Stochastic Estimation of Arm Mechanical Impedance During Robotic Stroke Rehabilitation
| Autor: | J.J. Palazzolo, Hermano Igo Krebs, Bruce T. Volpe, M. Ferraro, Daniel V. Lynch, Neville Hogan |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
medicine.medical_specialty
Engineering Movement medicine.medical_treatment Biomedical Engineering Context (language use) Models Biological Signal Article Physical medicine and rehabilitation Electric Impedance Internal Medicine medicine Humans Computer Simulation Stroke Physical Therapy Modalities Stochastic Processes Rehabilitation business.industry General Neuroscience Stroke Rehabilitation Mechanical impedance Biomechanics Robotics medicine.disease Biomechanical Phenomena Paresis body regions Therapy Computer-Assisted Arm Robot Stress Mechanical Artificial intelligence business |
| Zdroj: | IEEE Transactions on Neural Systems and Rehabilitation Engineering. 15:94-103 |
| ISSN: | 1558-0210 1534-4320 |
| DOI: | 10.1109/tnsre.2007.891392 |
| Popis: | This paper presents a stochastic method to estimate the multijoint mechanical impedance of the human arm suitable for use in a clinical setting, e.g., with persons with stroke undergoing robotic rehabilitation for a paralyzed arm. In this context, special circumstances such as hypertonicity and tissue atrophy due to disuse of the hemiplegic limb must be considered. A low-impedance robot was used to bring the upper limb of a stroke patient to a test location, generate force perturbations, and measure the resulting motion. Methods were developed to compensate for input signal coupling at low frequencies apparently due to human–machine interaction dynamics. Data was analyzed by spectral procedures that make no assumption about model structure. The method was validated by measuring simple mechanical hardware and results from a patient's hemiplegic arm are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|