Biomedical Engineering

Focus:

The research within the Biomedical Engineering group focuses on reliable non-invasive physiological data acquisition and signal processing. The aim is to find solutions to real problems and the projects are performed in close collaboration with the public sector.


Division:

Division of Intelligent Future Technologies

The Biomedical engineering group´s research is focused towards multisensor systems for measurements of physiological parameters. The systems are developed to be wearable, also including artificial intelligence and wireless communication to enable free mobility.

Project TitleStatus
Brain technology in stroke rehabilitation – increasing motor recovery active
Digitalization of HVDC grids by means of smart data discovery active
Embedded Sensor Systems for Health Plus active
ITS ESS-H Industrial Graduate School in Reliable Embedded Sensor Systems active
RECOG: Closed-loop neurofeedback innovation for cognitive rehabilitation active
Algorithms & Protocols Enhancing Mobility Support in Wireless Sensor Networks Based on Bluetooth and Zigbee finished
Alternative input and control devices for disabled finished
CAMI - Artificially intelligent ecosystem for self-management and sustainable quality of life in AAL (Ambient Assisted Living) finished
CogTrack: Real-Time Cognitive Tracking as an Approach to Identify Substance Abuse finished
Continuous monitoring of COPD patients finished
Development of a telemetric system for bioelectrical monitoring finished
ecare@home finished
ESS-H - Embedded Sensor Systems for Health Research Profile finished
Giraff + Combining social interaction and long term monitoring for promoting independent living finished
IEMI: Intelligent extraction of mental imagery during stroke rehabilitation finished
Improving Accuracy of the Cardiac Stress Test by Applying Advanced Signal Processing Methods to an Embedded Sensor Setting finished
Innocare finished
Interaktiv teknik för långsiktigt stöd av fysisk aktivitet hos äldre finished
Investigation of needs and requirements related to monitoring of physical activity in daily life: A qualitative study of older adults' experiences from using activity bracelets finished
IPOS, Integrated Personal Health Optimizing System finished
Kompetensnav Inbyggda Sensorsystem för hälsa / Competence hub Embedded Sensor Systems for Health finished
LACTA - a new method to identify the lactate threshold finished
MAMACELL finished
Measurement system for prevention of pressure sores finished
Micro sensors for better health finished
Microwaves in biomedicine finished
NovaMedTech finished
NovaMedTech II finished
PEWIT finished
RALF3 - Software for Embedded High Performance Architectures finished
Respiratory monitoring and other clinical applications of measurements of carbon dioxide in expiratory air finished
SALUTOGEN - Seniors’ Activity and quality of Life sUpported by Technology thrOugh deliGht, Engagement and iNterest finished
Stabilizing control of electrical drives finished
STARK - Skattning Tidigt av fysisk förmåga för Alla och Riktat stöd ger Kunskap och minskad fallrisk senare i livet finished
Systematiska översikter av hälso- och välfärdsteknik med bred implementering finished
Technology support for health promotive behavioural change finished
Wireless sensors for monitoring physiological parameters finished

[Show all publications]

User-centered requirements engineering to manage the fuzzy front-end of open innovation in e-health (Sep 2021)
Maria Ehn, Mattias Derneborg , Åsa Revenäs , Antonio Cicchetti
International journal of medical informatics (Int J Med Inform)

Using Patch ECG Device During Lower Third Molar Surgery (Sep 2021)
Ana Prkic , Ivan Tomasic, Antonella Lesin , Tina Becic , Danijela Kalibovic Govorko , Ivana Medvedec Mikic
International Journal of Reliable and Quality E-Healthcare (IJRQEH)

Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review (Aug 2021)
Annica Kristoffersson, Jiaying Du, Maria Ehn
Sensors, SI: Sensor Technology for Fall Prevention (Sensors)

Nocturnal digital surveillance in aged populations and its effects on health, welfare and social care provision (Jun 2021)
Matt Richardson , Maria Ehn, Sara Landerdahl Stridsberg , Ken Redekop , Sarah Wamala Andersson
BMC Health Services Research (BMC H Serv Res)

EEG non-stationarity across multiple sessions during a Motor Imagery-BCI intervention: two post stroke case series (May 2021)
Elaine Åstrand, Jeanette Plantin , Susanne Palmcrantz , Jonatan Tidare
10th International IEEE EMBS Conference on Neural Engineering (NER'21)

Integrating Key User Characteristics in User-Centered Design of Digital Support Systems for Seniors’ Physical Activity Interventions to Prevent Falls (Dec 2020)
Åsa Revenäs , Ann-Christin Johansson , Maria Ehn
JMIR Research Protocols (JMIR Res Protoc)

Maria Lindén, Professor

Email: maria.linden@mdh.se
Room: U1-139
Phone: +46-21-101548