Implementing New Technologies for Neuromuscular Disorders

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About this Research Topic

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Background

New technologies have transformed the way we communicate and live our lives. Digital tools are part of our daily practice and have evolved alongside progress in robotics, artificial intelligence, and other new technologies. These advances can change the way patients are diagnosed, care is managed, and disease progression is understood. Some incurable illnesses are now manageable, and treatments exist to help patients where none were available previously.

In terms of diagnosis in neuromuscular diseases, the evolution of genetic tools revolutionized genetic disease diagnosis, allowing the identification of many genes involved in the pathophysiology of neuromuscular or other diseases, leading to the elaboration of new treatments, and improving patients' quality of life. Routine analysis has also evolved through the implementation of new tools or improvement of already existing ones. The level of detail and resolution of imaging machines are now so refined that it is possible to classify disease severity or detect tiny muscle changes based on MRI analysis. An electromyogram can be performed using bracelet-type sensors to stimulate and detect muscle contraction. Muscle pathology also benefited from technological progress to identify reliable biomarkers for disease evolution and severity, with machine learning and automated tissue pattern recognition approaches to quantify the muscular dystrophies, inflammation, and fat infiltration.
Finally, the emergence of new devices to precisely measure and record specific outcomes such as distance, speed, movement, and mobile application, in addition to the development of telemedicine, has eased the monitoring and follow-up process by making them remote.

Neuromuscular diseases are rare and fluctuating in terms of symptoms; patients are often diagnosed late in the disease course, and they do not have enough information to understand their condition and to be proactive in their management. Usually, insufficient resources or services are available, leading to a social burden on patients. From a medical perspective, the rarity of such diseases leads to the unfamiliarity of the medical staff and caregiver, as well as an absence of consensus in disease assessment, treatment, and management. Thus, innovations must be developed in response to patients’ and physicians’ unmet needs.

Clinicians also need technological innovations to help them recognize neuromuscular diseases and find the best therapeutic approach based on medical consensus, as well as the necessary tools to follow patients’ states regularly. Diagnosis also has to be improved by implementing automated systems to analyze a considerable amount of data, representing a significant step forward to accelerate the diagnosis and the patients’ follow up treatment. Further, it is important to develop new tools able to precisely and reliably measure specific outcomes in clinical trials, to assess the efficacy of a newly developed compound.

In this context, this Research Topic aims to discuss the new perspectives and challenges to developing and implementing innovative tools in the field of neuromuscular diseases.

This Research Topic welcomes any types of manuscripts supported by Frontiers in Neurology (including review and original research), pertaining but not limited to the following themes:
- Challenges and strategies of e-health and innovation
- E-registries –telemedicine –m-health apps
- Robotics and domotics
- Connected devices

Conflicts of Interest: Dr Dubuisson has received travel grants from Pfizer and Novarti. Dr Claeys has participated at advisory boards and/or received speaker honorary from Alnylam, Amicus, ArgenX, Biogen, CSL Behring, Ipsen, Janssen, Lupin, Pfizer, Roche, Sanofi-Genzyme and UCB. Additionally, Dr Claeys is Chairholder of the Emil von Behring Chair for Neuromuscular and Neurodegenerative Disorders, which is supported by CSL Behring.

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Keywords: neuromuscular disorders, treatment, new technologies, diagnosis, outcome measures, biomarkers, -omics, wearables, artificial intelligence, telemedicine

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