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Current psychiatric triage for paediatric ADHD and anxiety relies on subjective behavioural checklists that cannot objectively separate conditions requiring opposite pharmacological interventions. I am building a unified computational framework that produces a "Kinematic Phase Space" for the transdiagnostic separation of neuropsychiatric conditions.
The system uses an iPad Pro to extract two mathematically independent biomarkers from a 3-minute spiral tracing task: Kinematic Entropy (Multiscale Sample Entropy of the velocity signal, indexing dopaminergic motor disorganisation) and 8–12 Hz Tremor Power (Welch Power Spectral Density, indexing catecholamine-driven physiological tremor). When plotted as orthogonal axes, these biomarkers define a two-dimensional Phase Space in which neuropsychiatric conditions separate into distinct clusters. I have already retrospectively validated this framework on over 1,000 subjects across seven independently collected clinical datasets (including ADHD-200, EMOTHAW, and PaHaW).
Our immediate goal is to complete the prospective clinical validation required to make a mechanistic claim about the underlying neurobiology of these motor fluctuations. We have established convergent validity using the Bermperidis, Rai & Torres (2024) closed-form analytical bridge for differential entropy.
To achieve the statistical power required to translate this from retrospective theory into prospective clinical reality, I am executing an $N=100$ pilot trial at a paediatric clinic this July. Furthermore, we plan to extend the pipeline to include passive 30 Hz front-camera capture during the spiral task to extract facial micro-movement spikes as a second non-invasive biomarker for autonomic arousal, based on Torres & Elsayed (2026).
Our budget is heavily prioritized toward securing flawless clinical ground-truth data. I have set a minimum goal of $2,500 and a target goal of $10,000. Standard academic grants take 12 months to clear; I need this liquid capital immediately to legally and financially lock in our clinical partner for the July sprint.
The Minimum Viable Threshold ($2,500): Pure Clinical Execution - If we only raise the minimum, 100% of the funds will be deployed directly to the clinical testing bottleneck to ensure the science happens.
$1,500 - Clinical Ground-Truth Licenses: Purchasing 100x Pearson Conners-3 and SCARED digital assessments. This is the absolute core of the validation: without these established psychiatric baselines, we cannot make our mechanistic claims about the Phase Space against traditional peer reviewers.
$1,000 - Institutional Testing Overhead: Covering the Institutional Ethics Committee (IEC) review fees and essential clinical staff stipends at Continua Kids to legally process our patient cohort.
The Target Goal ($10,000): Full Hardware & Clinical Optimization
Reaching the $10k goal allows us to fully secure the clinical testing pipeline while adding the required edge-computing hardware to process the stochastic data locally.
$3,500 - Enhanced Clinical Testing Protocol: Fully funds the 100x Pearson licenses, the IEC fees, and provides increased clinical staff stipends to guarantee a dedicated nurse pipeline (ensuring we can process 5+ patients per day). This ensures we hit our strict $N=100$ statistical power target before the August Nature portfolio submission deadline.
$1,300 - High-Fidelity Capture Hardware: iPad Pro 11-inch & Apple Pencil Pro. Required strictly for the 240Hz touch-sampling rate. Standard tablets drop frames and ruin the Gamma Noise-to-Signal Ratio (NSR) calculations.
$5,200 - Edge-Computing Hardware: M-Max machine. Required to locally compile the 15-script Python pipeline, run the B-Spline smoothing, and calculate multiscale sample entropy on an air-gapped machine without ever uploading sensitive pediatric patient data to cloud servers.
Dev D. Goyal (Principal Investigator & Corresponding Author): 17-year-old independent researcher. I designed the methodology, software pipeline, and formal analysis for the phase space.
Prof. Elizabeth B. Torres (Co-Author & Scientific Advisor): Director of the Sensory Motor Integration Lab and Center for Cognitive Science at Rutgers University. She is supervising the statistical platform for individualized behavioral analyses, the micro-movement spikes methodology, and the Gamma-process analysis.
Failure Cause (Data Corruption): Capturing 240Hz data from hyperactive children is physically chaotic. If children lift the pen mid-spiral, the kinematic traces break. We mitigate this with strict protocols, but data loss is a real risk.
The Failsafe Outcome: If the paper is rejected by our apex tier targets (e.g. Nature Mental Health), we have a predefined cascade strategy. Our primary target is Behavior Research Methods (Springer), cascading to IEEE Transactions on Affective Computing, Computers in Human Behavior, and Frontiers in Digital Health. Regardless of the journal, all analysis code is open-source and will be released on GitHub under an MIT license.
$0 in institutional funding. No external funding was received for the retrospective work. I currently have approximately $1,900 in personal capital ring-fenced as an emergency buffer for this project. I have active applications in the queue for Emergent Ventures and the 1517 Fund, but no capital has been deployed yet.
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