RESC and the Swiss Paraplegic Foundation awarded research grant to promote technologies for clinical decision making in spinal cord injury
The ETH RESC – Swiss Paraplegic Foundation research programme funded a promising project aimed at developing novel sensing technology and artificial intelligence methods for monitoring autonomic dysregulation for individuals with a spinal cord injury (SCI).
The research programme aims to drastically change medical care for people with SCI, from a medical guideline-driven standardised follow-up routine to an individualised, risk-stratified interaction, including the needs and expectations of the affected persons. Funding for this programme is supported by RESC’s strategic partner the Swiss Paraplegic Foundation within the framework of external external page ETH’s Rehab Initiative.
iAD - An Intelligent Prediction of Autonomic Dysregulation through Bladder and Cardiac Sensing
Problem
People with spinal cord injuries (SCI) above the 6th thoracic level (T6) often experience a serious condition named Autonomic Dysreflexia (AD). This happens when the body loses control over automatic functions like blood pressure regulation. AD causes sudden and extreme spikes in blood pressure, which can reach life-threatening levels (up to 300 mmHg). If left unmanaged, these episodes can lead to strokes, heart attacks, and other severe complications. Unfortunately, many individuals struggle to recognise AD in daily life.
Some of the leading triggers of AD are bladder management events, such as overfilled bladders, urinary tract infections or blocked catheters. Managing bladder volume is critical for preventing AD and maintaining overall health. However, the existing medical system and clinical practice do not provide a real-time, accurate, and non-invasive way to continuously track bladder volume and blood pressure together in an ambulatory setting.
Solution: A Smart Wearable Device for Early Detection
The project is developing a wearable-based, non-invasive system that will continuously monitor both urine volume in the bladder and vital signs to predict AD episodes. The system will use advanced sensors and Artificial Intelligence (AI)-based analysis to detect early warning signs, providing real-time alerts before a dangerous spike occurs.
The project leverages the combined expertise of three research labs and the Neuro-Urology department of the Swiss Paraplegic Centre (SPZ) to develop a wearable-based, non-invasive system for continuous monitoring of bladder urine volume and blood pressure, aiming to predict and prevent AD episodes. The Center for Project-Based Learning (PBL) lead by PD Dr. Michele Magno advances both embedded software and hardware for the UROPATCH, optimising algorithms for bladder volume estimation. The Sensing, Interaction & Perception Lab (external page SIPLAB) headed by Prof. Christian Holz leads the development of multi-modal processing, focusing on embedded machine learning for real-time AD detection. The Spinal Cord Injury & Artificial Intelligence (SCAI) Lab headed by Dr. Diego Paez leads the data collection and multimodal sensing integration from multiple wearables for real-time feedback of AD. Dr. med. Jürgen Pannek, head of Neuro-Urology at the external page SPZ , provides clinical expertise, guiding patient selection and validating bladder function assessments in both normal and neurogenic individuals.
This technology will bring to:
- Help individuals with SCI monitor their bladder function, reducing the risk of AD.
- Act as a biofeedback tool, teaching individuals how to manage their bladder at safe volumes to prevent sudden blood pressure spikes.
- Improve AD detection by analyzing cardiovascular and urological changes, helping both individuals and healthcare providers manage the condition more effectively.
Why This Matters
Cardiovascular disease is one of the leading causes of death among people with SCI, where AD is significantly linked to cardiovascular disease and reducing life expectancy. However, early detection and intervention can prevent severe health risks and improve quality of life. The project aims to bridge this gap by introducing a real-time, user-friendly monitoring system that can be used at home or in clinical settings.
By developing this smart monitoring technology, we hope to transform AD management—offering a safer, more effective way to prevent life-threatening complications and improve long-term health outcomes for individuals with SCI.
Project timeline: Q1/2025 – Q4/2027