Abstract
One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.
| Original language | English |
|---|---|
| Title of host publication | 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 |
| Pages | 629-632 |
| Number of pages | 4 |
| DOIs | |
| State | Published - Oct 27 2009 |
| Externally published | Yes |
| Event | 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 - Antalya, Turkey Duration: Apr 29 2009 → May 2 2009 |
Other
| Other | 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 |
|---|---|
| Country | Turkey |
| City | Antalya |
| Period | 4/29/09 → 5/2/09 |
Fingerprint
ASJC Scopus subject areas
- Biomedical Engineering
- Clinical Neurology
- Neuroscience(all)
Cite this
Compression of neural signals using discriminative coding for wireless applications. / Craciun, Stefan; Cheney, David; Gugel, Karl; Sanchez, Justin C.; Principe, Jose C.
2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09. 2009. p. 629-632 5109375.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Compression of neural signals using discriminative coding for wireless applications
AU - Craciun, Stefan
AU - Cheney, David
AU - Gugel, Karl
AU - Sanchez, Justin C.
AU - Principe, Jose C.
PY - 2009/10/27
Y1 - 2009/10/27
N2 - One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.
AB - One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.
UR - http://www.scopus.com/inward/record.url?scp=70350227369&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350227369&partnerID=8YFLogxK
U2 - 10.1109/NER.2009.5109375
DO - 10.1109/NER.2009.5109375
M3 - Conference contribution
SN - 9781424420735
SP - 629
EP - 632
BT - 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
ER -