OBM Neurobiology is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. By design, the scope of OBM Neurobiology is broad, so as to reflect the multidisciplinary nature of the field of Neurobiology that interfaces biology with the fundamental and clinical neurosciences. As such, OBM Neurobiology embraces rigorous multidisciplinary investigations into the form and function of neurons and glia that make up the nervous system, either individually or in ensemble, in health or disease. OBM Neurobiology welcomes original contributions that employ a combination of molecular, cellular, systems and behavioral approaches to report novel neuroanatomical, neuropharmacological, neurophysiological and neurobehavioral findings related to the following aspects of the nervous system: Signal Transduction and Neurotransmission; Neural Circuits and Systems Neurobiology; Nervous System Development and Aging; Neurobiology of Nervous System Diseases (e.g., Developmental Brain Disorders; Neurodegenerative Disorders).
OBM Neurobiology publishes research articles, technical reports and invited topical reviews. Although the OBM Neurobiology Editorial Board encourages authors to be succinct, there is no restriction on the length of the papers. Authors should present their results in as much detail as possible, as reviewers are encouraged to emphasize scientific rigor and reproducibility.
Archiving: full-text archived in CLOCKSS.
Rapid publication: manuscripts are undertaken in 11.8 days from acceptance to publication (median values for papers published in this journal in the second half of 2021, 1-2 days of FREE language polishing time is also included in this period).
Application of Smart Sensing Systems, Machine Learning and Data Analytics Techniques for Patients with Neurological Disabilities
Submission Deadline: July 31, 2023 (Open) Submit Now
Lu Bai, PhD
School of Computing, Ulster University, Belfast, UK
Research interests: smart sensing systems; machine learning; data analytics technique; smart health.
About This Topic
In recent years, the advancement of smart sensing technologies supported by novel machine learning and data analytics techniques have opened up new opportunities to detect neurological disorders and address the challenges in assessing the patients disabilities. Future machine learning models will keep transforming neurological disabilities treatment strategies and rehabilitation regimes. Some of the innovations including the use of machine learning models deriving insights into the neurological disorder detection and automate the process of estimating the clinical scores for daily disability assessment. This issue explores future novel data analytics techniques in how to improve the treatment for patients with neurological disabilities.
Smart sensing system, machine learning, data analytics, neurological disorders, artificial intelligence, neurological disabilities.
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