Industry

Healthcare

Core Technologies

Python 3.8.10
MS SQL 2014
OpenCV (Video processing, frame extraction)
MediaPipe (Face & body landmark detection)
PoseNet (Body joint detection)
LSTM Neural Networks (Movement sequence assessment)
Speech Recognition Library (Audio-to-text conversion)
Windows-based MVC architecture
VS Code & Jupyter Notebook

Project Solution

We engineered an advanced neurocognitive assessment platform designed to support stroke patients through continuous monitoring, automated testing, and AI-driven evaluation. The solution uses a 3D animated model to guide patients through specific movements and commands, while integrated artificial intelligence (AI) interprets facial expressions, body posture, response time, and movement accuracy in real time. Doctors and hospital staff manage assessments through a dedicated interface that captures patient details, initiates examinations, and generates final reports. The system enables reliable neurological evaluation without disrupting standard patient care.

The Client

The organization, led by an expert in neurology and a university faculty member, is dedicated to modernizing neurological evaluations. Their goal is to automate cognitive and motor assessments for stroke patients using objective, data-driven methods to ensure timely detection of neurological decline.

The Approach

We implemented a structured and scalable approach to build a dual-interface system that connects clinicians and patients in real time.

Understanding the Core Needs

Provide real-time neurocognitive assessment at a patient’s bedside.
Offer a 3D interactive model in the patient’s native language (English, Gujarati, Spanish)
Capture and interpret facial expressions, body movements & verbal responses.
Reduce nurses' and clinicians' manual workload.
Ensure accuracy, consistency, and minimal setup time.

The Solution

We developed a synchronized two-screen application:

1. Patient-Side Module

A 3D animated model instructs the patient to perform specific movements.
Commands are delivered visually and in the patient's chosen language.
A camera tracks the patient’s actions and expressions in real time.

2. Doctor/Staff-Side Application

Secure login with access to patient demographic and provider details
Ability to select patients and initiate examinations
Real-time visibility into patient responses
Automated scoring of TD points using facial and body landmark data
Final report generation for each completed exam

AI-Driven Assessment Workflow

This approach ensures precision, minimal disruption to care, and continuous, reliable data collection.

The Impact

The platform significantly enhances diagnostic speed, accuracy, and patient engagement by automating the entire neurological evaluation process. AI-driven analysis reduces assessment time by 60–70% and improves scoring reliability through pose detection, facial landmark mapping, and LSTM-based interpretation. The multilingual 3D model increases patient responsiveness by up to 40%, while clinicians benefit from clear, data-driven insights into behavioral changes, movement accuracy, and exam progression. Operationally, the system reduces manual nurse involvement, minimizes errors, supports faster repeatable assessments, and maintains organized digital records for long-term continuity of care.

Want to Get Your AI-Powered Diagnostics Project Off the Ground?

We help healthcare organizations modernize neurological evaluation through real-time automation, machine learning, and seamless user experience design. Whether you’re optimizing existing workflows or building a next-gen assessment platform, our experts can guide you end-to-end.

AI-Powered Neurocognitive Assessment & Stroke-Care Automation