Digital Fundamental care

The Purpose of the project is to develop new clinical devices for use of nursing care. We are using user-centric designs and smart technology based on Artificial Intelligence. One of the used technologies is the Internet of Things (IoT), a novel paradigm where objects with unique identities can be integrated into an information network to provide intelligent services for health care. With embedded sensor systems and advanced data analytics and machine learning the heterogeneous data can be transformed into useful form for the caregivers.

Smart Gloves for CPR

Smart Gloves to evaluate the quality of CPR (ResuGloves) The aim of the Smart Glove project is to develop portable, cost-effective and easy to use medical device that will provide real-time feedback, aimed to improve the quality of chest compressions during laypersons’ CPR training and prehospital resuscitation. Once developed and implemented, the smart glove is expected to be valuable to train CPR in communities as well as governmental and private institutions. Besides, the smart glove has the potential to be used by laypersons and inexperienced health professionals both in hospitals and out of hospital real cardiac arrests, particularly in resources limited settings.

Smart Pain Assessment tool based on IoT (SPA)

Sanna Salanterä
Pasi Liljeberhg, PhD, Professor, Department of Future Technologies, University of Turku

The purpose of the SPA project is to benefit from the offered features of the Internet of Things and sensor networks to provide an automatic tool which can detect and assess pain employing behavioral and physiologic indicators such as facial muscle activity, heart rate, blood pressure, breathing rate and galvanic skin response. The aim of this project is to develop a system based on Internet of Things to detect and assess pain in a reliable way by enabling the pain diagnoses in the case when the patient is unable to communicate and express the pain sensations.

Machine Learning for Clinical Information Analytics (ML4CIA)

Laura-Maria Peltonen, Department of Nursing Science, University of Turku
Hans Moen, Department of Future Technologies, University of Turku

This project aims to assess the content of documented care data of adult cardiac patients and to explore the use of machine learning methods and tools to support managers, clinicians, patients and researchers for the purpose of delivering individual-centered, safe and efficient care. Our main focus is on the free-text narratives written by nurses, physicians and allied health professionals, supported by structured data about the patients and their care.

• Sanna Salanterä
• Laura-Mari Peltonen

• Riitta Rosio, PT, MHSc, PhD candidate, Smart Pain Assessment Tool for noncommunicative patients – Early stage development and evaluation
• Desale Tewelde Kahsay, MSc, CRNA, ENP, PhD candidate, Smart Gloves to evaluate the quality of CPR
• Minttu Saari, PhD candidate
• Kristiina Heikkilä, PhD candidate
• Kirsi Terho, PhD candidate

• Tanja Liukas