Early Parkinson’s Insights from Hand-Drawn Patterns

NeuroSketch is a digital diagnostic tool that detects early signs of Parkinson’s through simple spiral and sine wave drawings. We worked with the client to design and engineer the solution end-to-end, from an accessible drawing interface for older adults to an AI/ML pipeline that transforms sketches into reliable neuromotor insights. The result is a non-invasive, scalable, and clinician-ready screening tool.

NeuroSketch prediction history dashboard shown on a laptop
NeuroSketch logo

70%

faster screenings compared to conventional neurology visits

85%

model accuracy in detecting early Parkinsonian signs

3X

higher accessibility with at-home, self-administered tests

How We Engineered a Digital Pathway for Preventive Neurology

The client, a digital health startup, faced a critical challenge: early detection of Parkinson’s is vital, but current diagnostic tools are invasive, costly, and inaccessible for regular screening. We partnered with them to design and engineer NeuroSketch, a domain-informed, AI-powered diagnostic platform. By combining expertise in AI/ML, mobile UX for older adults, and secure health data management, we built a tool that empowers both patients and clinicians with real-time, actionable insights.

NeuroSketch prediction dashboard shown on a laptop placed on rocks

Use Cases

Sketch Capture Guidance

At-home spiral/sine tests on mobile or tablet with stroke smoothing for reliability.

HOG-based signal extraction

Measures jitter, angle, amplitude to surface tremor patterns.

Dual-pattern protocol

Standardizes tasks for consistent results across sessions/devices.

Instant, explainable scoring

RF/XGBoost probabilities with heatmaps & velocity maps.

Clinician access & sharing

Secure portal, session tracking, consented result exchange.

Longitudinal tracking

History, trendlines, stability index for remote monitoring.

Tech Stack

  • React Native
  • React
  • react-native-canvas
  • Go API Gateway
  • Flask microservices
  • JWT + Firebase Auth
  • OpenCV (HOG)
  • scikit-learn (RF, XGBoost)
  • AWS ECS
  • Docker
  • S3
  • Helm
  • GitHub Actions
  • HIPAA-compliant data handling

Explore More Case Studies.

NutriBot Dashboard on phone

NutriBot

Developed an AI-powered nutrition assistant that personalized meal planning and automated patient engagement workflows.

25%higher patient adherence to diet plans
40%increase in user engagement with providers
PrideLedger Dashboard on phone

PrideLedger

Built a blockchain-based platform that secured financial transactions, automated reconciliations, and improved auditability.

70%Reduced manual processing time
35%Increased reporting accuracy

Get in touch to discuss your software vision with industry experts

Comma Icon

What stood out the most was how easy it was to communicate with their team. We always knew where things stood, and there were no surprises.

Author Avatar

CEO, DigitArtisan