |
| title_fullStr | A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation |
| title_full_unstemmed | A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation |
| title_short | A fuzzy-logic approach for longitudinal assessment of patients’ psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation |
| title_sort | fuzzy logic approach for longitudinal assessment of patients psychophysiological state an application to upper limb orthopedic robot aided rehabilitation |
| topic | Psychophysiological estimation Robot-aided rehabilitation Physiological monitoring Fuzzy logic |
| url | https://doi.org/10.1186/s12984-024-01501-y |
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