Open AccessHuman Activity Recognition Using Smart phones
Author(s) -
Aman Gupta and Nidhi Senger
Publication year - 2020
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst061285
Subject(s) - activity recognition , computer science , context (archaeology) , inertial measurement unit , human–computer interaction , support vector machine , field (mathematics) , domain (mathematical analysis) , context awareness , artificial intelligence , ubiquitous computing , assisted living , machine learning , data science , phone , mathematical analysis , linguistics , philosophy , mathematics , pure mathematics , medicine , paleontology , nursing , biology
Human-centered computing is an emerging research field that aims to understand human behavior andintegrate users and their social context with computer systems. One of the most recent, challenging andappealing applications in this framework consists in sensing human body motion using smartphones togather context infor-mation about people actions. In this context, we describe in this work an ActivityRecognition database, built from the recordings of 30 subjects doing Activities of Daily Living (ADL) whilecarrying a waist-mounted smartphone with embedded inertial sensors, which is released to public domainon a well-known on-line repos-itory. Results, obtained on the dataset by exploiting a multiclass SupportVector Machine (SVM), are also acknowledged.