The inflammatory, reparative and regenerative mechanisms activated in ischemic stroke patients immediately after the event cooperate in the response to injury, in the restoration of functions and in brain remodeling even weeks after the event and can be sustained by the rehabilitation treatment. Nonetheless, patients’ response to treatments is difficult to predict because of the lack of specific measurable markers of recovery, which could be complementary to clinical scales in the evaluation of patients. Considering that Extracellular Vesicles (EVs) are carriers of multiple molecules involved in the response to stroke injury, in the present study, we have identified a panel of EV-associated molecules that (i) confirm the crucial involvement of EVs in the processes that follow ischemic stroke, (ii) could possibly profile ischemic stroke patients at the beginning of the rehabilitation program, (iii) could be used in predicting patients’ response to treatment. By means of a multiplexing Surface Plasmon Resonance imaging biosensor, subacute ischemic stroke patients were proven to have increased expression of vascular endothelial growth factor receptor 2 (VEGFR2) and translocator protein (TSPO) on the surface of small EVs in blood. Besides, microglia EVs and endothelial EVs were shown to be significantly involved in the intercellular communications that occur more than 10 days after ischemic stroke, thus being potential tools for the profiling of patients in the subacute phase after ischemic stroke and in the prediction of their recovery.

Objective: To assess the benefits of neurological rehabilitation and the dose-response relationship for the treat-ment of mobility and balance in multiple sclerosis. Methods: We included studies investigating the effects of neurological rehabilitation on mobility and balance with the following eligibility criteria for inclusion: Population, People with Multiple Sclerosis (PwMS); Intervention, method of rehabilitation interventions; Comparison, experimental (specific balance intervention) vs control (no intervention/no specific balance intervention); Outcome, balance clinical scales; Study Design, randomised controlled trials. We conducted a random effects dose-response meta-analysis to assess linear trend estimations and a one stage linear mixed effects meta-regression for estimating dose-response curves. Results: We retrieved 196 studies from a list of 5020 for full text review and 71 studies (n subjects=3306) were included. One study was a cross-over and 70 studies were randomized controlled trials and the mean sample size per study was 46.5 +/- 28.6 (mean +/- SD) with a mean age of 48.3 +/- 7.8years, disease duration of 11.6 +/- 6.1years, and EDSS of 4.4 +/- 1.4points. Twenty-nine studies (40.8%) had the balance outcome as the primary outcome, while 42 studies (59.1%) had balance as secondary outcome or did not specify primary and secondary outcomes. Thirty-three trials (46.5%) had no active intervention as comparator and 38 trials (53.5%) had an active control group. Individual level data from 20 studies (n subjects=1016) were analyzed showing a medium pooled effect size for balance interventions (SMD=0.41; 95% CIs 0.22 to 0.59). Moreover, we analyzed 14 studies (n subjects=696) having balance as primary outcome and BBS as primary endpoint yielding a mean difference of 3.58 points (95% CIs 1.79 to 5.38, p<0.0001). Finally, we performed meta regression of the 20 studies showing an association between better outcome, log of intensity defined as minutes per session (B=1.26; SEB=0.51; p = 0.02) and task-oriented intervention (B=0.38; SEB=0.17; p = 0.05). Conclusion: Our analyses provide level 1 evidence on the effect of balance intervention to improve mobility. Furthermore, according to principles of neurological rehabilitation, high intensity and task-specific interventions are associated with better treatment outcomes.

BACKGROUND:The International Classification of Functioning, Disability and Health (ICF) parsimonious Generic set can provide identification of functional profiles and recovery after rehabilitation in persons post stroke. AIM:To explore concurrent validity of the ICF Generic-6_Functioning score with the Barthel Index (BI) and responsiveness after rehabilitation in persons post stroke. Further, the feasibility of applying the ICF Brief Stroke Core set in routine rehabilitation recovery was evaluated. DESIGN:Prospective study. SETTING:Inpatient rehabilitation setting. POPULATION:Persons post stroke. METHODS:The study included 71 persons post stroke (mean age 66.8 [standard deviation 14.5], mean onset 199.3 [565.3] days, BI score improvement: 17/100), N.=44 acute stroke (<3 months, stroke subacute [SA]_group) and N.=27 chronic stroke (>3 months, Stroke chronic [SC]_group). The Brief Stroke core set, including the Generic set, was used for classification at admission and at discharge using the five grade qualifiers. The median value of the groups' qualifiers on the Generic set (excluding item 850) was used to form a Functioning score (Generic-6 FS). Responsiveness was assessed with effect sizes (ES) and confidence intervals (CI). The concurrent validity of the Generic-6 FS was explored with the BI as a gold standard using Spearman's correlation coefficient. P was set at 0.05. RESULTS:The Generic-6 FS proved responsive with ES being moderate for the Generic-6 FS and the BI for the whole group (0.48, CI 0.14-0.82 and 0.67, CI -1.02--0.32 respectively). ES of the Generic-6 FS was significant only for the SA_group (0.62, CI 0.27-0.96. Correlation between the Generic-6 FS and the BI at baseline and discharge were respectively r=-0.59 and r=0.60, while correlation between change values was lower (r=0.44). The Generic-6 FS did not distinguish between the SA_group and the SC_group. Classification with the ICF brief stroke core set was feasible with 89% of the persons being classified both at admission and discharge. CONCLUSIONS:ICF classification of persons post stroke during rehabilitation recovery was feasible. The Generic-6 FS detected changes in functioning and health in persons recovered for rehabilitation after stroke and distinguished between different recovery rates of persons in the acute and chronic phase after stroke.

Background:Stroke represents the second preventable cause of death after cardiovascular disease and the third global cause of disability. In countries where national registries of the clinical quality of stroke care have been established, the publication and sharing of the collected data have led to an improvement in the quality of care and survival of patients. However, information on rehabilitation processes and outcomes is often lacking, and predictors of functional outcomes remain poorly explored. This paper describes a multicenter study protocol to implement a Stroke rehabilitation Registry, mainly based on a multidimensional assessment proposed by the Italian Society of Physical and Rehabilitation Medicine (PMIC2020), in a pilot Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation, to provide a systematic assessment of processes and outcomes and develop data-driven prediction models of functional outcomes.Methods:All patients with a diagnosis of ischemic or haemorrhagic stroke confirmed by clinical assessment, admitted to intensive rehabilitation units within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled. Measures will be taken at admission (T0), at discharge (T1), and at follow-up, 3 months (T2) and 6 months (T3) after the stroke. Assessment variables include anamnestic data, clinical and nursing complexity information and measures of body structures and function, activity and participation (PMIC2020), rehabilitation interventions, adverse events and discharge data. The modified Barthel Index will be our primary outcome. In addition to classical biostatistical analysis, learning algorithms will be cross-validated to achieve data-driven prognosis prediction models.Conclusions:This study will test the feasibility of a stroke rehabilitation registry in the Italian health context and provide a systematic assessment of processes and outcomes for quality assessment and benchmarking. By the development of data-driven prediction models in stroke rehabilitation, this study will pave the way for the development of decision support tools for patient-oriented therapy planning and rehabilitation outcomes maximization.Clinical tial registration:The registration on ClinicalTrials.gov is ongoing and under review. The identification number will be provided when the review process will be completed.

Background: Balance and gait impairments increase fall rate and injury in people with neurological disorders (PwND). The modified Dynamic Gait Index(mDGI) is a scale assessing dynamic balance during walking, however its ability in identifying Fallers and Recurrent Fallers has not been studied. Research Question: To evaluate mDGI's ability in identifying retrospective Fallers and Recurrent Fallers establishing cut-off scores for its use in clinical practice. Method: In this cross-sectional study, the number of retrospective falls and mDGI scores were collected. PwND were categorised as Non-Fallers or Fallers (falls>1) and as Recurrent Fallers(falls>2) or Non-Recurrent/NonFallers(falls<2) according to their number of retrospective falls over two months. Two generalised linear logistic models were developed using a machine learning method to detect Fallers (Model 1) and Recurrent Fallers (Model 2) based on mDGI scores. ROC curves were used to identify mDGI cut-off scores to distinguish between different fall categories. Results: 58 PwND (mean +/- standard deviation age: 63.4 +/- 12 years) including 28 people with Multiple Sclerosis, 15 people with Parkinson's disease and 15 people with Stroke were analysed. The mDGI score(median (IQR)) for Non-Fallers, Fallers, Recurrent Fallers and Non-Recurrent/Non-Fallers was respectively 50(22), 37(22), 26.5 (20.25) and 46.5(20.5)points. The cut-off to identify Fallers from Non-Fallers was 49 points(sensitivity:100 %, specificity:50 %, post-test probability with mDGI < cut-off: 53.2 %, post-test probability with mDGI > cut-off: 0%, AUC:0.68), while 29 points(sensitivity:60 %, specificity:79 %, post-test probability with mDGI < cutoff:52.1 %, post-test probability with mDGI > cut-off:16.1 %, AUC:0.70) was the best cut-off to identify Recurrent Fallers. Significance: People with mDGI score>49 points have low or minimal fall risk, while people with mDGI score<49 points should be further investigated with other scales before starting a balance-focused rehabilitation intervention. People scoring <29 points on the mDGI scale may need a fall prevention intervention, regardless of the results of other balance clinical measures.

The state of the art is still lacking an extensive analysis of which clinical characteristics are leading to better outcomes after robot-assisted rehabilitation on post-stroke patients. Prognostic machine learning-based models could promote the identification of predictive factors and be exploited as Clinical Decision Support Systems (CDSS). For this reason, the aim of this work was to set the first steps toward the development of a CDSS, by the development of machine learning models for the functional outcome prediction of post-stroke patients after upper-limb robotic rehabilitation. Four different regression algorithms were trained and cross-validated using a nested $5\times 10$ -fold cross-validation. The performances of each model on the test set were provided through the Median Average Error (MAE) and interquartile range. Additionally, interpretability analyses were performed, to evaluate the contribution of the features to the prediction. The results on the two best performing models showed a MAE of 13.6 [13.4] and 13.3 [14.8] on the Modified Barthel Index score (MBI). The interpretability analyses highlighted the Fugl-Meyer Assessment, MBI, and age as the most relevant features for the prediction of the outcome. This work showed promising results in terms of outcome prognosis after robot-assisted treatment. Further research should be planned for the development, validation and translation into clinical practice of CDSS in rehabilitation. Clinical relevance— This work establishes the premises for the development of data-driven tools able to support the clinical decision for the selection and optimisation of the robotic rehabilitation treatment.

BACKGROUND AND AIMS:Poststroke shoulder pain is a common complication. We aimed to investigate the prevalence of poststroke shoulder pain, with attention to the neuropathic component, and the relationship between poststroke shoulder pain and upper limb improvement in motor function, strength, disability, and quality of life after upper limb rehabilitation.METHODS:This is a secondary analysis of a multicenter randomized controlled trial to compare upper limb conventional or robotic rehabilitation on 224 patients enrolled in eight rehabilitation centers. We assessed poststroke shoulder pain (using the Numerical Rating Scale and the Douleur Neuropathique 4), and upper limb motor function, strength, disability, and quality of life at baseline (T0), after 30 rehabilitation sessions (T1), and three months after the end of rehabilitation (T2).RESULTS:A moderate/severe poststroke shoulder pain was reported by 28.9% of patients, while 19.6% of them showed a neuropathic component. At T0, the intensity of pain was higher in women and in patients with neglect syndrome, positively correlated with the time since stroke and disability and negatively correlated with motor function, strength, and the physical aspects of the quality of life.Moderate/severe pain and neuropathic component significantly reduced after both treatments and this reduction was maintained at T2. Finally, the intensity of pain at baseline was negatively correlated with the improvement of upper limb motor function.CONCLUSIONS:Poststroke shoulder pain negatively impact on motor performance, strength, disability, and physical aspects of the quality of life as well as on upper limb motor recovery; however, it can be reduced after a robotic or a conventional rehabilitation. Therefore, we suggest considering poststroke shoulder pain when planning the rehabilitation intervention.

Background and Purpose: Falls are a common and persistent concern among people with neurological disorders (PwND), as they frequently result in mobility deficits and may lead to loss of functional independence. This study investigated the ceiling and floor effects, internal consistency, and convergent validity of 2 patient-reported fall prevention strategy scales in PwND. Methods: This is a prospective cohort study. Two-hundred and ninety-nine PwND (111 people with multiple sclerosis, 94 people with Parkinson's disease, and 94 people with stroke) were seen for rehabilitation and assessed. The number of retrospective and prospective falls, use of walking assistive devices, scores on the Fall Prevention Strategy Survey (FPSS), Falls Behavioural Scale (FaB), and balance and mobility scales (Berg Balance Scale, Dynamic Gait Index, Timed Up and Go, 10-m walking test, and Activities-specific Balance Confidence) were analyzed. Results: Total score distributions showed negligible ceiling and floor effects for both the FPSS (ceiling: 0.3%, floor: 0.3%) and the FaB (ceiling: 0%, floor: 0%). The Cronbach α (CI) was of 0.87 (0.85-0.89) for the FPSS and 0.86 (0.84-0.88) for the FaB. In terms of convergent validity, the FPSS and FaB were moderately correlated (Spearman correlation coefficient = 0.65). Moreover, the correlations between the FPSS and FaB and balance and mobility scales ranged from 0.25 to 0.49 (P < .01). Both scales are slightly better able to distinguish between retrospective fallers/nonfallers [area under the curve, AUC (95% CI): FPSS: 0.61 (0.5-0.7); FaB: 0.60 (0.5-0.6)] compared with prospective fallers/nonfallers [AUC (95% CI): FPSS: 0.56 (0.4-0.6); FaB: 0.57 (0.4-0.6)]. Both scales accurately identified individuals who typically required the use of a walking assistive device for daily ambulation [AUC (95% CI): FPSS: 0.74 (0.7-0.8); FaB: 0.69 (0.6-0.7)]. Multiple regression analysis showed that previous falls, use of an assistive device, and balance confidence significantly predicted participants' prevention strategies (FPSS: R2 = 0.31, F(8,159) = 10.5, P < .01; FaB: R2 = 0.31, F(8,164) = 10.89, P < .01). Conclusion: The FPSS and the FaB appear to be valid tools to assess fall prevention strategies in people with neurological disorders. Both scales provide unique and added value in providing information on individual behavior for fall prevention.

Background: The minimal clinically important difference (MCID) of modified Dynamic Gait Index (mDGI) has not yet been determined for People with Neurological Disorders (PwND). Research question: To establish the MCID of the mDGI to determine clinically meaningful improvement in balance and gait in PwND. Methods: In this longitudinal study from a randomised clinical trial, 55 participants both in and outpatients with neurological disorders, received fifteen 40-minute rehabilitation sessions. Inpatients received daily treatments over a period of three weeks while outpatients received three treatments/week over a period of five weeks. An anchor-based method using percentage rating of improvement in balance (Activities Balance Confidence scale, ABC) was used to determine the MCID of mDGI. The MCID was defined as the minimum change in mDGI total score (post - pre intervention) that was needed to perceive at least a 10 % improvement on the ABC scale. A Receiver Operating Characteristic curve was used to define the cut-off for the optimal MCID of the mDGI discriminating between improved and not improved participants. Results: The MCID of the mDGI total score was 6 points and Area under the Curve was 0.64. For the mDGI time sub-scores the MCID was 2 points and Area under the Curve was 0.6. Significance: The MCID of balance and gait improvement measured by mDGI was prudently establish at >= 7 points, meaning that this is the minimum improvement score PwND need to get to perceive a clinically relevant change in their balance and gait confidence. These reference values can be a tool incorporated into clinicians daily practice to interpret mDGI change scores helping to determine whether the intervention is effective; to develop clinical tailored intervention goals and to establish meaningful perceived change in PwND.

Background The majority of stroke survivors experiences significant hand impairments, as weakness and spasticity, with a severe impact on the activity of daily living. To objectively evaluate hand deficits, quantitative measures are needed. The aim of this study is to assess the reliability, the validity and the discriminant ability of the instrumental measures provided by a robotic device for hand rehabilitation, in a sample of patients with subacute stroke. Material and methods In this study, 120 patients with stroke and 40 controls were enrolled. Clinical evaluation included finger flexion and extension strength (using the Medical Research Council, MRC), finger spasticity (using the Modified Ashworth Scale, MAS) and motor control and dexterity during ADL performance (by means of the Frenchay Arm Test, FAT). Robotic evaluations included finger flexion and extension strength, muscle tone at rest, and instrumented MAS and Modified Tardieu Scale. Subjects were evaluated twice, one day apart, to assess the test-retest reliability of the robotic measures, using the Intraclass Correlation Coefficient (ICC). To estimate the response stability, the standard errors of measurement and the minimum detectable change (MDC) were also calculated. Validity was assessed by analyzing the correlations between the robotic metrics and the clinical scales, using the Spearman’s Correlation Coefficient (r). Finally, we investigated the ability of the robotic measures to distinguish between patients with stroke and healthy subjects, by means of Mann-Whitney U tests. Results All the investigated measures were able to discriminate patients with stroke from healthy subjects ( p < 0.001). Test-retest reliability was found to be excellent for finger strength (in both flexion and extension) and muscle tone, with ICCs higher than 0.9. MDCs were equal to 10.6 N for finger flexion, 3.4 N for finger extension, and 14.3 N for muscle tone. Conversely, test-retest reliability of the spasticity measures was poor. Finally, finger strength (in both flexion and extension) was correlated with the clinical scales (r of about 0.7 with MRC, and about 0.5 with FAT). Discussion Finger strength (in both flexion and extension) and muscle tone, as provided by a robotic device for hand rehabilitation, are reliable and sensitive measures. Moreover, finger strength is strongly correlated with clinical scales. Changes higher than the obtained MDC in these robotic measures could be considered as clinically relevant and used to assess the effect of a rehabilitation treatment in patients with subacute stroke.

Objective The aims of the study were to compare mobility in multiple sclerosis, Parkinson disease, and stroke, and to quantify the relationship between mobility and participation restrictions. Design This is a multicenter cross-sectional study. Included were compliant subjects with Parkinson disease, multiple sclerosis, and stroke seen for rehabilitation, with no comorbidities interfering with mobility. Functional scales were applied to each subject to investigate gait speed (10-meter walking test), balance while maintaining body position (Berg Balance Scale), dynamic balance and mobility (Timed Up and Go and Dynamic Gait Index), and participation (Community Integration Questionnaire). Results Two hundred ninety-nine patients (111 multiple sclerosis, 94 Parkinson disease, and 94 stroke) were enrolled. Stroke had the slowest gait speed (mean gait speed = 0.9 m/sec) compared with Parkinson disease (1.1 m/sec), and multiple sclerosis (1.2 m/sec) ( P < 0.001). Multiple sclerosis was more limited than Parkinson disease and stroke in dynamic balance both in the Timed Up and Go Test (multiple sclerosis = 16.7 secs, Parkinson disease = 11.4 secs, stroke = 14.0 secs; P < 0.001) and Dynamic Gait Index (multiple sclerosis = 11.6 points, Parkinson disease = 12.9 points, stroke = 13.6 points; P = 0.03); ability to maintain balance and body position (Berg Balance Scale) was more affected in stroke and Parkinson disease than multiple sclerosis (multiple sclerosis = 42.6 points, Parkinson disease = 39.4 points, stroke = 39.7 points; P = 0.03). Balance disorders were associated with participation restrictions but not gait speed. Conclusions Neurological conditions have differing impacts on gait and balance, leading to different levels of participation restriction.

There is consistent evidence that robotic rehabilitation is at least as effective as conventional physiotherapy for upper extremity (UE) recovery after stroke, suggesting to focus research on which subgroups of patients may better respond to either intervention. In this study, we evaluated which baseline variables are associated with the response after the two approaches. This is a secondary analysis of a randomized-controlled trial comparing robotic and conventional treatment for the UE. After the assigned intervention, changes of the Fugl-Meyer Assessment UE score by ≥ 5 points classified patients as responders to treatment. Variables associated with the response were identified in a univariate analysis. Then, variables independently associated with recovery were investigated, in the whole group, and the two groups separately. A sample of 190 patients was evaluated after the treatment; 121 were responders. Age, baseline impairment, and neglect were significantly associated with worse response to the treatment. Age was the only independently associated variable (OR 0.967, p = 0.023). Considering separately the two interventions, age remained negatively associated with recovery (OR 0.948, p = 0.013) in the conventional group, while none of the variables previously identified were significantly associated with the response to treatment in the robotic group. We found that, in our sample, age is significantly associated with the outcome after conventional but not robotic UE rehabilitation. Possible explanations may include an enhanced positive attitude of the older patients towards technological training and reduced age-associated fatigue provided by robotic-assisted exercise. The possibly higher challenge proposed by robotic training, unbiased by the negative stereotypes concerning very old patients’ expectations and chances to recover, may also explain our findings. NCT02879279.

Objectives: Treatment for progressive multiple sclerosis (pMS) is a key area of research. To date, whether MS type and the rehabilitation setting are associated with worse or better response to rehabilitation is unclear. We aimed to understand the association between balance and MS type, in/outpatient treatment and specificity of the intervention. Methods: We assessed 150 people with MS before and after in/outpatient rehabilitation. The Berg Balance Scale (BBS) was used to discriminate between responders (>= +3-point improvement in BBS score; a clinically meaningful improvement) and non-responders to specific or non-specific balance rehabilitation. Factors associated with balance were analyzed by univariate and multivariable logistic regression analyses, estimating odds ratios (ORs) and 95% confidence intervals (CIs). Results: Balance improved after rehabilitation: median (quartile 1 [Q1]-Q3) BBS score pre- and post-rehabilitation of 49 (45-53) and 52 (47-55) (P < 0.001). Univariate logistic analysis revealed a clinically meaningful improvement in balance associated with pMS (OR 2.21 [95% CI 1.09-4.05]), inpatient therapy (0.41 [0.19-0.84]), using a walking aid (1.68 [1.06-2.69]), and low baseline BBS score (0.86 [0.81-0.92]). On multivariable analysis, probability of improvement was similar for participants with pMS and the relapsing-remitting form but was associated with low baseline BBS score and specific treatment (OR 0.81 [95% CI 0.74-0.89] and 5.66 [1.79-21.5]). Conclusion: A clinically meaningful improvement in balance was more likely when MS individuals with moderate to high disability had specific exercises targeting balance, but MS type did not influence the outcome. (C) 2019 Elsevier Masson SAS. All rights reserved.

The Publisher regrets that this article is an accidental duplication of an article that has already been published, https://doi.org/10.1016/j.msard.2019.101464. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Background: Falls, mobility impairments and lack of social support lead to participation restrictions in people with neurological conditions. The aim of this multicenter, single blinded randomized controlled trial was to test whether an educational program focusing on fall prevention and safe mobility reduces falls and increases social participation among people with neurological conditions. Methods: Ninety people with Stroke (n = 25), multiple sclerosis (n = 33) and Parkinson disease (n = 32), median age 63 (31-89), were randomized. A permuted block algorithm stratified by field center was used to allocate participants to an education group (EG, n = 42) consisting of an educational program focused on fall prevention and tailored balance exercises and a control group (CG, n = 48) receiving usual treatments. After baseline assessment, each participants was followed for 6 months with telephone contacts by blinded interviewers. Being fallers (> 1 fall) and time to become a faller were used as primary outcomes. Community Integration Questionnaire (CIQ) and Instrumental Activities of Daily Living (IADL) scales assessed treatment effects on social integration and daily living activities. Results: Over a median (Interquartile Range) follow-up of 189 (182-205) days, [EG = 188 (182-202), CG = 189 (182-209)] fallers were 10 in the CG and 11 in the EG (hazard ratio 0.95, 95% confidence interval (CI) 0.45 to 2.5; P = 0.94). At follow-up the EG scored significantly better than CG on the CIQ (+1.7 points, CI: 0.1 to 3.3) and IADL (+2.2 points, CI: 0.4 to 4.0). Conclusions: This educational program did not reduce the risk of falls but it improved the ability to carry out activities of daily living and decreased participation restrictions in people with neurological conditions.

•Arm function improved in persons with MS after virtual reality serious games.•Both arms improved but only the treated arm reached a statistical significance.•Both 9 Hole Peg Test and Box & Block Test should be used as arm measures in MS.

Background: The recent exponential growth of Digital Health (DH) in the healthcare system provides a crucial transformation in healthcare, answering to alarming threats related to the increasing number of Chronic Neurological Diseases (CNDs). New long-term integrated DH-care approaches, including rehabilitation, are warranted to address these concerns. Methods: The Human Empowerment Aging and Disability (HEAD) rehabilitation program, a new long-term integrated care including DH-care system, was evaluated in terms of efficiency and patient-reported outcome measures (PROMs) in 107 CND patients (30 with Parkinson's Disease, PD; 32 with Multiple Sclerosis, MS; 45 with stroke in chronic stage). All participants followed 1-month of HEAD rehabilitation in clinic (ClinicHEAD: 12 sessions, 3/week), then 1:3 patient was consecutively allocated to 3-months telerehabilitation at home (HomeHEAD: 60 sessions, 5/week). Efficiency (i.e., adherence, usability, and acceptability) and PROMs (i.e., perceived functioning in real-world) were analyzed. Results: The rate of adherence to HEAD treatment in clinic (≥90%) and at home (77%) was high. Usability of HEAD system was judged as good (System Usability Scale, median 70.00) in clinic and even more at home (median 80.00). Similarly, administering the Technology Acceptance Model 3 questionnaire we found high scores both in clinic/at home (Usefulness, mean 5.39 ± 1.41 SD/mean 5.33 ± 1.29 SD; Ease of use, mean 5.55 ± 1.05 SD/ mean 5.45 ± 1.17 SD, External Control, mean 4.94 ± 1.17 SD/mean 5.07 ± 1.01 SD, Relevance, mean 5.68 ± 1.29 SD/mean 5.70 ± 1.13 SD and Enjoyment, mean 5.70 ± 1.40 SD/mean 6.01 ± 1.08 SD). After ClinicHEAD, participation and autonomy in daily routine was maintained or even ameliorated (PD and stroke > MS). Whereas, increased functionality and participation in the MS group was found only after HomeHEAD intervention. Discussion: Our results suggest that a tele-health-based approach is both feasible and efficient in providing rehabilitation care to CNDs from clinic to home. Increasing and maintaining participation as well as autonomy in daily routine are promising findings that open up scenarios for the continuity of care at home through DH-care for CNDs.