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Prof. Dr. Didier Stricker

Dr. Alain Pagani

Dr. Gerd Reis

Eric Thil

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser
Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz
Dr. Muhammad Zeshan Afzal

Sk Aziz Ali

Mhd Rashed Al Koutayni
Murad Almadani
Alaa Alshubbak
Yuriy Anisimov

Jilliam Maria Diaz Barros

Ramy Battrawy
Hammad Butt

Mahdi Chamseddine
Steve Dias da Cruz

Fangwen Shu

Torben Fetzer

Ahmet Firintepe
Sophie Folawiyo

David Michael Fürst
Kamalveerkaur Garewal

Christiano Couto Gava
Leif Eric Goebel

Tewodros Amberbir Habtegebrial
Simon Häring
Khurram Hashmi

Jigyasa Singh Katrolia

Andreas Kölsch
Onorina Kovalenko

Stephan Krauß
Paul Lesur

Muhammad Jameel Nawaz Malik
Michael Lorenz
Markus Miezal

Mina Ameli

Nareg Minaskan Karabid
Mohammad Minouei

Pramod Murthy

Mathias Musahl

Peter Neigel

Manthan Pancholi
Qinzhuan Qian

Engr. Kumail Raza
Dr. Nadia Robertini
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar

Alexander Schäfer
Pascal Schneider

René Schuster

Mohamed Selim
Lukas Stefan Staecker

Dennis Stumpf

Yongzhi Su

Xiaoying Tan
Yaxu Xie

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão
Introducing a Modular Activity Monitoring System
Introducing a Modular Activity Monitoring System
Attila Reiss, Didier Stricker
Conference Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC-11), 33rd, August 30 - September 3, Boston, MA, USA
- Abstract:
- In this paper, the idea of a modular activity monitoring system is introduced. By using different combinations of the system�s three modules, different functionality becomes available: 1) a coarse intensity estimation of physical activities 2) different features based on HR-data and 3) the recognition of basic activities and postures. 3D-accelerometers � placed on lower arm, chest and foot�and a heart rate monitor were used as sensors. A dataset with 8 subjects and 14 different activities was recorded to evaluate the performance of the system. The overall performance on the intensity estimation task, relying on the chest-worn accelerometer and the HR-monitor, was 94.37%. The overall performance on the activity recognition task, using all three accelerometer placements and the HR-monitor, was 90.65%. This paper also gives an analysis of the importance of different accelerometer placements and the importance of a HR-monitor for both tasks.