Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands.
Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands.
J Neuroeng Rehabil. 2021 Feb 17;18(1):36. doi: 10.1186/s12984-021-00809-3.
People with brain or neural injuries, such as cerebral palsy or spinal cord injury, commonly have joint hyper-resistance. Diagnosis and treatment of joint hyper-resistance is challenging due to a mix of tonic and phasic contributions. The parallel-cascade (PC) system identification technique offers a potential solution to disentangle the intrinsic (tonic) and reflexive (phasic) contributions to joint impedance, i.e. resistance. However, a simultaneous neurophysiological validation of both intrinsic and reflexive joint impedances is lacking. This simultaneous validation is important given the mix of tonic and phasic contributions to joint hyper-resistance. Therefore, the main goal of this paper is to perform a group-level neurophysiological validation of the PC system identification technique using electromyography (EMG) measurements.
Ten healthy people participated in the study. Perturbations were applied to the ankle joint to elicit reflexes and allow for system identification. Participants completed 20 hold periods of 60 seconds, assumed to have constant joint impedance, with varying magnitudes of intrinsic and reflexive joint impedances across periods. Each hold period provided a paired data point between the PC-based estimates and neurophysiological measures, i.e. between intrinsic stiffness and background EMG, and between reflexive gain and reflex EMG.
The intrinsic paired data points, with all subjects combined, were strongly correlated, with a range of [Formula: see text] in both ankle plantarflexors and dorsiflexors. The reflexive paired data points were moderately correlated, with [Formula: see text] in the ankle plantarflexors only.
An agreement with the neurophysiological basis on which PC algorithms are built is necessary to support its clinical application in people with joint hyper-resistance. Our results show this agreement for the PC system identification technique on group-level. Consequently, these results show the validity of the use of the technique for the integrated assessment and training of people with joint hyper-resistance in clinical practice.
脑或神经损伤(如脑瘫或脊髓损伤)患者通常有关节高阻力。由于紧张和相位贡献的混合,关节高阻力的诊断和治疗具有挑战性。平行级联(PC)系统识别技术提供了一种潜在的解决方案,可以分离关节阻抗(即阻力)的固有(紧张)和反射(相位)贡献。然而,缺乏对固有和反射关节阻抗的同时神经生理验证。鉴于关节高阻力中紧张和相位贡献的混合,这种同时验证非常重要。因此,本文的主要目标是使用肌电图(EMG)测量对 PC 系统识别技术进行组水平神经生理验证。
10 名健康人参加了这项研究。踝关节施加扰动以引发反射并允许系统识别。参与者完成了 20 个 60 秒的保持期,假设关节阻抗恒定,每个保持期的固有和反射关节阻抗的幅度在各期之间变化。每个保持期为基于 PC 的估计值和神经生理测量值(即固有刚度和背景 EMG 之间,以及反射增益和反射 EMG 之间)提供一对数据点。
所有受试者的固有配对数据点均具有很强的相关性,范围为 [公式:见正文],在踝关节跖屈肌和背屈肌中均如此。反射性配对数据点中度相关,仅在踝关节跖屈肌中为 [公式:见正文]。
必须与 PC 算法构建的神经生理基础达成一致,以支持其在关节高阻力人群中的临床应用。我们的结果表明,该组水平的 PC 系统识别技术具有这种一致性。因此,这些结果表明该技术可用于临床实践中对关节高阻力人群进行综合评估和训练的有效性。