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Cancer as a whole, but especially childhood cancer, creates a number of psychological, social, and family problems as well as practical and financial issues, which every parent is called upon to solve. This study focuses on childhood cancer and aims at a thorough analysis of the physical/organic, psychological, and social problems associated with the parents and relatives of a child with cancer. The special element in pediatric neoplasms is not only the vulnerable population target group, but also the set of secondary effects it has on the environment of the sick child. The research was conducted on a sample of 133 families of children with cancer, and the results were displayed after statistical processing and data analysis with R statistical software. The results of the study confirm with statistically significant data the effect of childhood cancer on the physical, mental, and social health and behavior of the parent. Thus, 53.8% of the respondents stated 5 and above on the 7-point Likert scale for fatigue issues, 55.6% for sleep disorders, 78.1% for stress, and 82.7% for fear. The key findings are characterized by high specificity as it is a unique study that reveals particular aspects of the Greek parent's behavior, mind, and body during the period of their child's illness.   Conclusion: The effects of childhood illnesses, particularly when they are severe, such as neoplasms, present a looming threat, ushering in a multitude of adverse alterations in the daily lives of the affected child's family. What is Known - What is New: • We know the effects that a childhood illness brings not only to the sick child, but also to the entire family circle. The new element in the present research is that these data reflect the situation in Greece, for which the research data in this area is quite limited. Our research is one of the few studies that demonstrate with statistical data the change in the psychosomatic health of the parent who has a child with cancer., (© 2023. The Author(s).)

Introduction: Duchenne muscular dystrophy (DMD) is a genetic disorder that induces progressive muscular degeneration. Currently, the increase in DMD individuals' life expectancy is not being matched by an increase in quality of life. The functioning of the hand and wrist is central for performing daily activities and for providing a higher degree of independence. Active exoskeletons can assist this functioning but require the accurate decoding of the users' motor intention. These methods have, however, never been systematically analyzed in the context of DMD. Methods: This case study evaluated direct control (DC) and pattern recognition (PR), combined with an admittance model. This enabled customization of myoelectric controllers to one DMD individual and to a control population of ten healthy participants during a target-reaching task in 1- and 2- degrees of freedom (DOF). We quantified real-time myocontrol performance using target reaching times and compared the differences between the healthy individuals and the DMD individual. Results and Discussion: Our findings suggest that despite the muscle tissue degeneration, the myocontrol performance of the DMD individual was comparable to that of the healthy individuals in both DOFs and with both control approaches. It was also evident that PR control performed better for the 2-DOF tasks for both DMD and healthy participants, while DC performed better for the 1-DOF tasks. The insights gained from this study can lead to further developments for the intuitive multi-DOF myoelectric control of active hand exoskeletons for individuals with DMD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Nizamis, Ayvaz, Rijken, Koopman and Sartori.)

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.

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., (©Alkinoos Athanasiou, Konstantinos Mitsopoulos, Apostolos Praftsiotis, Alexander Astaras, Panagiotis Antoniou, Niki Pandria, Vasileia Petronikolou, Konstantinos Kasimis, George Lyssas, Nikos Terzopoulos, Vasilki Fiska, Panagiotis Kartsidis, Theodoros Savvidis, Athanasios Arvanitidis, Konstantinos Chasapis, Alexandros Moraitopoulos, Kostas Nizamis, Anestis Kalfas, Paris Iakovidis, Thomas Apostolou, Ioannis Magras, Panagiotis Bamidis. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 13.09.2022.)

Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human-machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals-namely, family members and professional carers-to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.

Duchenne muscular dystrophy (DMD) is a genetic disorder that results in progressive muscular degeneration. Although medical advances increased their life expectancy, DMD individuals are still highly dependent on caregivers. Hand/wrist function is central for providing independence, and robotic exoskeletons are good candidates for effectively compensating for deteriorating functionality. Robotic hand exoskeletons require the accurate decoding of motor intention typically via surface electromyography (sEMG). Traditional low-density sEMG was used in the past to explore the muscular activations of individuals with DMD; however, it cannot provide high spatial resolution. This study characterized, for the first time, the forearm high-density (HD) electromyograms of three individuals with DMD while performing seven hand/wrist-related tasks and compared them to eight healthy individuals (all data available online). We looked into the spatial distribution of HD-sEMG patterns by using principal component analysis (PCA) and also assessed the repeatability and the amplitude distributions of muscle activity. Additionally, we used a machine learning approach to assess DMD individuals' potentials for myocontrol. Our analysis showed that although participants with DMD were able to repeat similar HD-sEMG patterns across gestures (similarly to healthy participants), a fewer number of electrodes was activated during their gestures compared to the healthy participants. Additionally, participants with DMD activated their muscles close to maximal contraction level (0.63 ± 0.23), whereas healthy participants had lower normalized activations (0.26 ± 0.2). Lastly, participants with DMD showed on average fewer PCs (3), explaining 90% of the complete gesture space than the healthy (5). However, the ability of the DMD participants to produce repeatable HD-sEMG patterns was unexpectedly comparable to that of healthy participants, and the same holds true for their offline myocontrol performance, disproving our hypothesis and suggesting a clear potential for the myocontrol of wearable exoskeletons. Our findings present evidence for the first time on how DMD leads to progressive alterations in hand/wrist motor control in DMD individuals compared to healthy. The better understanding of these alterations can lead to further developments for the intuitive and robust myoelectric control of active hand exoskeletons for individuals with DMD., (Copyright © 2020 Nizamis, Rijken, van Middelaar, Neto, Koopman and Sartori.)

Duchenne muscular Dystrophy (DMD) is a progressive degenerative muscle disease, affecting, among others, the upper extremities. Effective hand rehabilitation can improve the hand function of people with DMD. To reach this goal, we first need to gain more insight into the hand cognitive-motor performance of people with DMD. This is the first study employing a systematic analysis on multi-finger, cognitive-motor performance of people with DMD. For this purpose, we propose an active dynamic visuo-motor task. The task employed six visual stimuli, a subset of which was activated at each trial. The stimuli were activated with a frequency of 1, 2, 3 and 4 Hz. Eight healthy participants and three participants with DMD performed the task. Additionally, the healthy participants performed seven sessions, and we assessed the training effects. Task-related cognitive-motor performance was evaluated using information transfer rate (ITR) and perceived workload. Regarding ITR, healthy participants performed significantly better than DMD participants; however, this was more evident for trials involving more than three fingers. Workload showed no difference between the healthy and the DMD groups. Healthy participants significantly improved their performance during training. Our results suggest that hand rehabilitation of people with DMD should consider multi-finger dynamic training. However, additional research with more people with DMD is needed for further generalization of our conclusions., Competing Interests: This work was supported by the Flextension Foundation (http://www.flextension.nl/en/) through the Netherlands Organisation for Scientific Research (NWO https://www.nwo.nl/en), the Duchenne Parent Project (https://duchenne.nl/), Hankamp Rehab (http://www.hankamprehab.nl/), Spieren voor Spieren (https://www.spierenvoorspieren.nl/), TMSi (https://www.tmsi.com/), Festo (https://www.festo.com) and Pontes Medical (https://www.pontesmedical.com/), all awarded to BFJMK. Grant Number: 13525. The funding from commercial sources does not alter our adherence to PLOS ONE policies on sharing data and materials.

With recent improvements in healthcare, individuals with Duchenne muscular dystrophy (DMD) have prolonged life expectancy, and it is therefore vital to preserve their independence. Hand function plays a central role in maintaining independence in daily living. This requires sufficient grip force and the ability to modulate it with no substantially added effort. Individuals with DMD have low residual grip force and its modulation is challenging and fatiguing. To assist their hand function, we developed a novel dynamic hand orthosis called SymbiHand, where the user's hand motor intention is decoded by means of surface electromyography, enabling the control of an electrohydraulic pump for actuation. Mechanical work is transported using hydraulic transmission and flexible structures to redirect interaction forces, enhancing comfort by minimizing shear forces. This paper outlines SymbiHand's design and control, and a case study with an individual with DMD. Results show that SymbiHand increased the participant's maximum grasping force from 2.4 to 8 N. During a grasping force-tracking task, muscular activation was decreased by more than 40% without compromising task performance. These results suggest that SymbiHand has the potential to decrease muscular activation and increase grasping force for individuals with DMD, adding to the hand a total mass of no more than 241 g. Changes in mass distributions and an active thumb support are necessary for improved usability, in addition to larger-scale studies for generalizing its assistive potential.

The human hand is important for the performance of activities of daily living which are directly related to quality of life. Various conditions, such as Duchenne muscular dystrophy (DMD) can affect the function of the human hand and wrist. The ability to assess the impairment in the hand and the wrist by measuring the range of motion (ROM), is essential for the development of effective rehabilitation protocols. Currently the clinical standard is the goniometer. In this study we explore the feasibility and reliability of an optical sensor (Leap motion sensor) in measuring active hand/wrist ROM. We measured the hand/wrist ROM of 20 healthy adults with the goniometer and the Leap motion sensor, in order to check the agreement between the two methods and additionally, we performed a test-retest of the Leap motion sensor with 12 of them, to assess its reliability. The results suggest low agreement between the goniometer and the leap motion sensor, yet showing a large decrease in measurement time and high reliability when using the later. Despite the low agreement between the two methods, we believe that the Leap motion sensor shows potential to contribute to the development of hand rehabilitation protocols and be used with patients in a clinical setting.

Background: Adults with Duchenne muscular dystrophy (DMD) can benefit from devices that actively support their arm function. A critical component of such devices is the control interface as it is responsible for the human-machine interaction. Our previous work indicated that surface electromyography (sEMG) and force-based control with active gravity and joint-stiffness compensation were feasible solutions for the support of elbow movements (one degree of freedom). In this paper, we extend the evaluation of sEMG- and force-based control interfaces to simultaneous and proportional control of planar arm movements (two degrees of freedom)., Methods: Three men with DMD (18-23 years-old) with different levels of arm function (i.e. Brooke scores of 4, 5 and 6) performed a series of line-tracing tasks over a tabletop surface using an experimental active arm support. The arm movements were controlled using three control methods: sEMG-based control, force-based control with stiffness compensation (FSC), and force-based control with no compensation (FNC). The movement performance was evaluated in terms of percentage of task completion, tracing error, smoothness and speed., Results: For subject S1 (Brooke 4) FNC was the preferred method and performed better than FSC and sEMG. FNC was not usable for subject S2 (Brooke 5) and S3 (Brooke 6). Subject S2 presented significantly lower movement speed with sEMG than with FSC, yet he preferred sEMG since FSC was perceived to be too fatiguing. Subject S3 could not successfully use neither of the two force-based control methods, while with sEMG he could reach almost his entire workspace., Conclusions: Movement performance and subjective preference of the three control methods differed with the level of arm function of the participants. Our results indicate that all three control methods have to be considered in real applications, as they present complementary advantages and disadvantages. The fact that the two weaker subjects (S2 and S3) experienced the force-based control interfaces as fatiguing suggests that sEMG-based control interfaces could be a better solution for adults with DMD. Yet force-based control interfaces can be a better alternative for those cases in which voluntary forces are higher than the stiffness forces of the arms.

Duchenne muscular Dystrophy (DMD) Is a progressive muscle degenerative disease. Active hand assistive devices, can improve the quality of life of people with DMD. Such devices show a rejection rate due to complexity. Our hypothesis is, that a simple orthosis might prove more functional and realistic in assisting people with DMD. To investigate, we developed a portable setup that provides various visual stimuli and records the response of the subjects' fingers through a mouse clicking task. Six LEDs served as visual stimuli. The subjects' responses were obtained through mechanical interaction with two vertical mice. Different combinations of frequencies and numbers of stimuli were tested with 8 healthy subjects and one with DMD. Performance was evaluated in terms of information transfer rate (ITR), pattern accuracy and perceived workload. The outcome shows that lower complexity results in lower ITR and lower workload for all subjects. While for healthy subjects, maximum ITR was 4.3 bits/s, for DMD maximum ITR was 2.5 bits/s. Both maxima were achieved at the same trial (3 fingers at 2 Hz). This trial agrees with a pareto optimization analysis of ITR with respect to workload. The results support our hypothesis for a simple yet functional solution. Furthermore healthy subjects and the individual with DMD, in principal show similar finger control, albeit with lower absolute performance.

The development of dynamic hand orthoses is a fast-growing field of research and has resulted in many different devices. A large and diverse solution space is formed by the various mechatronic components which are used in these devices. They are the result of making complex design choices within the constraints imposed by the application, the environment and the patient's individual needs. Several review studies exist that cover the details of specific disciplines which play a part in the developmental cycle. However, a general collection of all endeavors around the world and a structured overview of the solution space which integrates these disciplines is missing. In this study, a total of 165 individual dynamic hand orthoses were collected and their mechatronic components were categorized into a framework with a signal, energy and mechanical domain. Its hierarchical structure allows it to reach out towards the different disciplines while connecting them with common properties. Additionally, available arguments behind design choices were collected and related to the trends in the solution space. As a result, a comprehensive overview of the used mechatronic components in dynamic hand orthoses is presented.