AEQUIPA Technology

The VERSA study (prediction for maintaining self-employment in old age) is a subproject within the BMBF-funded collaborative AEQUIPA (physical activity and health equity: primary prevention for healthy aging) project. The study aims to examine whether sensor-based assessments as a two-point delta-measure over 6 months are an appropriate approach to predict functional decline in advance.

Background and Needs

Muscle power, balance and endurance are crucial for stable movements and, thus, represent the main technically measurable indicators for functional degradation. In order to maintain these factors and to prevent functional disruption, regular training is necessary - especially in and before phases of acute functional degradation. In order to initiate preventive interventions in advance of such phases, measuring techniques for motion analysis that can be used in daily living and enable preventive and precise detction of functional degradation, are required.

Approach

The VERSA study aims to develop a motion analysis system (as a combined set of hardware and detection algorithms) for the predictive detection of functional degradation to recognize gradual functional degradations in the elderly as early as possible. Thereby, 251 subjects between 70 and 89 years were included in this study. The measurements are taken at three measuring times within a period of two years. In this case, established geriatric tests of physical functionality and mobility, the measurement of body composition, and sensor-based motion analyzes are used to characterize subjects. In addition, movement data are recorded and evaluated for motion analysis and longer-term analysis of the individual physical activity by inertial sensors integrated into a belt (accelerometer, gyroscope, magnetometer and barometer).

In order to investigate the motion analysis system's applicability for unstandardized everyday activities in unsupervised settings, participants also carry the inertial sensors for a subsequent week following each assessment in their everyday life. This setting promises ideal prerequisites for more detailed screening, as well as support and reviews of primary prevention measures.

Publications

2021
[13] LC. Büker, F. Zuber, A. Hein, S. Fudickar. HRDepthNet: Depth Image-Based Marker-Less Tracking of Body Joints. Sensors. 2021;21(4). [bibtex][url][doi]
2020
[12] S. Hellmers, L. Peng, S. Lau, R. Diekmann, L. Elgert, JM.. Bauer, A. Hein, S. Fudickar. Activity Scores of Older Adults based on Inertial Measurement Unit Data in Everyday Life. In: Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF. Valetta (Malta): SCITEPRESS – Science and Technology Publications, Lda.; 2020:579–585. [bibtex][url][doi]
[11] S. Fudickar, S. Hellmers, S. Lau, R. Diekmann, JM.. Bauer, A. Hein. Measurement System for Unsupervised Standardized Assessment of Timed “Up & Go” and Five Times Sit to Stand Test in the Community—A Validity Study. Sensors. 2020;20(10):2824. [bibtex][url][doi]
[10] R.. Diekmann, S.. Hellmers, L.. Elgert, S.. Fudickar, A.. Heinks, S.. Lau, J. M.. Bauer, T.. Zieschang, A.. Hein. Minimizing comprehensive geriatric assessment to identify deterioration of physical performance in a healthy community-dwelling older cohort: longitudinal data of the AEQUIPA Versa study. Aging Clinical and Experimental Research. Springer International Publishing; 2020. [bibtex][url][doi]
2019
[9] S. Hellmers, S. Fudickar, S. Lau, L. Elgert, R. Diekmann, JM.. Bauer, A. Hein. Measurement of the Chair Rise Performance of Older People Based on Force Plates and IMUs. Sensors. 2019;19(6):1370. [bibtex][url][doi]
[8] S. Hellmers, S. Lau, R. Diekmann, L. Dasenbrock, T. Kromke, J.M. Bauer, S. Fudickar, A. Hein. Evaluation of Power-Based Stair Climb Performance via Inertial Measurement Units. In: A. Cliquet Jr., S. Wiebe, P. Anderson, G. Saggio, R. Zwiggelaar, H. Gamboa, A. Fred, S. Bermúdez i Badia, eds. Biomedical Engineering Systems and Technologies. Cham: Springer International Publishing; 2019:238–261. [bibtex]
2018
[7] S. Hellmers, S. Fudickar, L. Dasenbrock, A. Heinks, JM.. Bauer, A. Hein. A Model-Based Approach for Jump Analyses Regarding Strength and Balance. In: P. Nathalia, M. and Silveira, and AH. H., and M. Carlos, and van den BE. L, eds. Biomedical Engineering Systems and Technologies. Cham: Springer International Publishing; 2018:354–375. [bibtex][url][doi]
[6] S. Hellmers, T. Kromke, L. Dasenbrock, A. Heinks, JM.. Bauer, A. Hein. Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments. In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications; 2018:39–47. [bibtex][url][doi]
[5] S. Hellmers, B. Izadpanah, L. Dasenbrock, R. Diekmann, JM. Bauer, A. Hein, S. Fudickar. Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements. Sensors. 2018;18(10). [bibtex][url][doi]
2017
[4] S. Hellmers, S. Fudickar, C. Büse, L. Dasenbrock, A. Heinks, JM.. Bauer, A. Hein. Technology Supported Geriatric Assessment. Chapter in R. Wichert, B. Mand, eds. Ambient Assisted Living: 9. AAL-Kongress, Frankfurt/M, Germany, April 20 - 21, 2016. Cham: Springer International Publishing; 2017:85–100. [bibtex][url][doi]
[3] S. Hellmers, S. Fudickar, E. Lange, C. Lins, A. Hein. Validation of a motion capture suit for clinical gait analysis. In: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare - PervasiveHealth '17. New York, New York, USA: ACM Press; 2017:120–126. [bibtex][url][doi]
[2] S. Hellmers, EE. Steen, L. Dasenbrock, A. Heinks, JM.. Bauer, S. Fudickar, A. Hein. Towards a minimized unsupervised technical assessment of physical performance in domestic environments. In: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare - PervasiveHealth '17. New York, New York, USA: ACM Press; 2017:207–216. [bibtex][url][doi]
[1] S. Hellmers, S. Fudickar, L. Dasenbrock, A. Heinks, JM.. Bauer, A. Hein. Understanding Jump Landing as an Oscillating System: A Model-based Approach of Balance and Strength Analyses. In: Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies. Porto: SCITEPRESS - Science and Technology Publications; 2017:159–168. [bibtex][url][doi]
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Grants and Cooperation

The AEQUIPA project has been funded from 02/2015 till 01/2018 by the federal Bundesministerium für Bildung und Forschung (BMBF).

Contributing Partners:

  • Universitätsklinik für Geriatrie Oldenburg der Carl von Ossietzky Universität Oldenburg
  • Geriatrisches Zentrum am AGAPLESION BETHANIEN KRANKENHAUS HEIDELBERG, Lehrstuhl für Geriatrie der Universität Heidelberg (Prof. Bauer)
  • Abteilung Technik und Gesundheit für Menschen an der Jade Hochschule Oldenburg (Prof. Koppelin)
  • OFFIS (Institut für Informatik, Prof. Boll-Westermann)