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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
What is the study for? The goal of this study is to characterize biophysical signals simultaneously co-registered from the person's nervous systems. To that end the investigators use multiple wearable biosensors (electroencephalogram, electrocardiogram, kinematics,etc.) and have the person move naturally during activities that are similar to what the person would do in activities of daily living. These include walking, walking with a metronome in the background and walking while breathing at the metronome's pace. The purpose of the study is to learn about the inherent properties of the biorhythms of each person in order to build a proper neurotypical scale and measure the departure of several groups of subjects from this typical ranges. These include Autism Spectrum Disorder(s), ADHD (Attention-deficit/hyperactivity disorder) , Asperger's Syndrome, Alzheimer's Disease, and/or Fragile X syndrome. This study does not provide any recommendations of diagnosis or treatment. It is merely a characterization of the person's biorhythms across these conditions.
What will the participant do? The participant will perform naturalistic behaviors (ex. walk naturally around the room, point at an object) while hearing a metronome beating in the background. At certain points, the participant will be instructed to breathe along with the beat of the metronome. During this experiment, the participant will be wearing a wireless Electroencephalographic (EEG) cap to record brain activity, wireless motion sensors around the body to record movement, and wireless electrocardiogram (ECG) on the chest to record heart activity.The participant will also be wearing Zeblok insoles placed inside their shoes, to monitor their gait. The recorded biophysical signals are to be used to assess biorhythms of the nervous system from an already diagnosed participants and neurotypical participants, as this experiment is designed to study and characterize the biophysical signals of various populations. The study does not provide criteria for diagnosis, nor does it provide recommendations for treatments. The study is merely characterizing the ranges of biophysical data and their variability across different populations to measure departure from neurotypical features. Please note, wearing a wireless EEG cap will involve applying electrode gel (similar to hair gel) on the participant's hair.
How long is the experiment? The experiment itself will take 45 minutes - comprising 3 walking trials lasting 15 minutes each - but this can be reduced depending on the participant's disposition. Breaks for light refreshments and sensory toys will be provided as needed. The setup will take an additional 15-30 minutes.
Where/when does the experiment take place? The experiment will be conducted at the Sensory-motor Integration Lab, Psychology Building on Busch campus, at Rutgers University (152 Frelinghuysen Road, Piscataway, NJ 08854). If necessary the experiment may also be conducted at the participant's home. Based on the availability of the participant and the experimenter, the date and place can be coordinated any day and time of the week - including weekends. Additional members of staff can provide on-site childcare for siblings upon request.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Neurological Disorder | Individuals with neurological disorders such as Autism Spectrum Disorder(s), including those who may also have an ADHD diagnosis, Asperger's Syndrome, Alzheimer's Disease, Fragile X syndrome, Parkinson's disease, Lewy Body Dementia, and/or Frontoparietal Dementia | ||
| Neurotypical | Healthy individuals with no known neurological disorders |
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| Measure | Description | Time Frame |
|---|---|---|
| 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 |
| Measure | Description | Time Frame |
|---|---|---|
| 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). |
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Inclusion Criteria:
Clinical diagnosis of any one of the following:
Exclusion Criteria:
-
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No restriction from which the cohort will be selected
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Rutgers University | Piscataway | New Jersey | 08854-8020 | United States |
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| ID | Term |
|---|---|
| D002659 | Child Development Disorders, Pervasive |
| D001289 | Attention Deficit Disorder with Hyperactivity |
| D020817 | Asperger Syndrome |
| D000544 | Alzheimer Disease |
| D020329 | Essential Tremor |
| D020961 | Lewy Body Disease |
| ID | Term |
|---|---|
| D065886 | Neurodevelopmental Disorders |
| D001523 | Mental Disorders |
| D019958 | Attention Deficit and Disruptive Behavior Disorders |
| D000067877 | Autism Spectrum Disorder |
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| through study completion, an average of 1 year |
| 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 |
| D003704 | Dementia |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D024801 | Tauopathies |
| D019636 | Neurodegenerative Diseases |
| D019965 | Neurocognitive Disorders |
| D009069 | Movement Disorders |
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D000080874 | Synucleinopathies |