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Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation/ Robert LeMoyne, Timothy Mastroianni.
其他題名:
Applied software development with Python and machine learning by wearable and wireless systems for movement disorder treatment via deep brain stimulation
作者:
LeMoyne, Robert
其他作者:
Mastroianni, Timothy.
出版者:
Singapore :World Scientific, : c2022.,
面頁冊數:
1 online resource (248 p.)
標題:
Movement disorders - Treatment -
電子資源:
https://www.worldscientific.com/worldscibooks/10.1142/12249#t=toc
ISBN:
9789811235962
Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation
LeMoyne, Robert
Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation
[electronic resource] /Applied software development with Python and machine learning by wearable and wireless systems for movement disorder treatment via deep brain stimulationRobert LeMoyne, Timothy Mastroianni. - Singapore :World Scientific,c2022. - 1 online resource (248 p.)
Includes bibliographical references and index.
"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."--
Mode of access: World Wide Web.
ISBN: 9789811235962Subjects--Topical Terms:
1406528
Movement disorders
--Treatment
LC Class. No.: RC376.5 / .L559 2022
Dewey Class. No.: 616.830285
Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation
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"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."--
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Treatment
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https://www.worldscientific.com/worldscibooks/10.1142/12249#t=toc
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