Our solution

PHRESH is designed for time-critical healthcare. Using wearable sensors, secure connectivity, and AI-driven analysis, the system enables rapid detection of emergencies and supports preventive intervention. Caregivers gain real-time insights to reduce response times and improve outcomes.

In the Netherlands, PHRESH powers the connected ambulance. Paramedics are equipped with tools to monitor patients on the way to the hospital and transmit data—EEG signals, continuous blood pressure, speech, and video—directly to emergency teams. This seamless data exchange allows hospitals to prepare treatment in advance, saving valuable minutes in acute care where every second counts.

Technical Solutions

The following high-level technical solutions will be explored and implemented:

Advanced sensor technologies for accurate data collection

Artificial Intelligence (AI) and machine learning for data analysis and risk prediction

Privacy-preserving data sharing to protect patient information

Quantum-secure communication for optimum data security

Real-time cyber threat prevention to ensure system integrity

Edge networking capabilities for faster and network data processing

Next-generation networks (i.e. 6G) for optimal connectivity

PHRESH Framework

The PHRESH project aims to apply this framework to clinically relevant use cases where the core concepts can be summarised as follows:

Sense for health

Continuous and non-invasive sensors gathering medical and behavioural data
Clinically validated data (e.g. cardiovascular diseases, support hypoxic and neurologic diagnoses)
Create patient-specific and collective risk profiles in a privacy-preserving manner

Alert to prevent

Use individual health data to generate risk profiles and personalise alerts
Provide treatment support and inform relevant patients (e.g. kidney emergency response teams)

Connected and mobile care

Share triage information between stakeholders: paramedics, and hospitals via modern networking technologies
Interoperability among technologies such as EDs and continuous blood pressure monitoring provide real-time, high-quality data

Secure and Collaborative Sensing

Use collected data for collaborative learning to improve AI models, risk assessment, and care quality
Contribute to policy-making through data sharing