About this Research Topic
As the most common neurodegenerative movement disorder, Parkinson’s Disease (PD) has enormous impact on health care systems around the world. While traditionally much emphasis has been placed on the motor aspects of the disease, it is increasingly recognized that PD is a multisystem disorder, and many of the non-motor features play at least as important a role in impacting overall quality of life.
There are a number of new technologies that may greatly assist in early diagnosis, monitoring and treatment of this disease. Modern neuroimaging technologies, including MRI, EEG, MEG, PET, and CT are able to noninvasively examine the diseased brain and investigate the underlying neural systems in PD, resulting in powerful approaches for disease detection and monitoring. New data fusion methods can combine information from complementary technologies allowing for comprehensive assessment. New lightweight and wireless sensors can monitor movement, electrodermal responses, temperature and heart rate. Non-invasive electrical stimulation can modulate brain activity, providing new unexplored avenues of treatment.
In order to have an overview of new technologies for PD research and create a platform to discuss how these can be used to diagnosis, assess and treat PD, for this Research Topic, we are interested in high quality original research and review articles. Potential subtopics include but are not limited to the following:
- Biomarkers of PD based on structural or functional imaging
- Biomarkers of non-motor aspects of PD
- Sensors for recording motion, heart rate, temperature and electrodermal response
- Algorithms for preprocessing (e.g. artifact rejection) from sensor recordings for PD monitoring
- Novel machine learning approaches applied to sensor and/or clinical PD data
- Non-invasive stimulation methods applied to PD (e.g. TMS, electrical stimulation)
- Data fusion methods pertinent to disease-related biodata
There are a number of new technologies that may greatly assist in early diagnosis, monitoring and treatment of this disease. Modern neuroimaging technologies, including MRI, EEG, MEG, PET, and CT are able to noninvasively examine the diseased brain and investigate the underlying neural systems in PD, resulting in powerful approaches for disease detection and monitoring. New data fusion methods can combine information from complementary technologies allowing for comprehensive assessment. New lightweight and wireless sensors can monitor movement, electrodermal responses, temperature and heart rate. Non-invasive electrical stimulation can modulate brain activity, providing new unexplored avenues of treatment.
In order to have an overview of new technologies for PD research and create a platform to discuss how these can be used to diagnosis, assess and treat PD, for this Research Topic, we are interested in high quality original research and review articles. Potential subtopics include but are not limited to the following:
- Biomarkers of PD based on structural or functional imaging
- Biomarkers of non-motor aspects of PD
- Sensors for recording motion, heart rate, temperature and electrodermal response
- Algorithms for preprocessing (e.g. artifact rejection) from sensor recordings for PD monitoring
- Novel machine learning approaches applied to sensor and/or clinical PD data
- Non-invasive stimulation methods applied to PD (e.g. TMS, electrical stimulation)
- Data fusion methods pertinent to disease-related biodata
Keywords: Parkinson’s Disease, non-motor biomarker, non-invasive technology, wireless sensor, stimulation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
