# Harnessing FPGA Technology for Energy-Efficient Wearable Medical Devices
## 5 Power Optimization Strategies
### Minimizing Transmission Energy Costs
#### 5.2.1 Data Compression  
Data compression at the sensor node lowers the amount of data to be transmitted and thereby also lowers the power consumption. The authors of [103] proposed a lossless compression scheme based on run-length coding for ECG signals. The signal is compressed through duplicate data encoding, exploiting the distribution and correlation of adjacent beats of the ECG. They obtained a compression ratio of 2.11:1 for lossless compression. Fusion of data from the body sensor network (BSN) also faces the challenge of higher data volumes and power consumption.  
\begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline
**Strategy** & **Description** & **Advantages** & **Constraints** \\ \hline Simplification of arithmetic operations & Complex operations, such as multiplication, are replaced with simpler ones (e.g., MAC to SAC or MUL to XNOR) to reduce computational resources. & & \\ \hline Approximation of arithmetic operations & Complex functions are approximated with simpler ones, having similar curves, to reduce computation complexity. & Requires fewer logic elements and memory resources. & \\ Sparsity-aware arithmetic reduce the number of active computations. & Exploiting the sparse nature of signals to reduce the number of active computations. & Simpler operations can lead to lower switching activity. & Possible loss of precision and therefore accuracy. \\ Parameter quantization & Floating-point operations are replaced with fixed-point or even lower-bit integer operations (e.g., P-32 to F-16, INT-32, INT16, INTS, or INT18, with binarization of parameters to 1 and \(-1\) values. & Reduced resource usage allows more parallelism for performance, lower latency, and faster computation. & Accumulation of smaller errors over time can affect reliability. \\ Feature reduction & Reduces data and computations by eliminating less relevant features. & Reduced power consumption. & Can limit the flexibility of the system. \\ \hline Fused-logic model implementation & Fusion of operations across adjacent layers or across the components to reduce memory access and improve computational efficiency. & Less heat generation leads to more comfort and safety of WMDs. & Less heat generation leads to more comfort and safety of WMDs. \\ \hline Signal format conversion & Conversion of signal formats to reduce complex arithmetic operations (e.g., ECG to binary image). & & \\ \hline \end{tabular}
\end{table}
Table 3: Optimization strategies for designing energy-conscious algorithms.  
In another work [104], the authors used a data compression approach in their ballistocardiograph (BCG)-based heart health monitor. The data sampled at 600 Hz with 16 bits for each sample pose a challenge for storage and wireless transmission due to power consumption in wearable applications. Modified delta encoding was used for online compression of large data volumes, achieving a compression ratio of 5.17 with negligible loss to reduce transmission power consumption and the storage requirements. In another approach, the authors of [105] proposed transmitting only lossy compressed ECG data initially until an anomaly is detected. This method achieved a compression ratio of 7.8\(\times\) at the cost of an RMS error of 4.61, requiring only 18% of the power consumption compared with uncompressed transmission using a Bluetooth transceiver. In the event of anomaly detection at the receiving end, the sensor node can be prompted to send the error residue. This allows the original signal to be accurately reconstructed without any loss, enabling further analysis of the anomaly.  
Depending on the compression technique used, there might be some loss of data fidelity. Any loss of data accuracy could potentially impact clinical decisions based on the monitored data. Moreover, decompression and analysis of compressed data require additional computational resources, which might complicate the device's design and operation at the receiving end.