Validation of online intrinsic and reflexive joint impedance estimates using correlation with EMG measurements
Ronald C. Van 't Veld (University of Twente)
Alfred Schouten (University of Twente, TU Delft - Biomechatronics & Human-Machine Control)
Herman van der Kooij (University of Twente, TU Delft - Biomechatronics & Human-Machine Control)
Edwin van Asseldonk (University of Twente)
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Abstract
Biofeedback of online system identification estimates of intrinsic and reflexive joint impedance can be used by able-bodied subjects to voluntarily modulate their reflexive impedance independent of the intrinsic contribution. Similar to EMG-based paradigms, this could potentially be used to reduce muscle hyperreflexia in people with spasticity by facilitating spinal neuroplasticity. However, it remains unanswered if spastic participants are able to use this specific feedback to modulate their reflexes. We show, while subjects were free to co-contract, that the system identification measures have a large linear association with independently measured and processed EMG measures. The impedance estimates were obtained using an existing algorithm with incremental improvements to increase general applicability and decrease bias on the identified parameters in both simulation an experimental data. The correlation with EMG-based measures demonstrates the validity of the use of joint impedance measures within a training paradigm to reduce hyperreflexia. This could potentially improve participant comfort, increase applicability across joints, target hyperreflexia at joint level and generate faster training effects.