Annica Kristoffersson, Associate Professor, Head of Division

E-mail:
annica.kristoffersson@mdu.se
Room:
U1-129
Phone:
+46 21 10 31 40
Division:
Division of Intelligent Future Technologies
Research groups:
Biomedical Engineering
Health-promoting engineering


Annica Kristoffersson is head of division and associate professor in medical- and health engineering. Annica is project leader, and researcher, for the HÖG-project PRE-fall (Personalized fall Risk reduction based on Early detection of deteriorated physical abilities). She is also involved in several internal medicine- and health engineering projects which focus on monitoring physiological parameters.

For Annica, it is important to ensure that the user perspective is taken into consideration during development and evaluation of technology. Current primary focuses are: fall prevention and stimulation of physical activity among type 2 diabetes mellitus patients.

Annica has previously conducted research within human-robot interaction, smart homes and evaluations thereof. She recieved her PhD degree in Information Technology in 2013 from Örebro University. The topic of the PhD thesis was: Measuring the quality of interaction in mobile robotic telepresence using presence, spatial formations and sociometry. (see thesis)

Annica has worked as a researcher, work package leader, test site coordinatior, co principal-investigator and assistant project manager in  a number of projects during her time at Örebro University. Projects include: the AAL JP project ExCITE (Enabling Social Interaction Through Robotic Telepresence), the FP7 project GiraffPlus (Combining social interaction and long term monitoring for elderly), the Länsförsäkringar Research Foundation project "En metod för att mäta ett sensornätverks inverkan på Trygghet, the Vinnova testbed "Smarta äldre", and the Knowledge Foundation distributed research environment E-care@home.

Previously, Annica was involved as a researcher in the research profile ESS-H+ (Embedded Sensor Systems for Health Plus) in which she was also the overall responsible for ensuring that the user perspective was considered.

I am PI for the KKS-project PRE-fall and my current research is mainly focused at the prevention of falls among middle-aged adults through detecting early deteriorations in strength and balance and the provision of encouraging support to reduce the physical deficiencies. I am the main supervisor for PhD student Agnieszka Jaff who focuses at motivating people people to performed recommended physical exercises through digital tools.

I am also involved in several projects regarding measuring and analyzing physiological parameters, e.g., bioimpedance and photopletysmography.

Previously, in the research profile ESS-H+ (Embedded Sensor Systems Plus), i was involved in the work packages: fall prevention and gait monitoring, mitigating type 2 diabetes mellitus using technology and physical activation, and IT-platform for health monitoring. I was also co-supervisor of the industrial PhD student Ann-Louise Lindborg (lic 2021) who developed robotic eating assistance devices for increased independence.

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My research conducted at Örebro University up until 2019 can be divided into the following areas:

To measure interaction quality.

Interaction via telepresence robots. During my PhD studies, conducted within the AAL JP-project ExCITE, I measured interaction quality along three tracks: observations (F-formations), objective quantitative measures (sociometry), and subjective questionnaires (perceives social and spatial presence and ease-of-use).

The PhD student Sai Pathi Krishna (who I co-supervised to his defense in April, 2024), used the F-formation theory (how we spatially position ourselves with respect to each other during interaction) and proxemics theory, while developing algorithms such that social robots can automatically position themselves in a natural way with respects to humans.

Social robot as an exercise coach for older people. The other Phd student Neziha Akalin (who I also co-supervised to her defense in April 2022), developed an adaptive social robotic system. The system should offer physical and cognitive traning at different difficulty levels depending on the individual and his/her development. The robot should be able to vary its social behavior.  Performance, facial expressions and physiological parameters were used as input.

Can sensor networks increase safety and security ("trygghet")? Many products designed for older people are said to increase safety and security in marketing. What this means, however, is not clearly defined but it involves physical, mental as well as existential aspects. In one of my previous projects, we attempted to study safety and security through a series of questionnaire administered to older people and their relatives during a five month evaluation of a sensor-based cognitive assistive technology. To measure safety and security is difficult but the study provided an increased insight in a sensor network's impact on quality of life and its usability. The study also provided an insight in the importance of building in privacy-by design.

What smart technology do we (the older people) want? This area involves 19 longitudinal test sites with observations of usage, interviews, administration of questionnnaires etc as well as the development of personas (older people, relatives, care professionals) and use cases for a potential E-care@home system.

In sum, my research profile, I am intersted in human-robot interaction, smart homes and how internet communication technologies can be developed to support a safe and secure life during aging. This user perspective should be considered during development of new products. Here, knowledge about the context in which older people are in, and how needs may change over time, is included.

My research has resulted in a number of publications. See my Google Scholar profile for information.

PhD students supervised as main supervisor:

Agnieszka Jaff

PhD students supervised as assistant supervisor:

Ann-Louise Lindborg (former)
Neziha Akalin (former)
Sai Krishna Pathi (former)