Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation (Record no. 97799)

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fixed length control field 03832nam a2200397 a 4500
001 - CONTROL NUMBER
control field 00012249
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240731095219.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211002s2021 si o 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811235962
-- (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9811235961
-- (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- (hbk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- (hbk.)
082 04 - CLASSIFICATION NUMBER
Call Number 616.830285
100 1# - AUTHOR NAME
Author LeMoyne, Robert
245 10 - TITLE STATEMENT
Title Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Singapore :
Publisher World Scientific,
Year of publication 2021.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (248 p.)
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- General concept of preliminary network centric therapy applying deep brain stimulation for ameliorating movement disorders with machine learning classification using Python based on feedback from a smartphone as a wearable and wireless system -- Global algorithm development -- Incremental software development using Python -- Automation of feature set extraction using Python -- Waikato environment for knowledge analysis (WEKA) a perspective consideration of multiple machine learning classification algorithms and applications -- Machine learning classification of essential tremor using a reach and grasp task with deep brain stimulation system set to 'on' and 'off' status -- Advanced concepts.
520 ## - SUMMARY, ETC.
Summary, etc "The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources. Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system. Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity."--
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Treatment
-- Computer programs.
700 1# - AUTHOR 2
Author 2 Mastroianni, Timothy.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.worldscientific.com/worldscibooks/10.1142/12249#t=toc
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
520 ## - SUMMARY, ETC.
-- Publisher's website.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Movement disorders

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