Combining Clinical and Spatial Constraints into Temporal Planning to Personalize Physical Rehabilitation

Authors

  • Alessandro Umbrico CNR - Institute of Cognitive Sciences and Technologies (CNR-ISTC)
  • Marco Benadduci INRCA IRCCS
  • Roberta Bevilacqua INRCA IRCCS
  • Amedeo Cesta CNR - Institute of Cognitive Sciences and Technologies (CNR-ISTC)
  • Francesca Fracasso CNR - Institute of Cognitive Sciences and Technologies (CNR-ISTC)
  • Elvira Maranesi IRCCS INRCA
  • Andrea Orlandini CNR - Institute of Cognitive Sciences and Technologies (CNR-ISTC)
  • Gabriella Cortellessa CNR - Institute of Cognitive Sciences and Technologies (CNR-ISTC)

DOI:

https://doi.org/10.1609/icaps.v33i1.27234

Keywords:

Planning algorithms, Health and bioinformatics, Search in planning and scheduling, Hierarchical planning

Abstract

This work investigate temporal planning to synthesize personalized physical rehabilitation programs. The first contribution of the work concerns the representation of (heterogeneous) clinical and spatial constraints into a planning framework. The second contribution is the integration of numerical and symbolic reasoning to synthesize technically valid and coherent plans with respect to different clinical objectives. The experimental section discusses the developed planner from a technical view, assessing solving and personalization capabilities, and from a clinical view, assessing the efficacy of plans on the involved patients.
ICAPS-23 Proceedings Cover

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Published

2023-07-01

How to Cite

Umbrico, A., Benadduci, M., Bevilacqua, R., Cesta, A., Fracasso, F., Maranesi, E., Orlandini, A., & Cortellessa, G. (2023). Combining Clinical and Spatial Constraints into Temporal Planning to Personalize Physical Rehabilitation. Proceedings of the International Conference on Automated Planning and Scheduling, 33(1), 532-540. https://doi.org/10.1609/icaps.v33i1.27234

Issue

Vol. 33 (2023): Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling

Section

Industry and Applications Track