Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease
Background: This paper aims to complement the latest contribution in the literature that provides estimates of physiological parameters of a dynamic model for the elbow time profile during walking while linking them to a neurodegenerative disorder (Parkinsons’s disease) characterized by motor sympto...
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2025-01-01
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| author | Luca Pietrosanti Giovanni Saggio Martina Patera Antonio Suppa Franco Giannini Cristiano Maria Verrelli |
| author_facet | Luca Pietrosanti Giovanni Saggio Martina Patera Antonio Suppa Franco Giannini Cristiano Maria Verrelli |
| author_sort | Luca Pietrosanti |
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| description | Background: This paper aims to complement the latest contribution in the literature that provides estimates of physiological parameters of a dynamic model for the elbow time profile during walking while linking them to a neurodegenerative disorder (Parkinsons’s disease) characterized by motor symptoms. An upper limb model is here proposed in which an active contractile element is included within a model, viewing the arm as a double pendulum system and muscles as represented by a Kelvin–Voight system. All model parameters characterizing both the shoulder and the elbow of each subject are estimated via a gradient-like identifier whose exponential convergence properties are determined by a non-anticipative Lyapunov function, ensuring robustness features. Methods: Joint angle data from different walking subjects (healthy subjects and patients with Parkinson’s disease) have been recorded using an IMU sensor system and compared with the joint angles obtained by means of the proposed model, which was adapted to each subject using available anthropometric knowledge and relying on the estimated parameters. Results: Experiments show that the reconstruction of shoulder and elbow time profiles can be definitely achieved through the proposed procedure with the estimated stiffness parameters turning out to constitute objective and quantitative indices of muscle stiffness (as a pivotal symptom of the pathology), which are able to track changes due to the therapy. Conclusions: The same dynamic model is actually able to capture the main features of the upper limb movement of both (healthy and pathological) walking subjects, with its parameters, in turn, characterizing the nature and progress of the pathology. |
| format | Article |
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| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj-art-e48667ada33249b59a0ab7c73f06a3cb2025-01-24T13:20:21ZengMDPI AGApplied Sciences2076-34172025-01-0115266810.3390/app15020668Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s DiseaseLuca Pietrosanti0Giovanni Saggio1Martina Patera2Antonio Suppa3Franco Giannini4Cristiano Maria Verrelli5Electronic Engineering Department, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, ItalyElectronic Engineering Department, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, ItalyDepartment of Human Neurosciences, Sapienza University of Rome, Viale dell’Università, 30, 00185 Rome, ItalyDepartment of Human Neurosciences, Sapienza University of Rome, Viale dell’Università, 30, 00185 Rome, ItalyElectronic Engineering Department, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, ItalyElectronic Engineering Department, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, ItalyBackground: This paper aims to complement the latest contribution in the literature that provides estimates of physiological parameters of a dynamic model for the elbow time profile during walking while linking them to a neurodegenerative disorder (Parkinsons’s disease) characterized by motor symptoms. An upper limb model is here proposed in which an active contractile element is included within a model, viewing the arm as a double pendulum system and muscles as represented by a Kelvin–Voight system. All model parameters characterizing both the shoulder and the elbow of each subject are estimated via a gradient-like identifier whose exponential convergence properties are determined by a non-anticipative Lyapunov function, ensuring robustness features. Methods: Joint angle data from different walking subjects (healthy subjects and patients with Parkinson’s disease) have been recorded using an IMU sensor system and compared with the joint angles obtained by means of the proposed model, which was adapted to each subject using available anthropometric knowledge and relying on the estimated parameters. Results: Experiments show that the reconstruction of shoulder and elbow time profiles can be definitely achieved through the proposed procedure with the estimated stiffness parameters turning out to constitute objective and quantitative indices of muscle stiffness (as a pivotal symptom of the pathology), which are able to track changes due to the therapy. Conclusions: The same dynamic model is actually able to capture the main features of the upper limb movement of both (healthy and pathological) walking subjects, with its parameters, in turn, characterizing the nature and progress of the pathology.https://www.mdpi.com/2076-3417/15/2/668upper-limb swing modelingshoulder and elbow anglesstiffness identificationcontractile elementParkinson’s disease |
| spellingShingle | Luca Pietrosanti Giovanni Saggio Martina Patera Antonio Suppa Franco Giannini Cristiano Maria Verrelli Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease Applied Sciences upper-limb swing modeling shoulder and elbow angles stiffness identification contractile element Parkinson’s disease |
| title | Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease |
| title_full | Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease |
| title_fullStr | Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease |
| title_full_unstemmed | Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease |
| title_short | Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease |
| title_sort | modeling of shoulder elbow movement with exponential parameter identification during walking gaits for healthy subjects and patients with parkinson s disease |
| topic | upper-limb swing modeling shoulder and elbow angles stiffness identification contractile element Parkinson’s disease |
| url | https://www.mdpi.com/2076-3417/15/2/668 |
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