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Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine

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A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Rehabilitation".

Deadline for manuscript submissions: closed (14 February 2025) | Viewed by 15318

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Dr. Giovanni Morone

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Department of Life, Health and Environmental Sciences, University of L'Aquila, 67100 L'Aquila, Italy
Interests: functional recovery; robot-sassited training; robotic training; neurorehabilitation; virtual reality; motor-cognitive recovery; stroke rehabilitation; serious game therapy
Special Issues, Collections and Topics in MDPI journals

Dr. Floriana Pichiorri

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Guest Editor

Fondazione Santa Lucia, IRCCS Via Ardeatina, Roma, Italy
Interests: clinical neurophysiology; electroencephalography; brain-computer interfaces; stroke rehabilitation; neurorehabilitation; motor system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Brain disorders are a leading cause of disability worldwide. Despite advancements in acute treatment and care, the role of neurorehabilitation is still pivotal in reducing the burden on patients, care-givers, and society. In the last two decades, neurorehabilitation has revealed itself as a multidisciplinary field, with novel approaches being proposed which employ non-invasive brain stimulation, robotics, virtual reality, brain–machine interfaces, and other highly technological systems. Some of those have currently reached a sufficient level of evidence to be included in international guidelines. All in all, this technological invasion in conjunction with artificial intelligence has promoted an improvement in the methods of outcome assessment and definition of outcome predictors, which capitalize on the technological and neuroscientific advancements. Furthermore, despite these tangible advances in neurorehabilitation technology, there is an enormous amount of work to be done in terms of translationality to improve current clinical practice and to lead to a real personalized rehabilitation medicine. The scope of this Special Issue is to provide an overview of the recent advancements (with or without the use of technology and/or artificial intelligence), challenges, and perspectives on neurorehabilitation (both motor and cognitive) and novel means of outcome assessment and prediction. Researchers in this field are invited to submit original articles or reviews.

Dr. Giovanni Morone
Dr. Floriana Pichiorri
Guest Editors

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Keywords

rehabilitation
translationality
personalized medicine
brain disorders
exoskeleton
artificial intelligence
technology
assessment
robot-assisted training
brain computer interface
virtual reality

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Published Papers (7 papers)

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Research

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12 pages, 677 KiB

Open AccessArticle

The Role of Psychological Variables in Predicting Rehabilitation Outcomes After Spinal Cord Injury: An Artificial Neural Networks Study

by Marta Mascanzoni, Alessia Luciani, Federica Tamburella, Marco Iosa, Emanuela Lena, Sergio Di Fonzo, Valerio Pisani, Maria Carmela Di Lucente, Vincenzo Caretti, Lucia Sideli, Gaia Cuzzocrea and Giorgio Scivoletto

J. Clin. Med. 2024, 13(23), 7114; https://doi.org/10.3390/jcm13237114 - 25 Nov 2024

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Abstract

Background: Accurate prediction of neurorehabilitation outcomes following Spinal Cord Injury (SCI) is crucial for optimizing healthcare resource allocation and improving rehabilitation strategies. Artificial Neural Networks (ANNs) may identify complex prognostic factors in patients with SCI. However, the influence of psychological variables on rehabilitation outcomes remains underexplored despite their potential impact on recovery success. Methods: A cohort of 303 patients with SCI was analyzed with an ANN model that employed 17 input variables, structured into two hidden layers and a single output node. Clinical and psychological data were integrated to predict functional outcomes, which were measured by the Spinal Cord Independence Measure (SCIM) at discharge. Paired Wilcoxon tests were used to evaluate pre–post differences and linear regression was used to assess correlations, with Pearson’s coefficient and the Root Mean Square Error calculated. Results: Significant improvements in SCIM scores were observed (21.8 ± 15.8 at admission vs. 57.4 ± 22.5 at discharge, p < 0.001). The model assigned the highest predictive weight to SCIM at admission (10.3%), while psychological factors accounted for 36.3%, increasing to 40.9% in traumatic SCI cases. Anxiety and depression were the most influential psychological predictors. The correlation between the predicted and actual SCIM scores was R = 0.794 for the entire sample and R = 0.940 for traumatic cases. Conclusions: The ANN model demonstrated the strong impact, especially for traumatic SCI, of psychological factors on functional outcomes. Anxiety and depression emerged as dominant negative predictors. Conversely, self-esteem and emotional regulation functioned as protective factors increasing functional outcomes. These findings support the integration of psychological assessments into predictive models to enhance accuracy in SCI rehabilitation outcomes. Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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13 pages, 1377 KiB

Open AccessArticle

Quality-of-Life- and Cognitive-Oriented Rehabilitation Program through NeuronUP in Older People with Alzheimer’s Disease: A Randomized Clinical Trial

by Anthia Cristina Fabara-Rodríguez, Cristina García-Bravo, Sara García-Bravo, Isabel Quirosa-Galán, Mª Pilar Rodríguez-Pérez, Jorge Pérez-Corrales, Gemma Fernández-Gómez, Madeleine Donovan and Elisabet Huertas-Hoyas

J. Clin. Med. 2024, 13(19), 5982; https://doi.org/10.3390/jcm13195982 - 8 Oct 2024

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Abstract

(1) Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and functional impairment. The NeuronUP platform is a computer program whose main function is cognitive stimulation through three types of activities that change so that the user does not manage to learn it. This program provides opportunities to work on various domains, including activities of daily living (ADLs), social skills, and cognitive functions. The main objective of this randomized clinical trial was to assess the impact of integrating the NeuronUP platform with conventional occupational therapy to enhance or maintain cognitive, perceptual, and quality of life (QoL) abilities in people with AD compared to a control group. (2) Methods: A randomized, single-blind clinical trial was conducted. The sample was randomized using a software program, OxMar, which allowed the separation of the sample into a control group (CG) that received their conventional occupational therapy sessions and an experimental group (EG) that received therapy with NeuronUP, in addition to their conventional occupational therapy sessions. An eighteen-week intervention was conducted. (3) Results: The study included 20 participants, and significant differences were observed in most variables analyzed, indicating improvements after the intervention, particularly in measures of QoL and cognitive status. (4) Conclusions: Our findings demonstrate that an eighteen-week experimental protocol, incorporating the NeuronUP platform alongside conventional occupational therapy, led to improvements in cognitive status and QoL in older adults with AD. Thus, integrating the NeuronUP platform as a complementary tool to occupational therapy can be a valuable resource for enhancing the QoL of individuals with AD. However, due to the small sample size, further studies are needed to corroborate these findings. Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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10 pages, 520 KiB

Open AccessArticle

Nociception Coma Scale—Revised with Personalized Painful Stimulus Versus Standard Stimulation in Persons with Disorders of Consciousness: An International Multicenter Study

by Rita Formisano, Marta Aloisi, Giulia Ferri, Sara Schiattone, Anna Estraneo, Alfonso Magliacano, Enrique Noé, Maria Dolores Navarro Pérez, Bahia Hakiki, Anna Maria Romoli, Erik Bertoletti, Gloria Leonardi, Aurore Thibaut, Charlotte Martial, Olivia Gosseries, Marie Brisbois, Nicolas Lejeune, Myrtha O’Valle, Joan Ferri, Anne Frédérick, Nathan Zasler, Caroline Schnakers and Marco Iosa Show full author list Hide full author list

J. Clin. Med. 2024, 13(18), 5528; https://doi.org/10.3390/jcm13185528 - 18 Sep 2024

Cited by 1 | Viewed by 1228

Abstract

Background/Objectives: Persons with disorders of consciousness (DoCs) may perceive pain without being able to communicate their discomfort. The Nociception Coma Scale (NCS) and its revised form (NCS-R) have been proposed to assess nociception in persons with DoCs. The main aim of this international multicenter study was to confirm (or not) our preliminary results and compare the NCS-R scores of standard stimulus (NCS-R-SS) to scores of personalized painful stimuli (NCS-R-PS). A secondary aim of the study was to verify possible correlations between the NCS-R-PS and Coma Recovery Scale—Revised (CRS-R) and to estimate convergent validity. Methods: Sixty-one patients with prolonged DoCs (pDoCs) were enrolled from seven European post-acute rehabilitation centers. Responsiveness and pain perception were assessed by CRS-R and NCS-R with standard stimulus (NCS-R-SS) and personalized stimulation (NCS-R-PS). ClinicalTrials.gov Identifier: NCT06012357. Results: our results support our prior findings on the superiority and the validity of the personalized painful stimulus approach in assessment of pain in persons with DoCs in comparison with the standardized pain assessment methodology. Conclusions: A more in-depth and tailored assessment of pain perception in persons with a DoC may lead to better acknowledgment of its presence and by extension an objective foundation for more aggressive and appropriate pain management. Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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16 pages, 1331 KiB

Open AccessArticle

Harnessing Artificial Neural Networks for Spinal Cord Injury Prognosis

by Federica Tamburella, Emanuela Lena, Marta Mascanzoni, Marco Iosa and Giorgio Scivoletto

J. Clin. Med. 2024, 13(15), 4503; https://doi.org/10.3390/jcm13154503 - 1 Aug 2024

Cited by 3 | Viewed by 1191

Abstract

Background: Prediction of neurorehabilitation outcomes after a Spinal Cord Injury (SCI) is crucial for healthcare resource management and improving prognosis and rehabilitation strategies. Artificial neural networks (ANNs) have emerged as a promising alternative to conventional statistical approaches for identifying complex prognostic factors in SCI patients. Materials: a database of 1256 SCI patients admitted for rehabilitation was analyzed. Clinical and demographic data and SCI characteristics were used to predict functional outcomes using both ANN and linear regression models. The former was structured with input, hidden, and output layers, while the linear regression identified significant variables affecting outcomes. Both approaches aimed to evaluate and compare their accuracy for rehabilitation outcomes measured by the Spinal Cord Independence Measure (SCIM) score. Results: Both ANN and linear regression models identified key predictors of functional outcomes, such as age, injury level, and initial SCIM scores (correlation with actual outcome: R = 0.75 and 0.73, respectively). When also alimented with parameters recorded during hospitalization, the ANN highlighted the importance of these additional factors, like motor completeness and complications during hospitalization, showing an improvement in its accuracy (R = 0.87). Conclusions: ANN seemed to be not widely superior to classical statistics in general, but, taking into account complex and non-linear relationships among variables, emphasized the impact of complications during the hospitalization on recovery, particularly respiratory issues, deep vein thrombosis, and urological complications. These results suggested that the management of complications is crucial for improving functional recovery in SCI patients. Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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10 pages, 1169 KiB

Open AccessArticle

Dynamic Cognitive–Motor Training versus Cognitive Computer-Based Training in People with Multiple Sclerosis: A Preliminary Randomized Controlled Trial with 2-Month Follow-Up

by Marco Tramontano, Ornella Argento, Nicola Manocchio, Chiara Piacentini, Amaranta Soledad Orejel Bustos, Sara De Angelis, Michela Bossa and Ugo Nocentini

J. Clin. Med. 2024, 13(9), 2664; https://doi.org/10.3390/jcm13092664 - 1 May 2024

Cited by 6 | Viewed by 1345

Abstract

Background: Recent studies underscore the intricate relationship between cognitive and motor impairments in Multiple Sclerosis (MS), often exacerbated by CNS damage compromising neural connections. These cognitive–motor deficits contribute to reduced efficiency in daily activities and heightened risks of falls and accidents. The combination of challenging cognitive–motor training in a more ecological setting could improve cognitive functions in people with MS (PwMS). Objective: This study aims to compare the impact of dynamic cognitive–motor training versus computer-based cognitive training on overall cognitive efficiency in PwMS. Methods: Thirty-eight PwMS were recruited through the neurorehabilitation services of an Institute of research and health. Twenty-four participants were randomly assigned to the Cognitive-Motor group (CMg) and Cognitive Therapy group (CTg). Participants underwent three training sessions per week for four weeks, each lasting 50 min. The primary outcome was a comprehensive cognitive assessment using the Cognitive Impairment Index (CII), and the secondary outcomes were the Multiple Sclerosis Quality of Life Questionnaire MSQOL-54 and the Stroop Color Word Interference Test (SCWT). Results: Significant differences in the CII scores across T0, T1, and T2, as indicated by Friedman’s test (χ2(2) = 14.558, p = .001), were found in the CMg. A significant difference in the change in health subscale of the MSQOL-54 was observed when comparing the groups across T0, T1, and T2 (χ2(2) = 6.059, p = .048). There were also statistically significant differences for the emotional well-being (χ2(2) = 7.581, p = .023) and health distress (χ2(2) = 11.902, p = .003) subscales. Post hoc analysis showed a statistically significant improvement in health-related quality of life (HRQOL) for the former at T1 vs. T0 (Z = −2.502, p = .012 and for the latter at T2 vs. T0 (Z = −2.670, p = .008), respectively. Conclusions: Our results support the combination of cognitive–motor training to enhance cognitive functional outcomes and quality of life compared to computer-based cognitive training in PwMS. Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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Review

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23 pages, 5141 KiB

Open AccessReview

High-Intensity Exercise Training Impact on Cardiorespiratory Fitness, Gait Ability, and Balance in Stroke Survivors: A Systematic Review and Meta-Analysis

by Alessio Baricich, Margherita Beatrice Borg, Marco Battaglia, Salvatore Facciorusso, Stefania Spina, Marco Invernizzi, Lorenza Scotti, Lucia Cosenza, Alessandro Picelli and Andrea Santamato

J. Clin. Med. 2024, 13(18), 5498; https://doi.org/10.3390/jcm13185498 - 17 Sep 2024

Cited by 2 | Viewed by 4392

Abstract

Stroke survivors commonly face challenges such as reduced physical activity and cardiorespiratory fitness (CRF) as well as balance and gait impairments, exacerbating their disability. While high-intensity exercise interventions have demonstrated some potential, their effects on these items remain uncertain. Therefore, our study aimed to investigate the impact of high-intensity training protocols on CRF, gait ability, and balance in stroke survivor populations. Two independent investigators systematically searched five databases for relevant RCTs following the PICO model. Through a systematic review of 25 RCTs published up to 31 May 2023, including adult first-stroke survivors, comparing high-intensity exercise training versus low-to-mild or no exercises, we evaluated outcomes such as the Six-Minute Walking Test (6 MWT), peak oxygen uptake (VO2peak), Ten-Meter Walk Test (10 MWT), Berg Balance Scale (BBS), and Timed Up and Go test (TUG). The protocol was registered in PROSPERO (registration number CRD42023456773). Meta-analyses indicated significant enhancements in CRF, as measured by 6 MWT and VO2peak, following high-intensity exercise interventions. However, no significant differences were observed in BBS, 10 MWT, and TUG. Our findings underscore the potential of high-intensity exercise interventions in ameliorating CRF among stroke survivors, although further research involving standardized protocols and long-term follow-ups is imperative to optimize rehabilitation outcomes. Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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25 pages, 2350 KiB

Open AccessReview

A Scoping Review of Technology-Based Approaches for Upper Limb Motor Rehabilitation after Stroke: Are We Really Targeting Severe Impairment?

by Emma Colamarino, Giovanni Morone, Jlenia Toppi, Angela Riccio, Febo Cincotti, Donatella Mattia and Floriana Pichiorri

J. Clin. Med. 2024, 13(18), 5414; https://doi.org/10.3390/jcm13185414 - 12 Sep 2024

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Abstract

Technology-based approaches for upper limb (UL) motor rehabilitation after stroke are mostly designed for severely affected patients to increase their recovery chances. However, the available randomized controlled trials (RCTs) focused on the efficacy of technology-based interventions often include patients with a wide range of motor impairment. This scoping review aims at overviewing the actual severity of stroke patients enrolled in RCTs that claim to specifically address UL severe motor impairment. The literature search was conducted on the Scopus and PubMed databases and included articles from 2008 to May 2024, specifically RCTs investigating the impact of technology-based interventions on UL motor functional recovery after stroke. Forty-eight studies were selected. They showed that, upon patients’ enrollment, the values of the UL Fugl-Meyer Assessment and Action Research Arm Test covered the whole range of both scales, thus revealing the non-selective inclusion of severely impaired patients. Heterogeneity in terms of numerosity, characteristics of enrolled patients, trial design, implementation, and reporting was present across the studies. No clear difference in the severity of the included patients according to the intervention type was found. Patient stratification upon enrollment is crucial to best direct resources to those patients who will benefit the most from a given technology-assisted approach (personalized rehabilitation). Full article

(This article belongs to the Special Issue Increasing the Efficacy of Neurorehabilitation: From the Translationality of Technology to Personalized Rehabilitation Medicine)

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