Neurodegenerative disorders (ND) are a common and growing cause of mortality and morbidity worldwide, particularly in older people. As life spans continue to increase, the incidence of the neurodegenerative diseases is expected to increase as well.
In addition to such pathological threats, adults above 60 years show increasing vulnerability to broad decline in memory, attention, and multi-tasking. Cognitive impairment is often a comorbidity with ND and can even predict imminent motor decline or neuropsychiatric symptoms.
ND, such as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD), develop progressively through several years. After an asymptomatic stage (only revealed by biomarker evidence), cognitive and neuropsychiatric symptoms often start to appear and then worsen over time, until they lead to a loss of autonomy in activities of daily living.
At present, there is no cure for these disorders, but multi-domain interventions (targeting simultaneously multiple areas, such as cognition, lifestyle, and physical activity) are showing promising results in delaying ND progression. The earlier and more personalized the intervention, the more effective the results. For this reason, detecting ND in early stages is an important clinical and research challenge.
Biomarkers can predict risk for AD, PD, and other ND, several years before the clinical symptoms appear but today these tests are invasive, expensive, and realized only in specialized clinical settings.
For these reasons, there is growing interest in finding new approaches that can be employed to investigate early signs of cognitive, motor, and behavioral decline that can be indicative of ND which are non-invasive, rapid to measure and usable also outside specialized clinics. Basic research with wearable sensors, new Information and Communication Technologies (such as automated video and audio-analyses), Virtual Reality video games, phone or tablet applications, olfactory tests, as well as artificial intelligence techniques show promise to reveal changes in subjects’ abilities and behaviors, which in turn can support the clinician in early identification of subtle disorders.
With this Research Topic we aim at bringing together papers dealing with non-invasive tools, methods or technology applied in assessments of the cognitive and/or motor performance and neuropsychiatric symptoms in cohorts of elderly adults with ND or with diminished performance in higher cognitive function.
This Research Topic is widely open to contributions that target the following topics:
• Novel protocols to highlight the early deterioration of motor, cognitive and/or neuropsychiatric abilities, especially if they promote a multimodal approach;
• Identification of prodromal signs and symptoms that can help in early assessment of neurodegenerative conditions and/or cognitive decline;
• Novel technologies (included ICTs and Internet of Things) to support the clinicians in the objective assessment of motor, cognitive and neuropsychiatric patterns in the elderly population;
• Novel AI-based techniques to predict the trajectory of the early signs of neurodegenerative disorders or cognitive decline over the time.
All paper types are welcome, including research articles, method papers, reviews and mini-reviews, and opinion papers.
Neurodegenerative disorders (ND) are a common and growing cause of mortality and morbidity worldwide, particularly in older people. As life spans continue to increase, the incidence of the neurodegenerative diseases is expected to increase as well.
In addition to such pathological threats, adults above 60 years show increasing vulnerability to broad decline in memory, attention, and multi-tasking. Cognitive impairment is often a comorbidity with ND and can even predict imminent motor decline or neuropsychiatric symptoms.
ND, such as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD), develop progressively through several years. After an asymptomatic stage (only revealed by biomarker evidence), cognitive and neuropsychiatric symptoms often start to appear and then worsen over time, until they lead to a loss of autonomy in activities of daily living.
At present, there is no cure for these disorders, but multi-domain interventions (targeting simultaneously multiple areas, such as cognition, lifestyle, and physical activity) are showing promising results in delaying ND progression. The earlier and more personalized the intervention, the more effective the results. For this reason, detecting ND in early stages is an important clinical and research challenge.
Biomarkers can predict risk for AD, PD, and other ND, several years before the clinical symptoms appear but today these tests are invasive, expensive, and realized only in specialized clinical settings.
For these reasons, there is growing interest in finding new approaches that can be employed to investigate early signs of cognitive, motor, and behavioral decline that can be indicative of ND which are non-invasive, rapid to measure and usable also outside specialized clinics. Basic research with wearable sensors, new Information and Communication Technologies (such as automated video and audio-analyses), Virtual Reality video games, phone or tablet applications, olfactory tests, as well as artificial intelligence techniques show promise to reveal changes in subjects’ abilities and behaviors, which in turn can support the clinician in early identification of subtle disorders.
With this Research Topic we aim at bringing together papers dealing with non-invasive tools, methods or technology applied in assessments of the cognitive and/or motor performance and neuropsychiatric symptoms in cohorts of elderly adults with ND or with diminished performance in higher cognitive function.
This Research Topic is widely open to contributions that target the following topics:
• Novel protocols to highlight the early deterioration of motor, cognitive and/or neuropsychiatric abilities, especially if they promote a multimodal approach;
• Identification of prodromal signs and symptoms that can help in early assessment of neurodegenerative conditions and/or cognitive decline;
• Novel technologies (included ICTs and Internet of Things) to support the clinicians in the objective assessment of motor, cognitive and neuropsychiatric patterns in the elderly population;
• Novel AI-based techniques to predict the trajectory of the early signs of neurodegenerative disorders or cognitive decline over the time.
All paper types are welcome, including research articles, method papers, reviews and mini-reviews, and opinion papers.
