View clinical trials related to Motor Disorders.
Filter by:The study aims to demonstrate the effectiveness and superiority of a 5-day immersive VR-rehabilitation treatment versus a 5-day conventional rehabilitation treatment in reducing FMDs symptoms severity, assessed by the Simplified Functional Movement Disorders Rating Scale (S- FMDRS).
The RECOMMENCER project aims at developing and testing a novel hybrid Brain Computer Interface device based on cortico-muscular connectivity, that will be employed to activate Functional Electrical Stimulation (FES) of upper limb muscles. After the technical implementation of the device and its preliminary testing on healthy subject, the investigators will evaluate the effects of a 1 month training with the device (RECOM) on post-stroke patients undergoing standard rehabilitation (add-on). The proposed intervention will be compared with an active physiotherapy training including FES (CTRL) which will be focused on upper limb with similar intensity as the target intervention (also delivered in add-on).
The PRéPaR project aims to construct, with the help of parents and early care providers, a support program for the families of infants at an increased risk for neurodevelopmental disorders, and to evaluate the acceptability and feasibility of such a program. This program aims to strengthen parenting skills, support infant development and improve the continuity of hospital/non-hospital care, including early identification of neurodevelopmental motor disorders and continuation of the support initiated during neonatal hospitalization.
The purpose of this three-year study is therefore three-fold: (1) Model Development- to apply pose estimation model and tracking recognition model on the movements of a large sample of term and preterm infants under a motor assessment in the laboratory to examine the accuracy of the AI algorithms in identifying individual movements using physical therapists' results as gold standards; (2) Model Validation- to examine the performance of the AI algorithms on the same term and preterm infants' movements when video recorded by the parents at home between the laboratory assessment ages using physical therapists' results as gold standards; and (3) Concurrent and Predictive Validity of AI Movement Sets- to select the identifiable movement classes into AI movement sets for individual ages to examine their concurrent validity with physical therapists' results and predictive validity on developmental outcomes at 18 months of age in these infants.
The clinical management of Parkinson's disease (PD) is frequently challenged by the occurrence of motor disorders and complications, such as freezing of gait, fluctuations and the ON-OFF phenomenon, primarily manifesting at home. Therapeutic decisions are usually based on periodic neurological examinations and patients' anamnestic experience collected in an outpatient setting, thus limited by several issues, including "recall bias" and subjective, semi-quantitative and operator-dependent evaluations in non-ecological settings. In the last two decades, new wearable technologies, consisting of "wireless" sensors (e.g., inertial, electromyography), have been widely applied to quantitatively assess movements in physiological and pathological conditions, even for prolonged periods in free-living settings (i.e., long-term monitoring). The aim of this study is to evaluate motor symptoms in patients with PD, such as bradykinesia, tremor, gait disturbances and balance disorders, objectively and quantitatively through the application of wearable sensors in intra- and extra hospital settings, also during common activities of daily living, in order to obtain ecological data possibly useful in the therapeutic management of the disease.
Functional motor disorders (FMDs) are a broad spectrum of functional neurological disorders, referring to abnormal movements like dystonia, tremor, and gait/balance disorders. Patients with FMDs experience high degrees of disability and distress equivalent to those suffering from degenerative neurological diseases. Rehabilitation is essential in managing FMDs. However, the current systems of rehabilitation delivery face two main challenges. Patients are not receiving the amount and kind of evidence-based rehabilitation they need due to the lack of rehabilitation professionals' experts in the field. The rehabilitation setting is not adequate for the long-term management and monitoring of these patients. To date, no randomized controlled trials are evaluating the effectiveness of Telemedicine in the management of patients with FMD. This is a single-blind randomized-controlled trial (RCT) with 2-parallel arms to demonstrate the effectiveness and superiority of a 5-day intensive rehabilitation treatment followed by a telemedicine program on the motor, non-motor symptoms (pain, fatigue, anxiety, and depression), the self-perception of clinical change and Health-Related Quality of Life, and health care costs in patients with FMDs.
A brain-computer interface (BCI) decodes users' behavioral intentions or mental states directly from their brain activity, thus allowing operation of devices without requiring any overt motor action. One major modality for BCI control is based on motor imagery (MI), which is the mental rehearsal of the kinesthetics of a movement without actually performing it. MI-based BCIs translate motor intents into control commands for external devices. A major challenge in such BCIs is differentiating MI patterns corresponding to fine hand movements of the same limb from non-invasive EEG recordings with low spatial resolution since the cortical sources responsible for these movements are overlapping. In this study, the investigators hypothesize that neuromuscular electrical stimulation (NMES) applied contingent to the voluntary activation of the primary motor cortex through MI can help differentiate patterns of activity associated with different hand movements of the same limb by consistently recruiting the separate neural pathways associated with each of the movements within a closed-loop BCI setup. This is expected to be associated with neuroplastic changes at the cortical or corticospinal levels.
The patients who had COVID-19 infection, and after that reported for one of the signs of gastrointestinal disorder (esophageal and anorectal) will be underwent to esophageal and anorectal motor monitoring investigation (HRM manometry) on standard protocol.
This study focuses on the mobile robot assist device for tele-interaction: the "COVEALINK 2" robot. This telepresence robot is designed for remote use inside the home. It works with an Internet connection (Wifi or 4G). It consists of a control interface (an application installed on the smartphone or tablet of the hospitalized patient) and a mobile robot placed in the home of the hospitalized patient (composed of a mobile platform, a visualization screen whose tilt is adjustable remotely for better adaptation to the interlocutors and an audio communication system). From the app installed on his smartphone or tablet, the patient hospitalized in the center for a long time (2 months minimum) will be able to start remotely (from the center where he is hospitalized) the robot and have it move within his home to communicate with the people present at the time of use (family, friends, neighbors etc.).
Stroke represents one of the main causes of adult disability and will be one of the main contributors to the burden of disease in 2030. However, the healthcare systems are not able to respond to the current demand let alone its future increase. There is a need to deploy new approaches that advance current rehabilitation methods and enhance their efficiency. One of the latest approaches used for the rehabilitation of a wide range of deficits of the nervous system is based on virtual reality (VR) applications, which combine training scenarios with dedicated interface devices. Market drivers exist for new ICT based treatment solutions. IBEC/ Eodyne Systems has developed and commercialised the Rehabilitation Gaming System (RGS), a science-based ICT solution for neurorehabilitation combining brain theory, AI, cloud computing and virtual reality and targeting motor and cognitive recovery after stroke. RGS provides a continuum of evaluations and therapeutic solutions that accompany the patient from the clinic to the therapy centre. RGS has been clinically validated showing its superiority over other products while reducing cost also through its use of standard off-the-shelf hardware and a Software as a Service model (SaaS). Commercial evaluations have shown that RGS acts as a workforce multiplier while delivering a high quality of care at clinical centres (RGS@Clinic). However, in order to achieve significant benefits in the patients' QoL, it is essential that RGS becomes an at home solution providing 24/7 monitoring and care. For this reason, this project aims at investigating the RGS acceptability and adoption model. The findings derived from this study will contribute to establish a novel and superior neurorehabilitation paradigm that can accelerate the recovery of hemiparetic stroke patients. Besides the clinical impact, such achievement could have relevant socioeconomic impact.