Annica Kristoffersson, Associate Professor, Senior Lecturer

Annica Kristoffersson is an associate professor in medical- and health engineering working mainly as 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.

She is currently the co-supervisor of one PhD student in Computer Science at Örebro University since spring 2017 and one industrial PhD student in Electronics at Mälardalen University since 2020.

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

Prior research in the research profile ESS-H+ (Embedded Sensor Systems Plus).

Fall prevention and gait monitoring. One of the subprojects of ESS-H+ focused at fall prevention and gait monitoring. The current research comprised: (1) assessments of needs and requirements on technology through the interviews with staff at an Orthopaedic clinic in Region Västmanland, (2) the conduction of a literature study to (a) determine which requirements can possibly be met by existing technology and (3) to outline where technology development is needed to fulfil requirements. 

Mitigating type 2 diabetes mellitus using technology and physical activation. The conduction of a case study on how physiological and quality of life aspects among T2DM patients are affected by following a specific physical activity scheme (guide and follow up). Survey on (1) what information Swedish nurses specialized on the patient groups provide non-insulin treated T2DM patients with and (2) what information the non-insulin treated T2DM patients perceive that they have obtained.

IT platform for health monitoring. Work towards a generic middleware for embedded sensor systems transmitting health parameters following the MDR is ongoing.

In addition, I am co-supervisor of the industrial PhD student Ann-Louise Lindborg (lic 2021, currently on leave) who develops robotic eating assistance devices for increased independence.


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 am currently a co-supervisor for), uses 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 am also a co-supervisor for until April 28th, 2022 when she defends), develops an adaptive social robotic system. The system shall offer physical and cognitive traning at different difficulty levels depending on the individual and his/her development. The robot shall be able to vary its social behavior.  Performance, facial expressions and physiological parameters are 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.

[Show all publications]

[Google Scholar author page]

Latest publications:

Unobtrusive Cognitive Assessment in Smart-Homes: Leveraging Visual Encoding and Synthetic Movement Traces Data Mining (Feb 2024)
Samaneh Zolfaghari, Annica Kristoffersson, Mia Folke, Maria Lindén, Daniele Riboni
Sensors (MDPI Sensors)

A Taxonomy of Factors Influencing Perceived Safety in Human-Robot Interaction (Jul 2023)
Neziha Akalin , Andrey Kiselev , Annica Kristoffersson, Amy Loutfi
International Journal of Social Robotics (SORO)

Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring (Jul 2023)
Abdelakram Hafid, Saad Abdullah, Maria Lindén, Annica Kristoffersson, Mia Folke
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS) (CBMS'23)

Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters (Jul 2023)
Saad Abdullah, Abdelakram Hafid, Maria Lindén, Mia Folke, Annica Kristoffersson
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS) (CBMS'23)

PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points (Jun 2023)
Saad Abdullah, Abdelakram Hafid, Mia Folke, Maria Lindén, Annica Kristoffersson

State of the Art of Non-Invasive Technologies for Bladder Monitoring: A Scoping Review (Mar 2023)
Abdelakram Hafid, Sabrina Difallah , Camilla Alves , Saad Abdullah, Mia Folke, Maria Lindén, Annica Kristoffersson
Sensors (MDPI Sensors)

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)