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Human Activity Classification Using Multilayer Perceptron

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248107" target="_blank" >RIV/61989100:27240/21:10248107 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.mdpi.com/1424-8220/21/18/6207" target="_blank" >https://www.mdpi.com/1424-8220/21/18/6207</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/s21186207" target="_blank" >10.3390/s21186207</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Human Activity Classification Using Multilayer Perceptron

  • Original language description

    The number of smart homes is rapidly increasing. Smart homes typically feature functions such as voice-activated functions, automation, monitoring, and tracking events. Besides comfort and convenience, the integration of smart home functionality with data processing methods can provide valuable information about the well-being of the smart home residence. This study is aimed at taking the data analysis within smart homes beyond occupancy monitoring and fall detection. This work uses a multilayer perceptron neural network to recognize multiple human activities from wrist- and ankle-worn devices. The developed models show very high recognition accuracy across all activity classes. The cross-validation results indicate accuracy levels above 98% across all models, and scoring evaluation methods only resulted in an average accuracy reduction of 10%.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: A Research Platform focused on Industry 4.0 and Robotics in Ostrava Agglomeration</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Sensors. Vol. 20

  • ISSN

    1424-8220

  • e-ISSN

    1424-8220

  • Volume of the periodical

    21

  • Issue of the periodical within the volume

    18

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    15

  • Pages from-to

    nestrankovano

  • UT code for WoS article

    000699984700001

  • EID of the result in the Scopus database

    2-s2.0-85117739813