國立高雄大學圖資館 |

登入

回首頁 到查詢結果 [ subject:"Movement disorders" ]

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-電子資源 : 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 stimulationRobert 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 disordersTreatment
電子資源:	https://www.worldscientific.com/worldscibooks/10.1142/12249#t=toc
ISBN:	9789811235962$q(ebook)

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: 9789811235962$q(ebook)Subjects--Topical Terms:

931271
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
LDR:02809cmm a2200313 a 4500 001 627243
003 WSP
005 20211007033616.0
006 m o d
007 cr cnu---unuuu
008 230118s2022 si ob 001 0 eng d
020 $a 9789811235962$q(ebook)
020 $a 9811235961$q(ebook)
020 $z 9789811235955$q(hbk.)
020 $z 9811235953$q(hbk.)
035 $a 00012249
040 $a WSPC $b eng $c WSPC
041 0 $a eng
050 4 $a RC376.5 $b .L559 2022
082 0 4 $a 616.830285 $2 23
100 1 $a LeMoyne, Robert $q (Robert Charles) $3 931270
245 1 0 $a Applied software development with Python & machine learning by wearable & wireless systems for movement disorder treatment via deep brain stimulation $h [electronic resource] / $c Robert LeMoyne, Timothy Mastroianni.
246 3 $a Applied software development with Python and machine learning by wearable and wireless systems for movement disorder treatment via deep brain stimulation
260 $a Singapore : $b World Scientific, $c c2022.
300 $a 1 online resource (248 p.)
504 $a Includes bibliographical references and index.
520 $a "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."-- $c Publisher's website.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Description based on print version record.
650 0 $a Movement disorders $x Treatment $x Computer programs. $3 931271
700 1 $a Mastroianni, Timothy. $3 801404
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/12249#t=toc