Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges

Clinical study on the safety and feasibility of AiWalker-K for lower limbs exercise rehabilitation in children with cerebral palsy

BACKGROUND

Robotic-assisted gait training (RAGT) devices are effective for children with cerebral palsy (CP). Many RAGT devices have been created and put into clinical rehabilitation treatment. Therefore, we aimed to investigate the safety and feasibility of a new RAGT for children with CP.

METHODS

This study is a cross-over design with 23 subjects randomly divided into two groups. The occurrence of adverse events and changes in heart rate and blood pressure were recorded during each AiWalker-K training. Additionally, Gross Motor Function Measure-88 (GMFM-88), Pediatric Balance Scale (PBS), 6 Minutes Walking Test (6MWT), Physiological Cost Index, and Edinburgh Visual Gait Score (EVGS) were used to assess treatment, period, carry-over, and follow-up effects in this study.

RESULTS

Adverse events included joint pain, skin pain, and injury. Heart rate and blood pressure were higher with the AiWalker-K compared to the rest (P < 0.05), but remained within safe ranges. After combined treatment with AiWalker-K and routine rehabilitation treatment, significant improvements in 6MWT, GMFM-88 D and E, PBS, and EVGS were observed compared to routine rehabilitation treatment alone (P < 0.05).

CONCLUSIONS

Under the guidance of experienced medical personnel, AiWalker-K can be used for rehabilitation in children with CP.

Editorial: Immersive media in connected health-volume II

Immersive media, particularly Extended Reality (XR), is at the forefront of revolutionizing the healthcare industry. Healthcare provides XR with "silver bullet" use cases that add value and societal effect to the technology. Healthcare interventions frequently require imaging or visualization to be applied correctly, and the sensation of presence that XR can provide is crucial as a training aid for healthcare learners. From anatomy to surgical training, multimodal immersion in the reality of a medical situation increases the impact of an XR resource compared to the usual approach. Thus, healthcare has become a specialized focus for the immersive media sector, with a multitude of development and research underway. This research subject, which followed on from the previous one, yielded an eclectic group of works spanning the gamut of immersive media applications in healthcare. The underlying theme in these works remains a consistent focus on calibrating, validating, verifying, and standardizing procedures, instruments, and technologies in order to constantly rigorously streamline the means and materials that will integrate immersive technologies in healthcare. In that spirit, we share the findings from this research topic as a motivator for rigorous and evidence-based use of immersive media in digital and connected health.

Recent Advances in Biomimetics for the Development of Bio-Inspired Prosthetic Limbs

Recent advancements in biomimetics have spurred significant innovations in prosthetic limb development by leveraging the intricate designs and mechanisms found in nature. Biomimetics, also known as "nature-inspired engineering", involves studying and emulating biological systems to address complex human challenges. This comprehensive review provides insights into the latest trends in biomimetic prosthetics, focusing on leveraging knowledge from natural biomechanics, sensory feedback mechanisms, and control systems to closely mimic biological appendages. Highlighted breakthroughs include the integration of cutting-edge materials and manufacturing techniques such as 3D printing, facilitating seamless anatomical integration of prosthetic limbs. Additionally, the incorporation of neural interfaces and sensory feedback systems enhances control and movement, while technologies like 3D scanning enable personalized customization, optimizing comfort and functionality for individual users. Ongoing research efforts in biomimetics hold promise for further advancements, offering enhanced mobility and integration for individuals with limb loss or impairment. This review illuminates the dynamic landscape of biomimetic prosthetic technology, emphasizing its transformative potential in rehabilitation and assistive technologies. It envisions a future where prosthetic solutions seamlessly integrate with the human body, augmenting both mobility and quality of life.

Robotic systems for upper-limb rehabilitation in multiple sclerosis: a SWOT analysis and the synergies with virtual and augmented environments

The robotics discipline is exploring precise and versatile solutions for upper-limb rehabilitation in Multiple Sclerosis (MS). People with MS can greatly benefit from robotic systems to help combat the complexities of this disease, which can impair the ability to perform activities of daily living (ADLs). In order to present the potential and the limitations of smart mechatronic devices in the mentioned clinical domain, this review is structured to propose a concise SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of robotic rehabilitation in MS. Through the SWOT Analysis, a method mostly adopted in business management, this paper addresses both internal and external factors that can promote or hinder the adoption of upper-limb rehabilitation robots in MS. Subsequently, it discusses how the synergy with another category of interaction technologies - the systems underlying virtual and augmented environments - may empower Strengths, overcome Weaknesses, expand Opportunities, and handle Threats in rehabilitation robotics for MS. The impactful adaptability of these digital settings (extensively used in rehabilitation for MS, even to approach ADL-like tasks in safe simulated contexts) is the main reason for presenting this approach to face the critical issues of the aforementioned SWOT Analysis. This methodological proposal aims at paving the way for devising further synergistic strategies based on the integration of medical robotic devices with other promising technologies to help upper-limb functional recovery in MS.

Therapeutic robots for post-stroke rehabilitation

Stroke is a prevalent, severe, and disabling health-care issue on a global scale, inevitably leading to motor and cognitive deficits. It has become one of the most significant challenges in China, resulting in substantial social and economic burdens. In addition to the medication and surgical interventions during the acute phase, rehabilitation treatment plays a crucial role in stroke care. Robotic technology takes distinct advantages over traditional physical therapy, occupational therapy, and speech therapy, and is increasingly gaining popularity in post-stroke rehabilitation. The use of rehabilitation robots not only alleviates the workload of healthcare professionals but also enhances the prognosis for specific stroke patients. This review presents a concise overview of the application of therapeutic robots in post-stroke rehabilitation, with particular emphasis on the recovery of motor and cognitive function.

Perspectives in Wearable Systems in the Human-Robot Interaction (HRI) Field

Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human-machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system's volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development.

NeBULA: A Standardized Protocol for the Benchmarking of Robotic-based Upper Limb Neurorehabilitation

The use of robotic technologies in neurorehabilitation is growing, because they allow highly repeatable exercise protocols and patient-tailored therapies. However, there is a lack of objective methods for assessing these technologies, which makes it difficult to determine their value in rehabilitation settings. While there exist many outcome measurements for motor assessment from a clinical standpoint (such as the Fugl-Meyer scale), the evaluation of performance and clinical benefits of technology for rehabilitation still lacks a standardized approach from a technical standpoint.In this work, we describe NeBULA (Neuromechanical Biomarkers for Upper Limb Assessment), a benchmarking platform for evaluating robotic technology for upper limb neurorehabilitation. By utilizing standardized neuromechanical biomarkers, NeBULA aims at providing a groundwork for assessing and comparing neurorehabilitation robots. We describe its implementation and preliminary results assessing a novel upper limb exoskeleton.Clinical Relevance- Standardized evaluation of neurorehabilitation robots can lead to better patient outcomes, optimizing resources by identifying the most effective technology and by boosting their use in clinical practice. This would provide quantitative and objective information to complement clinical motor evaluation - preventing suboptimal treatments and ensuring that patients receive personalized care. It can also facilitate the transfer of technologyto clinics, identifying the most promising ones for further investment and research.

Low Complex CORDIC-based Hand Movement Recognition Design Methodology for Rehabilitation and Prosthetic Applications

Hand movement recognition using Electromyography (EMG) signals have gained much significance lately and is extensively used for rehabilitation and prosthetic applications including stroke-driven disability and other neuromuscular disorders. Herein, quantitative analysis of EMG signals is very crucial. However, such applications are constrained by power consumption limitations due to the battery backup necessitating low-complex system design and the on-chip area requirement. Existing hand movement recognition methodologies using single-channel EMG signal involve computationally intensive stages, including Ensemble Empirical Mode Decomposition (EEMD), Fast Independent Component Analysis (FastICA), feature extraction, and Linear Discriminant Analysis (LDA) classification, which can not be mapped onto the low-complex architecture directly from the algorithmic level. The high computational complexity of LDA classification makes it difficult to be used for low-complex applications. In this paper, we introduce a low-complex CORDIC-based hand movement recognition design methodology targeting resource-constrained rehabilitation applications. This work explores replacing LDA classification with K-Means clustering due to its reduced complexity and efficient clustering algorithm. CORDIC-based K-Means clustering is used to further reduce the overall computational complexity of the system. The proposed low complex, K-Means clustering-based hand movement recognition for classifying seven hand movements using single-channel EMG data is found to be 99.77 % less complex and 1.28% more accurate than the conventional LDA-based classification.

Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review

BACKGROUND

Neuromotor rehabilitation and improvement of upper limb functions are necessary to improve the life quality of patients who have experienced injuries or have pathological outcomes. Modern approaches, such as robotic-assisted rehabilitation can help to improve rehabilitation processes and thus improve upper limb functions. Therefore, the aim of this study was to investigate the role of robots in upper limb disability improvement and rehabilitation.

METHODS

This scoping review was conducted by search in PubMed, Web of Science, Scopus, and IEEE (January 2012- February 2022). Articles related to upper limb rehabilitation robots were selected. The methodological quality of all the included studies will be appraised using the Mixed Methods Appraisal Tool (MMAT). We used an 18-field data extraction form to extract data from articles and extracted the information such as study year, country, type of study, purpose, illness or accident leading to disability, level of disability, assistive technologies, number of participants in the study, sex, age, rehabilitated part of the upper limb using a robot, duration and frequency of treatment, methods of performing rehabilitation exercises, type of evaluation, number of participants in the evaluation process, duration of intervention, study outcomes, and study conclusions. The selection of articles and data extraction was made by three authors based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth author. Inclusion criteria were articles involving upper limb rehabilitation robots, articles about upper limb disability caused by any illness or injury, and articles published in English. Also, articles involving other than upper limb rehabilitation robots, robots related to rehabilitation of diseases other than upper limb, systematic reviews, reviews, and meta-analyses, books, book chapters, letters to the editor, and conference papers were also excluded. Descriptive statistics methods (frequency and percentage) were used to analyses the data.

RESULTS

We finally included 55 relevant articles. Most of the studies were done in Italy (33.82%). Most robots were used to rehabilitate stroke patients (80%). About 60.52% of the studies used games and virtual reality rehabilitate the upper limb disabilities using robots. Among the 14 types of applied evaluation methods, "evaluation and measurement of upper limb function and dexterity" was the most applied evaluation method. "Improvement in musculoskeletal functions", "no adverse effect on patients", and "Safe and reliable treatment" were the most cited outcomes, respectively.

CONCLUSIONS

Our findings show that robots can improve musculoskeletal functions (musculoskeletal strength, sensation, perception, vibration, muscle coordination, less spasticity, flexibility, and range of motion) and empower people by providing a variety of rehabilitation capabilities.

Sensor-Based Rehabilitation in Neurological Diseases: A Bibliometric Analysis of Research Trends

BACKGROUND

As the field of sensor-based rehabilitation continues to expand, it is important to gain a comprehensive understanding of its current research landscape. This study aimed to conduct a bibliometric analysis to identify the most influential authors, institutions, journals, and research areas in this field.

METHODS

A search of the Web of Science Core Collection was performed using keywords related to sensor-based rehabilitation in neurological diseases. The search results were analyzed with CiteSpace software using bibliometric techniques, including co-authorship analysis, citation analysis, and keyword co-occurrence analysis.

RESULTS

Between 2002 and 2022, 1103 papers were published on the topic, with slow growth from 2002 to 2017, followed by a rapid increase from 2018 to 2022. The United States was the most active country, while the Swiss Federal Institute of Technology had the highest number of publications among institutions. Sensors published the most papers. The top keywords included rehabilitation, stroke, and recovery. The clusters of keywords comprised machine learning, specific neurological conditions, and sensor-based rehabilitation technologies.

CONCLUSIONS

This study provides a comprehensive overview of the current state of sensor-based rehabilitation research in neurological diseases, highlighting the most influential authors, journals, and research themes. The findings can help researchers and practitioners to identify emerging trends and opportunities for collaboration and can inform the development of future research directions in this field.

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

BACKGROUND

This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke.

METHODS

The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires.

RESULTS

Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported.

CONCLUSIONS

Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.

An augmented reality interface to control a collaborative robot in rehab: A preliminary usability evaluation

Human emotions can be seen as a valuable variable to explore in Human-Computer Interaction for effective, efficient, and satisfying interface development. The inclusion of appropriate emotional triggers in the design of interactive systems can play a decisive role in users' acceptance or rejection. It is well known that the major problem in motor rehabilitation is the high dropout rate resulting from the frustrated expectations given the typical slow recovery process and consequent lack of motivation to endure. This work proposes grouping a collaborative robot with one specific augmented reality equipment to create a rehabilitation system where some gamification levels might be added to provide a better and more motivating experience to patients. Such a system, as a whole, is customizable to adapt to each patient's needs on the rehabilitation exercises. By transforming a tedious exercise into a game, we expect to create an additional layer of enjoyment that can help in triggering positive emotions and stimulate users to continue the rehabilitation process. A pre-prototype was developed to validate this system's usability, and a cross-sectional study using a non-probabilistic sample of 31 individuals is presented and discussed. This study included the application of three standard questionnaires on usability and user experience. The analyses of these questionnaires show that the majority of the users found the system easy and enjoyable. The system was also analysed by a rehabilitation expert who gave a positive output regarding its usefulness, and positive impact on its use in the upper-limb rehabilitation processes. These results clearly encourage further development of the proposed system.

Robot-assisted rehabilitation for total knee or hip replacement surgery patients: A systematic review and meta-analysis

BACKGROUND

This study was performed to update the current evidence and evaluate the effects of robot-assisted rehabilitation (RAR) in comparison with conventional rehabilitation (CR) in patients following total knee (TKR) or hip replacements (THR).

METHODS

PubMed Central, OVID Medline, Cochrane Collaboration Library, and EMBASE for a comprehensive search for all relevant studies, from database inception to July 2022. The following inclusion criteria were used to determine eligibility for studies: randomized and matched controlled trials recruiting men and women who underwent TKR and THR; and studies examining the effect of RAR on outcome measures of physical function and pain.

RESULTS

A total of 9 studies (230 patients) were included in this review and 4 were included in the meta-analysis. The meta-analysis of 2 studies showed that Hybrid Assistive Limb (HAL) training for 5 days, significantly improved pain measured on a visual analogue scale, compared to CR in patients following TKR (SMD = 1.05, 95% confidence interval [Cl] 0.39-1.71). Heterogeneity for I2 value was lower than moderate (tau^2 = 0.0121; I2 = 5%; P = .30). There were 2 studies that assessed self-selected walking speed. The meta-analysis of these studies showed that HAL training was significantly superior to CR in patients following TKR (SMD = 48.70, 95% Cl -50.53 to 147.94) at 2 months. A high heterogeneity was detected (P < .01; I2 = 97%).

CONCLUSION

The result of this systematic review and meta-analysis suggest that RAR may be an effective treatment in TKR and THR patients. However, high-quality studies are needed to verify the long-term effect on their recovery.

Characterization of the Workspace and Limits of Operation of Laser Treatments for Vascular Lesions of the Lower Limbs

The increase of the aging population brings numerous challenges to health and aesthetic segments. Here, the use of laser therapy for dermatology is expected to increase since it allows for non-invasive and infection-free treatments. However, existing laser devices require doctors' manually handling and visually inspecting the skin. As such, the treatment outcome is dependent on the user's expertise, which frequently results in ineffective treatments and side effects. This study aims to determine the workspace and limits of operation of laser treatments for vascular lesions of the lower limbs. The results of this study can be used to develop a robotic-guided technology to help address the aforementioned problems. Specifically, workspace and limits of operation were studied in eight vascular laser treatments. For it, an electromagnetic tracking system was used to collect the real-time positioning of the laser during the treatments. The computed average workspace length, height, and width were 0.84 ± 0.15, 0.41 ± 0.06, and 0.78 ± 0.16 m, respectively. This corresponds to an average volume of treatment of 0.277 ± 0.093 m³. The average treatment time was 23.2 ± 10.2 min, with an average laser orientation of 40.6 ± 5.6 degrees. Additionally, the average velocities of 0.124 ± 0.103 m/s and 31.5 + 25.4 deg/s were measured. This knowledge characterizes the vascular laser treatment workspace and limits of operation, which may ease the understanding for future robotic system development.

Neurorehabilitation Through Synergistic Man-Machine Interfaces Promoting Dormant Neuroplasticity in Spinal Cord Injury: Protocol for a Nonrandomized Controlled Trial

Background

Spinal cord injury (SCI) constitutes a major sociomedical problem, impacting approximately 0.32-0.64 million people each year worldwide; particularly, it impacts young individuals, causing long-term, often irreversible disability. While effective rehabilitation of patients with SCI remains a significant challenge, novel neural engineering technologies have emerged to target and promote dormant neuroplasticity in the central nervous system.

Objective

This study aims to develop, pilot test, and optimize a platform based on multiple immersive man-machine interfaces offering rich feedback, including (1) visual motor imagery training under high-density electroencephalographic recording, (2) mountable robotic arms controlled with a wireless brain-computer interface (BCI), (3) a body-machine interface (BMI) consisting of wearable robotics jacket and gloves in combination with a serious game (SG) application, and (4) an augmented reality module. The platform will be used to validate a self-paced neurorehabilitation intervention and to study cortical activity in chronic complete and incomplete SCI at the cervical spine.

Methods

A 3-phase pilot study (clinical trial) was designed to evaluate the NeuroSuitUp platform, including patients with chronic cervical SCI with complete and incomplete injury aged over 14 years and age-/sex-matched healthy participants. Outcome measures include BCI control and performance in the BMI-SG module, as well as improvement of functional independence, while also monitoring neuropsychological parameters such as kinesthetic imagery, motivation, self-esteem, depression and anxiety, mental effort, discomfort, and perception of robotics. Participant enrollment into the main clinical trial is estimated to begin in January 2023 and end by December 2023.

Results

A preliminary analysis of collected data during pilot testing of BMI-SG by healthy participants showed that the platform was easy to use, caused no discomfort, and the robotics were perceived positively by the participants. Analysis of results from the main clinical trial will begin as recruitment progresses and findings from the complete analysis of results are expected in early 2024.

Conclusions

Chronic SCI is characterized by irreversible disability impacting functional independence. NeuroSuitUp could provide a valuable complementary platform for training in immersive rehabilitation methods to promote dormant neural plasticity.

Trial Registration

ClinicalTrials.gov NCT05465486; https://clinicaltrials.gov/ct2/show/NCT05465486

International Registered Report Identifier (IRRID)

PRR1-10.2196/41152

An sEMG-Controlled Forearm Bracelet for Assessing and Training Manual Dexterity in Rehabilitation: A Systematic Review

Background: The ability to perform activities of daily living (ADL) is essential to preserving functional independence and quality of life. In recent years, rehabilitation strategies based on new technologies, such as MYO Armband^®, have been implemented to improve dexterity in people with upper limb impairment. Over the last few years, many studies have been published focusing on the accuracy of the MYO Armband^® to capture electromyographic and inertial data, as well as the clinical effects of using it as a rehabilitation tool in people with loss of upper limb function. Nevertheless, to our knowledge, there has been no systematic review of this subject. Methods: A systematically comprehensive literature search was conducted in order to identify original studies that answered the PICO question (patient/population, intervention, comparison, and outcome): What is the accuracy level and the clinical effects of the MYO Armband^® in people with motor impairment of the upper limb compared with other assessment techniques or interventions or no intervention whatsoever? The following data sources were used: Pubmed, Scopus, Web of Science, ScienceDirect, Physiotherapy Evidence Database, and the Cochrane Library. After identifying the eligible articles, a cross-search of their references was also completed for additional studies. The following data were extracted from the papers: study design, disease or condition, intervention, sample, dosage, outcome measures or data collection procedure and data analysis and results. The authors independently collected these data following the CONSORT 2010 statement when possible, and eventually reached a consensus on the extracted data, resolving disagreements through discussion. To assess the methodological quality of papers included, the tool for the critical appraisal of epidemiological cross-sectional studies was used, since only case series studies were identified after the search. Additionally, the articles were classified according to the levels of evidence and grades of recommendation for diagnosis studies established by the Oxford Center for Evidence-Based Medicine. Also, The Cochrane Handbook for Systematic Reviews of Interventions was used by two independent reviewers to assess risk of bias, assessing the six different domains. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was followed to carry out this review. Results: 10 articles with a total 180 participants were included in the review. The characteristics of included studies, sample and intervention characteristics, outcome measures, the accuracy of the system and effects of the interventions and the assessment of methodological quality of the studies and risk of bias are shown. Conclusions: Therapy with the MYO Armband^® has shown clinical changes in range of motion, dexterity, performance, functionality and satisfaction. It has also proven to be an accurate system to capture signals from the forearm muscles in people with motor impairment of the upper limb. However, further research should be conducted using bigger samples, well-defined protocols, comparing with control groups or comparing with other assessment or therapeutic tools, since the studies published so far present a high risk of bias and low level of evidence and grade of recommendation.

Comment on Anwer et al. Rehabilitation of Upper Limb Motor Impairment in Stroke: A Narrative Review on the Prevalence, Risk Factors, and Economic Statistics of Stroke and State of the Art Therapies. Healthcare 2022, 10, 190

We are writing to you as the corresponding author of the interesting review study entitled “Rehabilitation of Upper Limb Motor Impairment in Stroke: A Narrative Review on the Prevalence, Risk Factors, and Economic Statistics of Stroke and State of the Art Therapies” [...]

Ethics and Automated Systems in the Health Domain: Design and Submission of a Survey on Rehabilitation and Assistance Robotics to Collect Insiders’ Opinions and Perception

Background: The problem of the relationship between ethics and robotics is very broad, has important implications, and has two large areas of impact: the first is conduct in research, development, and use in general. The second is the implication of the programming of machine ethics. Purpose: Develop and administer a survey of professionals in the health domain collection of their positions on ethics in rehabilitation and assistance robotics. Methods: An electronic survey was designed using Microsoft Forms and submitted to 155 professionals in the health domain (age between 23 and 64 years; 78 males, mean age 43.7, minimum age 24, maximum age 64; 77 females, mean age 44.3, minimum age 23, maximum age 64) using social media. Results and discussion: The outcome returned: (a) the position on ethics training during university studies and in the world of work, (b) the organizational aspects hindered by ethics and those to be perfected in relation to ethics, (c) issues of ethical concern, (d) structured feedback on the usefulness of the methodology along with considerations of open text. Conclusions: An electronic survey methodology has allowed the structured collection of information on positions towards ethics in this sector. Encouraging feedback from the participants suggests the continuation of the study is beneficial. A continuation is expected, expanding the audience of professionals involved and perfecting the survey with the support of scientific companies.

Virtual Reality and Lower Limb Rehabilitation: Effects on Motor and Cognitive Outcome-A Crossover Pilot Study

The effectiveness of virtual reality (VR) in the motor and cognitive rehabilitation of patients with severe acquired brain injury (sABI) is unclear. This randomized, controlled, crossover, single-blinded, pilot study investigates the cognitive and motor effects of lower limb robotic therapy with and without VR visual feedback in a group of patients with ABI. A total of 23 patients with ABI were randomized into two groups: one group (VR-NVR) underwent a 2-week rehabilitation for the lower limbs training with a robotic device (Omego^®) with VR feedback, followed by 2 weeks without VR; the other group (NVR-VR) performed the protocol in the opposite order. Patients were evaluated at baseline, after two and four weeks of treatment using the Level of Cognitive Functioning scale (LCF), Disability Rating Scale (DRS), and Motricity Index for Lower Limb (MI-LL) in the most affected limb. At the end of the intervention, both groups significantly improved in all the outcomes. A significant difference was found between VR treatment versus non-VR treatment for LCF (p = 0.024) and for DRS (p = 0.043) after the second week, while no significant differences were found in the group NVR-VR at T1. Our study indicates how the combination of robotic treatment with VR is effective in enhancing the recovery of cognitive function in patients with ABI, also improving disability and muscular function. Further, VR seems to enhance the early recovery process of motor and cognitive functions.

Digital Transformation Will Change Medical Education and Rehabilitation in Spine Surgery

The concept of minimally invasive spine therapy (MIST) has been proposed as a treatment strategy to reduce the need for overall patient care, including not only minimally invasive spine surgery (MISS) but also conservative treatment and rehabilitation. To maximize the effectiveness of patient care in spine surgery, the educational needs of medical students, residents, and patient rehabilitation can be enhanced by digital transformation (DX), including virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR), three-dimensional (3D) medical images and holograms; wearable sensors, high-performance video cameras, fifth-generation wireless system (5G) and wireless fidelity (Wi-Fi), artificial intelligence, and head-mounted displays (HMDs). Furthermore, to comply with the guidelines for social distancing due to the unexpected COVID-19 pandemic, the use of DX to maintain healthcare and education is becoming more innovative than ever before. In medical education, with the evolution of science and technology, it has become mandatory to provide a highly interactive educational environment and experience using DX technology for residents and medical students, known as digital natives. This study describes an approach to pre- and intraoperative medical education and postoperative rehabilitation using DX in the field of spine surgery that was implemented during the COVID-19 pandemic and will be utilized thereafter.

Brain Network Organization Following Post-Stroke Neurorehabilitation

Brain network analysis can offer useful information to guide the rehabilitation of post-stroke patients. We applied functional network connection models based on multiplex-multilayer network analysis (MMN) to explore functional network connectivity changes induced by robot-aided gait training (RAGT) using the Ekso, a wearable exoskeleton, and compared it to conventional overground gait training (COGT) in chronic stroke patients. We extracted the coreness of individual nodes at multiple locations in the brain from EEG recordings obtained before and after gait training in a resting state. We found that patients provided with RAGT achieved a greater motor function recovery than those receiving COGT. This difference in clinical outcome was paralleled by greater changes in connectivity patterns among different brain areas central to motor programming and execution, as well as a recruitment of other areas beyond the sensorimotor cortices and at multiple frequency ranges, contemporarily. The magnitude of these changes correlated with motor function recovery chances. Our data suggest that the use of RAGT as an add-on treatment to COGT may provide post-stroke patients with a greater modification of the functional brain network impairment following a stroke. This might have potential clinical implications if confirmed in large clinical trials.

XR (Extended Reality: Virtual Reality, Augmented Reality, Mixed Reality) Technology in Spine Medicine: Status Quo and Quo Vadis

In recent years, with the rapid advancement and consumerization of virtual reality, augmented reality, mixed reality, and extended reality (XR) technology, the use of XR technology in spine medicine has also become increasingly popular. The rising use of XR technology in spine medicine has also been accelerated by the recent wave of digital transformation (i.e., case-specific three-dimensional medical images and holograms, wearable sensors, video cameras, fifth generation, artificial intelligence, and head-mounted displays), and further accelerated by the COVID-19 pandemic and the increase in minimally invasive spine surgery. The COVID-19 pandemic has a negative impact on society, but positive impacts can also be expected, including the continued spread and adoption of telemedicine services (i.e., tele-education, tele-surgery, tele-rehabilitation) that promote digital transformation. The purpose of this narrative review is to describe the accelerators of XR (VR, AR, MR) technology in spine medicine and then to provide a comprehensive review of the use of XR technology in spine medicine, including surgery, consultation, education, and rehabilitation, as well as to identify its limitations and future perspectives (status quo and quo vadis).

Neuromechanical Biomarkers for Robotic Neurorehabilitation

One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.

Psychological and Emotional Effects of Digital Technology on Children in COVID-19 Pandemic

COVID-19 has caused obstacles in continuing normal life almost everywhere in the world by causing the implementation of social distancing and eventually imposing the lockdown. This has become the reason for the increase in technology usage in daily life for professional work as well as for entertainment purposes. There has been an increased prevalence of technology usage in adolescents and children during lockdown leaving its impact on their lives either in a positive or negative aspect. The overall documented percentage increase of technology usage in children was about 15%, of which smartphone usage has 61.7% of prevalence. Disturbance in brain functioning is suggested to be originated by compromise of neuroplasticity of the nerves. The radiofrequency (RF) radiations emitting from the smartphone are of doubtful concern as a brain tumor risk factor in children. The increased usage can have effects on brain functioning that will compromise sleep and cognitive abilities and develop risk for certain mental illnesses including, but not limited to, depression, anxiety, Alzheimer’s disease, and attention-deficit/hyperactive disorder (ADHD). Despite being a threat for developing mental illness, video games are proven to reduce depression and anxiety, and increase creativity, skills, and cognition in children. The increased usage of technology can have a positive and negative impact on the mental development of adolescents and children depending on the trends in the usage. However, parents should be monitoring their children’s mental health and behavior in these difficult times of pandemic.