Neurodegenerative diseases are caused by the degeneration of nerve cells in the central or peripheral nervous system, resulting in deterioration of gross and fine motor skills, speech, cognition, and executive function over time. As one of the worst kinds of illnesses affecting millions of people around the world, neurodegenerative diseases are irreversible and currently incurable. In the effort to discover disease-modifying treatment, efficacious assessment tools are critically needed to detect and monitor disease-related changes for developing targeted treatments and to evaluate treatment effects. However, the current clinical assessment options for neurodegenerative diseases, which rely largely on subjective symptom reports, neurological and physical examinations in conjunction with neuroimaging, neurophysiological, neuropsychological, and genetic tests, have various limitations including the lack of sensitivity, especially to the early disease stages, unquantifiability, and low reproducibility. Therefore, developing novel assessment tools has been an active area in the research of neurodegenerative diseases.
With the rapid development of technologies over the past decades, interdisciplinary research efforts have emerged in applying innovative machine learning and biomedical signal processing techniques to aid in the development of novel assessment tools for neurodegenerative diseases that are objective, quantifiable, reliable, and reproducible. Compared with the traditional clinical assessment options, these novel assessment tools can provide a more efficacious means of evaluating the disease and treatment-related physical and mental changes, thus facilitating the discovery of new treatments to improve the quality of life and survival for patients with neurodegenerative diseases.
This Research Topic will provide comprehensive coverage of research efforts in integrating state-of-the-art computational technologies into the development of novel assessment tools for detecting, monitoring, and predicting physical and mental changes in neurodegenerative diseases.
We welcome contributions of Original Research, Brief Research Reports, Systematic Reviews, Reviews (and Mini-Reviews), Methods, and Clinical Trials targeting, but not limited to, the following areas related to neurodegenerative diseases such as Amyotrophic Lateral Sclerosis, Parkinson’s disease, Huntington’s disease, and Alzheimer’s disease:
• Identification of novel biomarkers using advanced biomedical signal processing techniques
• Development of automated assessment tools
• Analytical and/or clinical validation of novel technology-based motor, cognitive, and behavioral assessments
• Use of novel objective and quantitative measurement tools to characterize the pathological mechanism, progression pattern, and phenotypes of neurodegenerative diseases
• Application of novel objective and quantitative measurement tools to evaluate treatment effects
• Design of technology-enabled protocols for self-monitoring of health data
Topic Editors, Dr. Wei Gu and Dr. Venkata Satagopam are founders and shareholders of Information Technology for Translational Medicine, ITTM S.A.. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
Neurodegenerative diseases are caused by the degeneration of nerve cells in the central or peripheral nervous system, resulting in deterioration of gross and fine motor skills, speech, cognition, and executive function over time. As one of the worst kinds of illnesses affecting millions of people around the world, neurodegenerative diseases are irreversible and currently incurable. In the effort to discover disease-modifying treatment, efficacious assessment tools are critically needed to detect and monitor disease-related changes for developing targeted treatments and to evaluate treatment effects. However, the current clinical assessment options for neurodegenerative diseases, which rely largely on subjective symptom reports, neurological and physical examinations in conjunction with neuroimaging, neurophysiological, neuropsychological, and genetic tests, have various limitations including the lack of sensitivity, especially to the early disease stages, unquantifiability, and low reproducibility. Therefore, developing novel assessment tools has been an active area in the research of neurodegenerative diseases.
With the rapid development of technologies over the past decades, interdisciplinary research efforts have emerged in applying innovative machine learning and biomedical signal processing techniques to aid in the development of novel assessment tools for neurodegenerative diseases that are objective, quantifiable, reliable, and reproducible. Compared with the traditional clinical assessment options, these novel assessment tools can provide a more efficacious means of evaluating the disease and treatment-related physical and mental changes, thus facilitating the discovery of new treatments to improve the quality of life and survival for patients with neurodegenerative diseases.
This Research Topic will provide comprehensive coverage of research efforts in integrating state-of-the-art computational technologies into the development of novel assessment tools for detecting, monitoring, and predicting physical and mental changes in neurodegenerative diseases.
We welcome contributions of Original Research, Brief Research Reports, Systematic Reviews, Reviews (and Mini-Reviews), Methods, and Clinical Trials targeting, but not limited to, the following areas related to neurodegenerative diseases such as Amyotrophic Lateral Sclerosis, Parkinson’s disease, Huntington’s disease, and Alzheimer’s disease:
• Identification of novel biomarkers using advanced biomedical signal processing techniques
• Development of automated assessment tools
• Analytical and/or clinical validation of novel technology-based motor, cognitive, and behavioral assessments
• Use of novel objective and quantitative measurement tools to characterize the pathological mechanism, progression pattern, and phenotypes of neurodegenerative diseases
• Application of novel objective and quantitative measurement tools to evaluate treatment effects
• Design of technology-enabled protocols for self-monitoring of health data
Topic Editors, Dr. Wei Gu and Dr. Venkata Satagopam are founders and shareholders of Information Technology for Translational Medicine, ITTM S.A.. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
