Development of wearable hardware platform to measure the ECG and EMG with IMU to detect motion artifacts

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Research units


Weareable biomedical devices make it possible to monitor physiological parameters of human beings where physical fitness is critical for their work. However, the motion artifacts corrupt the ambulatory measurements of electrophysiological parameters and it is necessary to detect and eliminate these motion artifacts. The long term measurement and analysis of health parameters require enormous data processing and storage resources on board. It is also challenging to perform sensor fusion of multiple devices and to manage multiple communication channels. This paper describes the development of a wearable hardware platform to measure electrocardiogram (ECG) and electromyogram (EMG) with an additional IMU sensor to detect the motion artifacts. Bringing all the sensors on single platform resolves the sensor fusion problems. The measurements are digitized and sent wirelessly through a bluetooth interface to a remote unit in real-time. Which is capable for the implementation of extensive processing and analysis algorithms to detect the motion artifacts and extract The features of ECG and EMG waveform structures.


Original languageEnglish
Title of host publicationProceedings - 2019 22nd International Symposium on Design and Diagnostics of Electronic Circuits and Systems, DDECS 2019
Publication statusPublished - 1 Apr 2019
MoE publication typeA4 Article in a conference publication
EventIEEE Symposium on Design and Diagnostics of Electronic Circuits and Systems
- Cluj-Napoca, Romania
Duration: 24 Apr 201926 Apr 2019
Conference number: 22

Publication series

NameIEEE symposium on design and diagnostics of electronic circuits and systems
ISSN (Print)2334-3133
ISSN (Electronic)2473-2117


ConferenceIEEE Symposium on Design and Diagnostics of Electronic Circuits and Systems
Abbreviated titleDDECS

    Research areas

  • ECG, EMG, IMU, Motion artifact

Download statistics

No data available

ID: 35739438