Neurodegenerative disorders are a type of neurological illness that causes gradual loss of neuronal structures and functions. In many patients, the disease has an insidious onset and a progressive clinical course, resulting in profound functional impairments and a lower quality of life. Parkinson's disease (PD) and Alzheimer's disease (AD) are the most common neurodegenerative diseases. Because of the global population aging, the number of patients with these two diseases is rapidly increasing, with more than 10 million patients today in China alone. The resulting economic and social burden can become unbearable for any national healthcare system in the near future.
The clinical symptoms of neurodegenerative diseases are complicated and differ substantially across individual patients in terms of type, severity, and frequency. Faced with such a large inter-individual variability, and in the absence of diagnostic and prognostic biomarkers, it is a major challenge for clinicians to make an accurate and timely diagnosis, prognosis, and management plan for a given patient.
These clinical challenges can nowadays be addressed by applying innovative artificial intelligence (AI)-based medical technologies and biosensing systems, which can assess, monitor, and analyze a variety of physiological functions and behaviors, including motor behavior, body temperature, mood, sleep, and circadian rhythmicity. Similarly, various invasive and noninvasive brain stimulation techniques have been developed, including deep brain stimulation (DBS) and transcranial magnetic or electric stimulation (e.g., TMS, tDCS), which can help to alleviate the clinical symptoms in some patients. Over the past decade, AI-based biosensing and neuromodulation, ranging from wearable biosensors to brain-computer interfaces and deep brain implant devices, have been increasingly applied to aid in the diagnosis, prognosis, and management of patients with neurodegenerative diseases, representing a major step closer to realizing personalized medicine.
This Research Topic aims to provide the state-of-the-art on the clinical use and role of biosensing and neuromodulation (especially AI-based) in the early detection, assessment, diagnosis, prognosis, and management of patients with neurodegenerative diseases. Original high-quality studies, as well as reviews, are welcomed. Clinical applications of particular interest include, but are not restricted to, the following:
• AI applications to health records, genetic, biological, clinical, cognitive, behavioral, or other data from patients or at-risk individuals for the early detection, diagnosis, or prediction of outcome of individuals with neurodegenerative diseases
• Use of brain-computer interfaces and wearable sensor devices for the early detection, diagnosis, and prognosis of neurodegenerative diseases
• Use of non-wearable and wearable sensor devices for the assessment and continuous monitoring of symptom severity, drug response and side effects, mood, sleep, cognitive function, or functional status in clinical or home settings
• Applications of noninvasive and invasive brain stimulation techniques in the treatment of neurodegenerative diseases, in particular when combined with AI, brain electrophysiology, or neuroimaging
Neurodegenerative disorders are a type of neurological illness that causes gradual loss of neuronal structures and functions. In many patients, the disease has an insidious onset and a progressive clinical course, resulting in profound functional impairments and a lower quality of life. Parkinson's disease (PD) and Alzheimer's disease (AD) are the most common neurodegenerative diseases. Because of the global population aging, the number of patients with these two diseases is rapidly increasing, with more than 10 million patients today in China alone. The resulting economic and social burden can become unbearable for any national healthcare system in the near future.
The clinical symptoms of neurodegenerative diseases are complicated and differ substantially across individual patients in terms of type, severity, and frequency. Faced with such a large inter-individual variability, and in the absence of diagnostic and prognostic biomarkers, it is a major challenge for clinicians to make an accurate and timely diagnosis, prognosis, and management plan for a given patient.
These clinical challenges can nowadays be addressed by applying innovative artificial intelligence (AI)-based medical technologies and biosensing systems, which can assess, monitor, and analyze a variety of physiological functions and behaviors, including motor behavior, body temperature, mood, sleep, and circadian rhythmicity. Similarly, various invasive and noninvasive brain stimulation techniques have been developed, including deep brain stimulation (DBS) and transcranial magnetic or electric stimulation (e.g., TMS, tDCS), which can help to alleviate the clinical symptoms in some patients. Over the past decade, AI-based biosensing and neuromodulation, ranging from wearable biosensors to brain-computer interfaces and deep brain implant devices, have been increasingly applied to aid in the diagnosis, prognosis, and management of patients with neurodegenerative diseases, representing a major step closer to realizing personalized medicine.
This Research Topic aims to provide the state-of-the-art on the clinical use and role of biosensing and neuromodulation (especially AI-based) in the early detection, assessment, diagnosis, prognosis, and management of patients with neurodegenerative diseases. Original high-quality studies, as well as reviews, are welcomed. Clinical applications of particular interest include, but are not restricted to, the following:
• AI applications to health records, genetic, biological, clinical, cognitive, behavioral, or other data from patients or at-risk individuals for the early detection, diagnosis, or prediction of outcome of individuals with neurodegenerative diseases
• Use of brain-computer interfaces and wearable sensor devices for the early detection, diagnosis, and prognosis of neurodegenerative diseases
• Use of non-wearable and wearable sensor devices for the assessment and continuous monitoring of symptom severity, drug response and side effects, mood, sleep, cognitive function, or functional status in clinical or home settings
• Applications of noninvasive and invasive brain stimulation techniques in the treatment of neurodegenerative diseases, in particular when combined with AI, brain electrophysiology, or neuroimaging
