Prof. Dr. Didier Stricker

Dr. Alain Pagani

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Dr. Muhammad Zeshan Afzal

Mhd Rashed Al Koutayni

Jilliam Maria Diaz Barros

Mahdi Chamseddine

Steve Dias da Cruz

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst

Kamalveerkaur Garewal

Christiano Couto Gava

Leif Eric Goebel

Tewodros Amberbir Habtegebrial

Jigyasa Singh Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Mohammad Minouei

Manthan Pancholi

Engr. Kumail Raza

Dr. Nadia Robertini

María Alejandra Sánchez Marín

Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Lukas Stefan Staecker

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão

Towards Global Aerobic Activity Monitoring

Towards Global Aerobic Activity Monitoring
Attila Reiss, Didier Stricker
Proceedings of the 4th International Conference on Pervasive Technologies Related to Assistive Environments International Conference on Pervasive Technologies Related to Assistive Environments (PETRA-11), May 25-27, Crete, Greece

Abstract:: With recent progress in wearable sensing it becomes reasonable for individuals to wear different sensors all day, thus global activity monitoring is establishing. The goals in global activity monitoring systems are amongst others to tell the type of activity that was performed, the duration and the intensity. With the information obtained this way, the individual’s daily routine can be described in detail. One of the strong motivations to achieve these goals comes from healthcare: to be able to tell if individuals were performing enough physical activity to maintain or even promote their health. This paper focuses on the monitoring of aerobic activities, and targets two main goals: to estimate the intensity of activities, and to identify basic/recommended physical activities and postures. For these purposes, a dataset with 8 subjects and 14 different activities was recorded, including the basic activities and postures, but also examples of household (ironing, vacuum cleaning), sports (playing soccer, rope jumping) and everyday activities (ascending and descending stairs). Data from 3 accelerometers — placed on lower arm, chest and foot — and a heart rate monitor were analyzed. In this paper, first results are shown on both the intensity estimation and activity recognition tasks, with a performance of 87,54% and 86,80%, respectively.

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