A Segmentation Technique Based on Standard Deviation in Body Sensor Networks

2007 ◽  
Author(s):  
Eric Guenterberg ◽  
Hassan Ghasemzadeh ◽  
Roozbeh Jafari ◽  
Ruzena Bajcsy
Keyword(s):  
Sensor Networks ◽  
Standard Deviation ◽  
Body Sensor Networks ◽  
Segmentation Technique

scholarly journals Synchronization in wireless biomedical-sensor networks with Bluetooth Low Energy

2015 ◽  
Vol 1 (1) ◽  
pp. 73-76 ◽  
Author(s):  
André Bideaux ◽  
Bernd Zimmermann ◽  
Stefan Hey ◽  
Wilhelm Stork
Keyword(s):  
Sensor Networks ◽  
Standard Deviation ◽  
Low Energy ◽  
Time Difference ◽  
Sensor Nodes ◽  
Body Sensor Networks ◽  
Average Delay ◽  
Bluetooth Low Energy ◽  
Transmission Delays ◽  
Wireless Body Sensor Networks

AbstractBluetooth Low Energy (BLE) has reduced the energy consumption for sensor nodes drastically. One major reason for this improvement is a non-continuous connection between the nodes. But this causes also a nondeterministic data transmission time. Most synchronization protocols are influenced by this characteristic, with the result of less accuracy. In wireless body sensor networks this accuracy is often of vital importance. Therefore this paper evaluates different synchronization principles customized for BLE.For the evaluation measurements we used two BLE modules connected to one micro controller. This setup allowed us to calculate the error directly for the different principles. First we measured the send-receive time as a reference which influences most synchronization protocols. This time is directly affected by random transmission delays of BLE. Second we used the time difference between receiving and acknowledging a message as principle (A). The last principle (B) can only be used between nodes that use BLE that don’t require a constant connection, because it needs to connect and disconnect the nodes. After a new connection the “connected” events occur in the BLE nodes almost at the same time and can be used for synchronization. The reference measurement showed the worst results. The average delay was 4.76 ms with a standard deviation of 2.32 ms. Principle (A) showed average delays of 7.51 ms, which was almost exactly 1 connection interval in our setup. The standard deviation was 0.41 ms. Principle (B) showed the best results with an average time difference of 39.92 μs and a standard deviation of 14.19 μsThe results showed that with the principles (A) and (B) the synchronization of nodes can be highly improved compared to the reference. In future we will test the principles with synchronization protocols in real sensor nodes also with respect to the processor load.

Towards Battery-Free Body Sensor Networks

2020 ◽  
Author(s):  
Sougata Sen ◽  
Sunghoon Ivan Lee ◽  
Robert Jackson ◽  
Rui Wang ◽  
Nabil Alshurafa ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Body Sensor Networks ◽  
Free Body
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