1 Title: User Performance Data from a Video-based Application/Platform to Enhance Mobility and Integrated Learning in Physical Activities of Daily Living Amongst Older Adults.
Applicants: Sofia Backåberg, Larry Katz, Mirjam Ekstedt, Welf Löwe, Niklas Backåberg 1. Research area of the proposal: eHealth, Healthy Aging, Physical Functioning.
2. Introduction paragraph: This study will explore how user performance data from a newly developed video-based smartphone platform/application (Move Improve) can be used to understand older adults’
(65+) user patterns and possible hinderances to the learning and improvement process of mobility and in physical activities of daily living (PADL). This study connects to a previous seed project supported by DISA (AVATAR-project) and will provide valuable knowledge for the development of future upscale projects with focus on improving competence, confidence, and mobility in PADL amongst older adults with support of digital technique.
3. Problem definition and value:
The proportion of people 65 years or older will increase dramatically in the near future around the world, which implies a global challenge in several aspects. To remain physically active and maintain mobility in daily life activities is crucial for older individuals to prolong their independence and improve their quality of life. Today there is a lack of easily accessible tools that are easy to use and support the individual learning process, and assessment of the quality of movements of daily living, such as getting up from bed, sitting to standing, walking upstairs e.g. ‘physical activities of daily living’. Becoming older implies a higher risk of physical impairment and symptoms that may limit mobility in PADL and also increase the risk of falls. The positive effects of being physically active and reducing sedentary behaviour amongst the elderly are well-known. The development of a technical tool that supports learning and improvement of competence, confidence, and mobility in PADL may have many positive effects on healthy aging, such as reduced sedentary behavior, increased level of physical activity, ability to live an independent life, aging in place and strengthen individuals’ involvement in their self-care. The preservation of functional skills and physical competence would prevent frailty and risk of falls among the elderly population, which today is a common cause of individual suffering from pain and increased dependency and increases in societal costs.
The recently developed peer to peer and self-assessment platform (Move Improve) allows content development of different activities and related skills. The idea of the platform is to provide the user with support through structured assessment/analysis of one’s own skill performance by using video and structural feedback. Move Improve is aimed to be used in collaboration with others, i.e. a partner, significant other or a health care provider to encourage creative discussions and long-term learning.
Studies of using Move Improve among coaches and children has shown promising results on improved self-efficacy and communication. The Move Improve platform is today available for Ipad and Iphone and will be offered for Android shortly as well as a Swedish version.
4. Objectives:
1. To develop and adjust content in the Move Improve platform with focus on older adults’ mobility and integrated learning and training in PADL.
2. To study the user experience of Move Improve during four interactive workshops among 8 older adults and their partner/significant others (16 participants in total).
3. To study the user performance data from 40 older adults and their partner/significant others (80 participants in total) during a four-weeks period of using Move Improve to understand their user patterns and possible hinderance to their learning and improvement process of mobility and integrated training in activities of daily living.
2 4. To assess the subjects with 2D skeleton avatar technology and to use performance data to train a
deep learning model for scoring performance based on the trained model.
5. Expected Results: This seed project will contribute to the development of a user-friendly and
inexpensive tool with focus on facilitating elderly persons’ integrated learning and training in PADL. The knowledge about older adults’ user performance from this project will be used in future upscaled studies to improve physical competence, confidence, and mobility in order to be implemented and integrated in health care interventions and services for the elderly population. Move Improve may furthermore be a valuable tool for health care providers to collaborate with the patient in their learning and improvement process as part of person-centered care. This seed project will result in a multi-disciplinary research funding proposal and 2- 3 publications.
6. Consortium: The project will be hosted by the Department of Health and Caring Sciences at Linnaeus University, and conducted in a multidisciplinary collaboration with researchers from DISA and the Faculty of Kinesiology, University of Calgary.
The project will be coordinated by Sofia Backåberg, PhD, Physiotherapist, Senior Lecturer at Linnaeus University and Post Doc Associate at the University of Calgary. The multidisciplinary research group comprises experienced researchers and associates within data science, caring science, innovative
technology development and creative video and image production. The group has a blend of experienced senior researchers as well as junior researchers, representing a great variety of methodological and theoretical skills. The combined skills and experiences within the group will provide a solid ground for the development, usability testing and implementation.
PhD, Post Doc Sofia Backåberg (sofia.backaberg@lnu.se) Linnaeus University, University of Calgary, Physiotherapy, eHealth, Healthy Aging. Contact person and coordinator of the Project.
Prof. Welf Löwe (welf.lowe@lnu.se) Linnaeus University, DISA. Computer and Information Sciences.
Prof. Mirjam Ekstedt (mirjam.ekstedt@lnu.se) Linnaeus University, Karolinska Institutet, Behavioural and nursing sciences, Implementation Science, eHealth, Co-design, Healthy Aging.
Prof. Larry Katz (katz@ucalgary.ca) University of Calgary, Director of the Sports and Technology Research Lab, Faculty of Kinesiology, Data Science, Innovative Technology, Educational Psychology.
Research Associate and Project Support Manager/Creative Image Producer, Niklas Backåberg (niklas@backaberg.se) University of Calgary and IKEA Communications AB.
7. Activities and Time plan:
2020 2021
Q3 Q4 Q1 Q2 Q3 Q4
Planning and organization (Obj. 1 - 3)
Content development in Move Improve (Obj 1-2) Recruitment process (Obj 2-3)
Usability test, data collection, revision process (Obj 2) Intervention and data collection (Obj 3)
Analysis of user performance data and 2D SAT (Obj 3 and 4) Analysis of result, submission of publications (Obj 2-4) Writing research proposal for future project
3 8. Budget The table below specify the estimated costs for 2020 and 2021.
We are applying for salary for one postdoc (Sofia Backåberg) 3 months 20% [salary: 46 680 kr/month x LKP 52,5% x Local cost 7,5% x OH 42%) x 20% * 3 months = 63 855 SEK] for the practical planning of the study and content development in Move Improve. This will extend her current 80% post doc
employment during 2020 at the University of Calgary. We are also applying for the expenses for editing and monitoring the material in Move Improve [5 days á 3500SEK = 17 500 SEK], for a Video shooting photographer [1 day = 7 000 SEK] expenses for having models performing in the demo videos [3 000 SEK] and for Technical services and data analytics [8 600 SEK].
The whole research group will be actively involved in the planning and organization process, the interpretation of the data and the dissemination of the results as well as the planning of future research applications projects.
Expenses 2020 2021
Project managing, post doc (3 months á 20%) 63,9 TKr Editing and monitoring content (2 days) 17,5 TKr
Video shooting (1 day) 7 TKr
Demo Video Models 3 TKr
Professional/Technical services (data analytics) 8,6 TKr Total 91,4 TKr 8,6 TKr
