Zusammenfassung
In-bed motion monitoring has become of great interest for a variety of clinical applications. In this paper, we introduce a hashbased learning method to retrieve human poses from pressure sensors data in real time considering temporal correlation between poses. The basis of our approach is a multimodal database describing different in-bed activities. Database entries have been created using an array of pressure sensors and an additional motion capture system. Our results show good performance even in poses where the subject has minimal contact with the sensors
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Literatur
Achilles F, Ichim AE, Coskun H, et al. Patient MoCap: Human pose estimation under blanket occlusion for hospital monitoring applications. Proc MICCAI. 2016;Part A:491–499.
Hoque E, Dickerson RF, Stankovic JA. Monitoring body positions and movements during sleep using WISPs. New York, NY, USA: ACM; 2010.
Heydarzadeh M, Nourani M, Ostadabbas S. In-bed posture classification using deep autoencoders. Proc EMBC. 2016; p. 3839–3842.
Toms MP. Patient movement detection. Google Patents; 2000. US Patent 6,036,660. Available from: https://www.google.com/patents/US6036660.
Alaziz M, Jia Z, Liu J, et al. Motion scale: a body motion monitoring system using bed-mounted wireless load cells. Proc IEEE CHASE. 2016 June; p. 183–192.
Harada T, Sato T, Mori T. Pressure distribution image based human motion tracking system using skeleton and surface integration model; 2001.
Gong Y, Lazebnik S, Gordo A, et al.. Iterative quantization: a procrustean approach to learning binary codes for large-scale image retrieval; 2013.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer-Verlag GmbH Deutschland
About this paper
Cite this paper
Casas, L. et al. (2018). Human Pose Estimation from Pressure Sensor Data. In: Maier, A., Deserno, T., Handels, H., Maier-Hein, K., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2018. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-56537-7_77
Download citation
DOI: https://doi.org/10.1007/978-3-662-56537-7_77
Published:
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-56536-0
Online ISBN: 978-3-662-56537-7
eBook Packages: Computer Science and Engineering (German Language)