Atjaunināt sīkdatņu piekrišanu

E-grāmata: Wearable and Wireless Systems for Healthcare I: Gait and Reflex Response Quantification

  • Formāts - EPUB+DRM
  • Cena: 130,85 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This book is the second edition of the one originally published in 2017. The original publication features the discovery of numerous novel applications for the use of smartphones and portable media devices for the quantification of gait, reflex response, and an assortment of other concepts that constitute first-in-the-world applications for these devices. Since the first edition, numerous evolutions involving the domain of wearable and wireless systems for healthcare have transpired warranting the publication of the second edition.





This volume covers wearable and wireless systems for healthcare that are far more oriented to the unique requirements of the biomedical domain. The paradigm-shifting new wearables have been successfully applied to gait analysis, homebound therapy, and quantifiable exercise. Additionally, the confluence of wearable and wireless systems for healthcare with deep learning and neuromorphic applications for classification is addressed. The authors expect that these significant developments make this book valuable for all readers.





 
Wearable and wireless systems for gait analysis and reflex
quantification.- Traditional clinical evaluation of gait and reflex response
by ordinal scale.- Quantification systems appropriate for a clinical
setting.- The rise of inertial measurement units.- Portable wearable and
wireless systems for gait and reflex response quantification.- Smartphones
and portable media devices as wearable and wireless systems for gait and
reflex response quantification.- Bluetooth inertial sensors for gait and
reflex response quantification with perspectives regarding Cloud Computing
and the Internet of Things.- Quantifying the spatial position representation
of gait through sensor fusion.- Role of machine learning for gait and reflex
response classification.- Homebound therapy with wearable and wireless
systems.- Future perspective of Network Centric Therapy.- Evolutions for
Wearable and Wireless Systems.- Gait Analysis with Advanced Wearable and
Wireless Systems.- New Developments in Homebound Therapy Enabled Through
Wearable and Wireless Systems.- New Quantifiable Exercise with Wearable and
Wireless Systems.- Deep Learning and Neuromorphic Applications for
Classifying Health Status Using Wearable and Wireless Systems.- Future
Perspectives for Wearable and Wireless Systems for Healthcare.
Dr. Robert LeMoyne presently is an Adjunct Professor for Northern Arizona University for the Department of Biological Sciences and an Adjunct Professor for Czech Technical University in Prague for the Department of Biomedical Technology. Dr. LeMoyne is researching advanced concepts for wearable and wireless systems, such as for the domain of gait, reflex response, movement disorders, and therapeutic interventions. His Ph.D. in Biomedical Engineering was earned at University of California Los Angeles (UCLA) (2010). He has first authored more than 150 technical proceedings, including four books, which have been cited more than 2000 times, spanning a broad array of subjects, such as the rampant assortment of applications for wearable and wireless systems.





Timothy Mastroianni is a cognitive scientist, researcher, and entrepreneur. He pioneered the non-invasive use of computer vision and pattern recognition to uncover the internal states of random number generators in machines (HiLoClient2002). Mastroianni developed the first model and algorithms capable of predicting a person's thoughts using machine learning and fMRI, presenting these groundbreaking methods at Carnegie Mellon University to map the human brain and identify brain states during specific tasks. He is also the founder of Cognition Engineering, a subsidiary of Cognition International LLC.