Introduction. Mobilization and Stimulation of Neuromuscular Tissue (MaSoNT) is a newly-invented technique that aims to trigger functional recovery in stroke patients. This is the first study that applies an intervention with MaSoNT in a patient's hemiplegic hand. The purpose was to investigate the effects of a MaSoNT intervention and to prove the safety of the technique. Methods. A case study is provided. The patient was a male stroke survivor, aged 71, who underwent a cerebrovascular accident a week before the intervention. He presented zero voluntary movement in the hemiplegic arm and some sensory impairment. The patient had had neither pain nor spasticity before the intervention. The intervention was standard upper limb therapy performed twice per week and MaSoNT application for 15 minutes, 5 times per week. The total duration of the intervention was 3 weeks. The following measurement tools were used: Modified Ashworth Scale, Motricity index Arm Score, Motor Assessment Scale items 6, 7, and 8, Thumb Localization Test, Nottingham Sensory Assessment. Results. The patient demonstrated both motor and sensory improvements by the end of the experiment. Pain and spasticity remained absent. Conclusions. The study possibly proves that MaSoNT is a safe technique to apply in a hemiplegic hand. Moreover, it could lead to functional recovery, although further research is mandated.

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Objective Stroke is a significant cause of disability, rendering patients with inability to perform activities of daily living due to lack of functional recovery. Precise prognosis in the early stage after stroke could enable realistic goal-setting and efficient resources allocation. Prediction algorithms have been tested and validate in the past, but they were using neurological biomarkers, thus they were time-consuming, difficult to apply, expensive and dangerous. The aim of this study was to create a new prediction algorithm that would not utilize any biomarkers. Methods 127 stroke patients prospectively enrolled at day 3 after their stroke (mean age: 71, males: 84, females: 43). First, a sum of shoulder abduction and finger extension (SAFE) MRC score was graded at day 3. Secondly, a binarized response was marked by the MaSoNT’s basic application on the upper-limb. Third, the NIHSS score was assessed. All data from the patients were included in a Classification and Regression Tree analysis to predict upper limb function 3 months poststroke according to the Action Research Arm Test score at week 12. Results The CART analysis produced that combines three different scores in order to predict upper-limb recovery: the SAFE score, MaSoNT’s application response and the NIHSS. The overall correct prediction of the new algorithm is 69% which is lower than previous algorithms, though not significantly. Conclusion This study offers basic data to support the validity of the APRAHL algorithm. The new algorithm is faster and easier, but less accurate than the previous similarly-designed ones. Future studies are necessary to generalize and validate APRAHL.