Client: HealthTech client Industry: HealthTech Region: USA
Building a Remote Patient Monitoring system for health providers

Building a Remote Patient Monitoring system for health providers

Our client partnered with Neurons Lab to achieve MVP readiness and prepare their Remote Patient Monitoring (RPM) artificial intelligence solution for commercialization.

Partner Overview

Our client is a scientific start-up that develops Remote Patient Monitoring (RPM) products for health providers. The company needed to launch an MVP in four months and collect user feedback to raise additional venture capital for the commercialization phase.

The team decided to test data-driven approaches for health anomaly detecting and health condition trend forecasting. AI-based monitoring would achieve a reduction in nursing observation costs – a key challenge for healthcare providers.

The team needed to run the whole AI development journey from Ideation, Market Intelligence, Data feasibility testing to ML/DL Models development and integration into the main Product on a tight schedule. Therefore, the company needed a reliable partner with significant expertise in Biosignal processing, DS algorithms, Machine Learning Operations (MLOps), and Product Development lifecycle understanding.


The main challenge was connected to the data layer feasibility. RPM like telehealth, telemedicine, virtual care, and digital health is designed to free healthcare workers from routine tasks, reduce the cost of the care, and unlock access to quality care for many more patients. RPM has to mimic many nurse/doctor functions based on uncertain and subjective data from wearables and smartphones to achieve this.

The project involved dealing with a vast amount of RPM-generated data, which were highly uncertain and subjective (such as video/text-based patient state detection). Besides that, Remote monitoring deals with the continuous real-time data stream and requires real-time processing and events detection. Physiological data is highly volatile, and it is hard to detect patterns and trends. The data collected with RPM has no direct diagnostic value and requires the search and engineering of significant features and models.


The Neurons Lab team defined Algorithmic Model requirements for some of the most critical use cases and checked AI feasibility based on data sourcing and available data health check.

During the Research & Development phase, the team performed knowledge extraction and data mining to find functional relations of patient medical/health monitoring data and evaluate significant predictive features.The predictive power of features connected with a patient’s medical condition was substantial for effective diagnosing.

The team then used Deep Learning models for face/voice/speech/text recognition for patient medical/health/well-being conditions self-assessment and fraud detection. Self-assessment enriches the dataset with symptom labels.

After this, series analysis for patterns and trends recognition were implemented for early detection and forecasting for a medical condition which allowed effective treatment prescription and operative correction.

Statistical models for anomaly detection in the data, patterns, and trends were then used to ensure effective anomaly detection, reducing emergency department attendance and readmission rates.

Finally, the team integrated Minimum Viable Models into the Product with a robust MLOps architecture supporting the whole Model Lifecycle.


Before the project the client had:

  • A list of potential ideas for improving Product Data readiness
  • Unexploited data collected from wearables and smartphones
  • The main use of the RPM app were e-check ins with nurses or doctors

By the end of the project, the team had achieved:

  • AI MVP readiness in four months and prepared to commercial scale
  • MVP-proven product hypothesis: Diseases knowledge extraction, patterns, and trends recognitions increase the efficiency of diagnosing and treatment programs by 30-40%
  • Effective anomaly detection reduces emergency department attendance and readmission rates by up to 50%
  • Effective medical condition early detection and forecasting reduce nursing costs up to 40%

About Neurons Lab

Neurons Lab is an AI service provider that partners with fast-growing companies to co-create disruptive AI solutions, empowering them to gain a competitive edge in their industries.

Our goal is to help businesses to unlock the full potential of AI technologies with support from our diverse and highly skilled team, made up of applied scientists and PhDs, industry experts, data scientists, AI developers, cloud specialists, user design experts and business strategists with international expertise from across a variety of industries.

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