Estimation of Upper Limb Impedance Parameters Using Recursive Least Square Estimator

• Published in: 2016 International Conference on Computer and Communication Engineering (ICCCE) pp. 144 - 148
• Main Authors: Htoon, Zaw Lay, Sidek, Shahrul Na'im, Fatai, Sado, Rashid, Muhammad Mahbubur
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-07-2016
• Subjects: Estimation; Force; Impedance; Impedance measurement; Mathematical model; neurorehabilitation; post-stroke; recursive least square estimator; Robot sensing systems; robot-assisted rehabilitation robot; upper-limb impedance parameter
• DOI: 10.1109/ICCCE.2016.41

For the past decade, researchers have developed rehabilitation robot based-therapy for post-stroke patients which goal is to complement the traditional manual therapy. However, they are still lacking in terms of measuring the human arm's impedance that neurorehabilitation therapist used to estimate before deploying a specific training regime. There are numerous assessment strategies exist to estimate the upper limb impedance parameters and movement ability post-stroke, but most of the strategies are subjective though guided by detailed description and the assessment consequence is qualitative rather than quantitative and objective. Hence, there are still remain challenges to unearth assessment strategy that can measure stroke patients' upper limb impedance parameters in a safe, cost efficient, quantitative, objective and reliable. The paper proposes appropriate mathematical model for a 3-DOF robot-assisted platform for post-stroke rehabilitation that has the ability to estimate the upper-limb mechanical impedance parameters using recursive least square estimator method. Preliminary experimental result shows that the upper-limb impedance parameters can be estimated. Therefore, these acquired outcomes could be useful in the interaction between the robot platform and patient undergoes neurorehabilitation therapy.