Intelligent Control System for Back Pain Therapy

Back pain is a pending subject in our society despite scientific advances. The Kazemi Back System (KBS) is a therapy machine that allows the patient to correctly perform manipulation exercises to heal or relieve pain. In this paper we describe and evaluate a CBR approach to suggest an stream of conf...

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Bibliographic Details
Published inCase-Based Reasoning Research and Development pp. 287 - 301
Main Authors Recio-Garcia, Juan A., Díaz-Agudo, Belén, Jorro-Aragoneses, Jose Luis, Kazemi, Alireza
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
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Summary:Back pain is a pending subject in our society despite scientific advances. The Kazemi Back System (KBS) is a therapy machine that allows the patient to correctly perform manipulation exercises to heal or relieve pain. In this paper we describe and evaluate a CBR approach to suggest an stream of configuration values for the KBS machine based on previous sessions from the same patient or other similar patients. Its challenge is to capture the expertise knowledge of physiotherapists and reuse it for future therapies. The CBR system includes two complementary reuse processes and an explanation module. Within our experimental evaluation we discuss the problem of incompleteness and noise in the data and how to solve the cold start configuration for new patients.
Bibliography:Supported by the UCM (Group 921330) and the Spanish Committee of Economy and Competitiveness (TIN2014-55006-R). The KBS machine is developed by Kazemi Back Health Inc. and funded by the Centre for the Development of Industrial Technology of the Spanish Committee of Economy and Competitiveness.
ISBN:3319610295
9783319610290
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-61030-6_20