Alzheimer Disease Clinical Trial
Official title:
Studies of Brain and Body Interaction at Rutgers University
NCT number | NCT03672266 |
Other study ID # | BrainBody |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | August 1, 2018 |
Est. completion date | July 1, 2019 |
The goal of this study is to characterize biophysiolgoical signals as a comprehensive profile of the nervous systems in order to understand interactions between the brain and body, while an individual performs naturalistic behaviors (ex. walking, pointing) and while breathing at a slow controlled pace. The investigators aim to study these interactions among a variety of populations, from healthy individuals to those with disorders such as Autism Spectrum Disorder(s), including those who may also have an ADHD (Attention-deficit/hyperactivity disorder) diagnosis, Asperger's Syndrome, Alzheimer's Disease, and/or Fragile X syndrome
Status | Recruiting |
Enrollment | 100 |
Est. completion date | July 1, 2019 |
Est. primary completion date | July 1, 2019 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | N/A and older |
Eligibility |
Inclusion Criteria: Clinical diagnosis of any one of the following: - Autism Spectrum Disorder(s) - ADHD - Asperger's syndrome - Alzheimer's disease - Fragile X syndrome - Parkinson's disease Exclusion Criteria: |
Country | Name | City | State |
---|---|---|---|
United States | Rutgers University | Piscataway | New Jersey |
Lead Sponsor | Collaborator |
---|---|
Rutgers University |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Unitless Stochastic Signatures of Biophysiological Signals, consisting of the Empirically Estimated Shape and Dispersion (scale) Parameters of Probability Distribution Functions | Biophysical signals extracted from the brain and heart (mV) and motor kinematics (m/s) activities will be normalized and scaled to a unit-less waveform dataset. The standardized unitless data set will account for anatomical differences and will then be empirically characterized as families of probability distributions for each person, by the shape and scale parameters of continuous families of probability distribution functions with variable shapes and dispersion (noise to signal ratio). These parameters are objective biomarkers for a variety of disorders, and inform the level of noise-to-signal ratio and predictability of an individual's biorhythms (Torres, 2018). Torres, E. (2018). Objective Biometric Methods for the Diagnosis and Treatment of Nervous Systems Disorder: Elsevier |
through study completion, an average of 1 year | |
Secondary | Brain and Body Connectivity metrics and Derived Geometric and Topological Indexes from the Network Connectivity Model and Inverse Kinematic Model | Based on a mathematical network connectivity model (Rubinov and Sporns, 2010), the investigators will measure how the brain and body (central and peripheral networks) interact while participants perform naturalistic tasks. Based on the physiological data from the brain and heart activities (mV) and motor kinematics (m/s), the experimental analytics provide a model that measures unit-less connectivity measures between different parts of the body. Namely, they are degrees (i.e., number of links connected to a node), shortest path length (a basis for measuring integration), number of triangles (a basis for measuring segregation), and modularity. Further, analyzes of forward and inverse kinematics dynamics will be derived from the three dimensional positional and orientation data of the kinematic sensors along with the person's mass and bone-length data, using state of the art models of inverse dynamics (Torres, 2001). | through study completion, an average of 1 year | |
Secondary | Information theoretic metric | Based on an information theoretic model (Shannon,1956), the investigators will quantify the probability distribution function of measured biophysical signals from the brain and heart (mV) and kinematics (m/s), and characterize information passing across the central and peripheral nervous systems, including as well the autonomic nervous system. | through study completion, an average of 1 year |
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