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Portable Multipurpose Bio-Signal Acquisition and Wireless Streaming Device for Wearables

Victor Sarker, Mingzhe Jiang, Tuan Nguyen Gia, Arman Anzanpour, Amir-Mohammad Rahmani, Pasi Liljeberg, Portable Multipurpose Bio-Signal Acquisition and Wireless Streaming Device for Wearables. In: John Schmalzel, Salvo Baglio (Eds.), Sensors Applications Symposium (SAS), 2017 IEEE, 1–6, IEEE, 2017.


Physical indicators are directly related with health and fitness of human body. By employing real-time e-health monitoring systems for acquiring, and analyzing bio-signals by measurements such as electrocardiogram (ECG) and electromyography (EMG), it is possible to extract information to achieve better health-care in terms of observation, diagnosis, and treatment. However, those systems are limited in acquiring and sending data at high rates, are not energy efficient, or, are restricted in terms of portability due to large size and weight. In this paper, a compact portable bio-signal acquisition device for wearables has been designed and implemented. The developed hardware is capable of acquiring and reliably sending the data wirelessly at a high transfer rate in real-time while keeping the overall energy consumption low. Finally, the signal acquisition performance of the device has been evaluated for both ECG and EMG at 8 channel 24 bit resolution/channel 500 samples/s configuration. Measurement of energy consumption has been conducted using professional tool and it is found that the device can continuously work for up to 13.6 hours with a 3.7V 1700 mAh battery. In addition, the device has been used in an IoT-based system as an example of possible integration

BibTeX entry:

  title = {Portable Multipurpose Bio-Signal Acquisition and Wireless Streaming Device for Wearables},
  booktitle = {Sensors Applications Symposium (SAS), 2017 IEEE},
  author = {Sarker, Victor and Jiang, Mingzhe and Nguyen Gia, Tuan and Anzanpour, Arman and Rahmani, Amir-Mohammad and Liljeberg, Pasi},
  editor = {Schmalzel, John and Baglio, Salvo},
  publisher = {IEEE},
  pages = {1–6},
  year = {2017},

Belongs to TUCS Research Unit(s): Embedded Computer and Electronic Systems (ECES)

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