Background: This study combined neuromechanical modeling analysis, muscle tone measurement from mechanical indentation and electrical impedance myography to assess the neural and peripheral contribution to spasticity post stroke at wrist joint. It also investigated the training effects and explored the underlying mechanism of radial extracorporeal shock wave (rESW) on spasticity.Methods: People with first occurrence of stroke were randomly allocated to rESW intervention or control group. The intervention group received one session of rESW therapy, followed by routine therapy which was the same frequency and intensity as the control group. Outcome measures were: (1) NeuroFlexor method measured neural component (NC), elastic component (EC) and viscosity component (VC), and (2) myotonometer measured muscle tone (F) and stiffness (S), (3) electrical impedance myography measured resistance (R), reactance (X) and phase angle (θ); (4) modified Asworth scale; (5) Fugl Meyer Upper limb scale. All outcome measures were recorded at baseline, immediately post rESW and at 1-week follow-up. The differences between the paretic and non-paretic side were assessed by t-test. The effectiveness of rESW treatment were analyzed by repeated-measures one-way analysis of variance (ANOVA) at different time points.Results: Twenty-seven participants completed the study. NC, EC, and VC of the Neuroflexor method, F and S from myotonometer were all significantly higher on the paretic side than those from the non-paretic side. R, X, and θ from electrical impedance were significantly lower on the paretic side than the non-paretic side. Immediately after rESW intervention, VC, F, and S were significantly reduced, and X was significantly increased. The clinical scores showed improvements immediate post rESW and at 1-week follow-up.Conclusions: The observed changes in upper limb muscle properties adds further support to the theory that both the neural and peripheral components play a role in muscle spasticity. ESW intervention may be more effective in addressing the peripheral component of spasticity in terms of muscle mechanical properties changes. The clinical management of post stroke spasticity should take into consideration of both the neural and non-neural factors in order to identify optimal intervention regime.

Post-stroke spasticity seriously affects patients’ quality of life. Spasticity is considered to involve both neural and non-neural factors. Current clinical scales, such as the Modified Ashworth Scale and the Modified Tardieu Scale, lack reliability and reproducibility. These scales are also unable to identify the neural and non-neural contributions to spasticity. Surface electromyography and biomechanical and myotonometry measurement methods for post-stroke spasticity are discussed in this report. Surface electromyography can provide neural information, while myotonometry can estimate muscular properties. Both the neural and non-neural contributions can be estimated by biomechanical measurement. These laboratory methods can quantitatively assess spasticity. They can provide more valuable information for further study on treatment and rehabilitation than clinical scales.

This study aims to quantify passive muscle stiffness of spastic wrist flexors in stroke survivors using shear wave elastography (SWE) and to correlate with neural and non-neural contributors estimated from a biomechanical model to hyper-resistance measured during passive wrist extension. Fifteen hemiplegic individuals after stroke with Modified Ashworth Scale (MAS) score larger than one were recruited. SWE were used to measure Young's modulus of flexor carpi radialis muscle with joint from 0° (at rest) to 50° flexion (passive stretch condition), with 10° interval. The neural (NC) and non-neural components i.e., elasticity component (EC) and viscosity component (VC) of the wrist joint were analyzed from a motorized mechanical device NeuroFlexor® (NF). Combining with a validated biomechanical model, the neural reflex and muscle stiffness contribution to the increased resistance can be estimated. MAS and Fugl-Meyer upper limb score were also measured to evaluate the spasticity and motor function of paretic upper limb. Young's modulus was significantly higher in the paretic side of flexor carpi radialis than that of the non-paretic side ( p < 0.001) and it increased significantly from 0° to 50° of the paretic side ( p < 0.001). NC, EC, and VC on the paretic side were higher than the non-paretic side ( p < 0.05). There was moderate significant positive correlation between the Young's Modulus and EC ( r = 0.565, p = 0.028) and VC ( r = 0.645, p = 0.009) of the paretic forearm flexor muscle. Fugl-Meyer of the paretic forearm flexor has a moderate significant negative correlation with NC ( r = −0.578, p = 0.024). No significant correlation between MAS and shear elastic modulus or NF components was observed. This study demonstrated the feasibility of combining SWE and NF as a non-invasive approach to assess spasticity of paretic muscle and joint in stroke clinics. The neural and non-neural components analysis as well as correlation findings of muscle stiffness of SWE might provide understanding of mechanism behind the neuromuscular alterations in stroke survivors and facilitate the design of suitable intervention for them.

Purpose This study aimed to translate the English version of the Action Research Arm Test (ARAT) into Chinese and to evaluate the initial validation of the Chinese version (C-ARAT) in patients with a first stroke. Methods An expert group translated the original ARAT from English into Chinese using a forward-backward procedure. Forty-four patients (36 men and 8 women) aged 22–80 years with a first stroke were enrolled in this study. The participants were evaluated using 3 stroke-specific outcome measures: C-ARAT, the upper extremity section of the Fugl–Meyer assessment (UE-FMA), and the Wolf Motor Function Test (WMFT). Internal consistency was analysed using Cronbach's α coefficients and item-scale correlations. Concurrent validity was determined using Spearman's rank correlation coefficients. Floor and ceiling effects were considered to be present when more than 20% of patients fell outside the preliminarily set lower or upper boundary, respectively. Results The C-ARAT items yielded excellent internal consistency, with a Cronbach's α of 0.98 (p < 0.001) and item-total correlations ranging from 0.727 to 0.948 (p < 0.001). The C-ARAT exhibited good-to-excellent correlations with the UE-FMA and WMFT functional ability (WMFT-FA) scores, with respective ρ values of 0.824 and 0.852 (p < 0.001), and an excellent negative correlation with the WMFT performance time (WMFT-time), with a ρ value of -0.940 (p < 0.001). The C-ARAT subscales generally exhibited good-to-excellent correlations with stroke-specific assessments, with ρ values ranging from 0.773 to 0.927 (p < 0.001). However, the gross subscale exhibited moderate-to-good correlations with the UE-FMA and WMFT-FA scores, with respective ρ values of 0.665 and 0.720 (p < 0.001). No significant floor effect was observed, and a significant ceiling effect was observed only on the WMFT-time. Conclusions The C-ARAT demonstrated excellent internal consistency and good-to-excellent concurrent validity. This test could be used to evaluate upper extremity function in stroke patients without cognitive impairment.

Purpose To detect the responsiveness and predictive ability of the Chinese version Action Research Arm Test (C-ARAT) in participants within the first 3 months after cerebral infarction. Methods Ninety-seven individuals (75 men, mean age 59.87 ± 10.94 years) with a first cerebral infarction were enrolled in this study. The participants were evaluated by two outcome measures: C-ARAT and the Barthel Activities of Daily Living Index (BI) at five time points: 0D, 3W, 3M, 6M and 1Y after enrolment. The standardised response mean (SRM) and the Wilcoxon signed rank test were used to analyse responsiveness. Predictive validity was determined by using Spearman's rank correlation coefficients. The predicted performance of C-ARAT on activities of daily living (ADLs) was measured by linear regression model. Floor and ceiling effects were estimated by counting the proportion of subjects falling outside the 5% lower or upper boundary, respectively. Results The C-ARAT showed moderate to large responsiveness in detecting changes over time (SRM = 0.58–0.84). The C-ARAT subscales showed small to large responsiveness (SRM = 0.44–0.90). The C-ARAT at 0D showed moderate to good correlation with the BI scores at 3W, 3M and 6M (ρ = 0.561–0.624, p < 0.001), and exhibited fair correlation with the BI score 1Y after enrolment (ρ = 0.384, p < 0.05). C-ARAT was a good predictor (adjusted R2 = 0.185–0.249) of BI within 3M follow-up. The C-ARAT total score showed a notable floor effect at 0D and 3W and a notable ceiling effect at 3M, 6M and 1Y. Conclusion The results of this study support the use of the C-ARAT as a measurement of upper extremity function in individuals with a first cerebral infarction.