Power analysis of a lossless data compression technique for wireless wearable biometric devices

TY - GEN

T1 - Power analysis of a lossless data compression technique for wireless wearable biometric devices

AU - Dai, Chengliang

AU - Crispin-Bailey, Christopher

PY - 2015/6/29

Y1 - 2015/6/29

N2 - This paper presents a promising time-domain based lossless compression technique called Log2 Sub-band encoding, which is designed for using on wireless biomedical devices. Data compression can help to save power from the wireless transceiver during data transmission, and from the storage medium during reading and writing, ultimately leading to a longer battery life of the device. The performance of Log2 Sub-band is measured in terms of its compression ratio (CR) on EEG data and its power consumption. Our simulation results indicate a CR that is comparable and even superior to the well-known Huffman coding, whilst consuming minimal hardware resource. The simulations primarily use electroencephalogram (EEG) data, and the power consumption during compressing process is given to evaluate the system's improvement on its power performance. The possible influence of different biomedical data on technique's performance will also be considered and the signal classification potential of Log2 Sub-band will be noted.

AB - This paper presents a promising time-domain based lossless compression technique called Log2 Sub-band encoding, which is designed for using on wireless biomedical devices. Data compression can help to save power from the wireless transceiver during data transmission, and from the storage medium during reading and writing, ultimately leading to a longer battery life of the device. The performance of Log2 Sub-band is measured in terms of its compression ratio (CR) on EEG data and its power consumption. Our simulation results indicate a CR that is comparable and even superior to the well-known Huffman coding, whilst consuming minimal hardware resource. The simulations primarily use electroencephalogram (EEG) data, and the power consumption during compressing process is given to evaluate the system's improvement on its power performance. The possible influence of different biomedical data on technique's performance will also be considered and the signal classification potential of Log2 Sub-band will be noted.

U2 - 10.1109/PRIME.2015.7251343

DO - 10.1109/PRIME.2015.7251343

M3 - Conference contribution

SN - 9781479982301

SP - 97

EP - 100

BT - 2015 11th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME 2015)

PB - IEEE

T2 - PhD. Research in Microelectronics and Electronics (PRIME), 2015 11th Conference on (pp. 97-100). IEEE.

Y2 - 27 June 2015

ER -