机译:基于自适应区域预测的低功耗可穿戴医疗设备实时无损ECG压缩
Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China;
CMOS integrated circuits; biomedical electronics; electrocardiography; encoding; feature extraction; fluctuations; medical signal processing; power consumption; signal classification; waveform analysis; CMOS technology; ECG signals; adaptive region prediction; compression ratio; fluctuation features; frequency 100 MHz; intellectual property core; large-scale integration implementation; linear prediction methods; low-power wearable medical devices; modified variable length code; power 127 muW; power consumption; prediction difference encoding; publically available test databases; real-time ECG waveform classification; real-time lossless ECG compression; simpler transmit format; size 0.18 mum; stringent low-power requirements;
机译:基于模糊决策和可穿戴设备优化方法的无损心电压缩设计VLSI架构
机译:基于STDP和R-STDP神经网络的ECG分类算法,用于超低功耗个人可穿戴设备的实时监控
机译:使用几何自适应分区和基于方形预测的无损医学图像压缩
机译:资源受限区域的实时心电图监测和心血管心律失常检测的可穿戴设备
机译:基于自适应边缘的无损图像压缩预测。
机译:基于块自适应空间预测的医学序列图像近无损压缩新算法
机译:基于STDP和R-STDP神经网络的ECG分类算法,用于超低功耗个人可穿戴设备的实时监控
机译:心电信号的无损和近无损压缩。