Increasing the Energy-Efficiency of Wearables Using Low-Precision Posit Arithmetic with PHEE

Wearable biomedical devices are increasingly being used for continuous patient health monitoring, enabling realtime insights and extended data collection without the need for prolonged hospital stays. These devices must be energy efficient to minimize battery size, improve comfort, and reduce recharging intervals. This paper investigates the use of specialized lowprecision arithmetic formats to enhance the energy efficiency of biomedical wearables. Specifically, we explore posit arithmetic, a floating-point-like representation, in two key applications: cough detection for chronic cough monitoring and R peak detection in ECG analysis. Simulations reveal that 16-bit posits can replace 32-bit IEEE 754 floating point numbers with minimal accuracy loss in cough detection. For R peak detection, posit arithmetic achieves satisfactory accuracy with as few as 10 or 8 bits, compared to the 16-bit requirement for floating-point formats. To further this exploration, we introduce PHEE, a modular and extensible architecture that integrates the Coprosit posit coprocessor within a RISC-V-based system. Using the X-HEEP framework, PHEE seamlessly incorporates posit arithmetic, demonstrating reduced hardware area and power consumption compared to a floating-point counterpart system. Post-synthesis results targeting 16nm TSMC technology show that the posit hardware targeting these biomedical applications can be 38% smaller and consume up to 54% less energy at the functional unit level, with no performance compromise. These findings establish the potential of low-precision posit arithmetic to significantly improve the energy efficiency of wearable biomedical devices.

@misc{mallasen2025Increasing,
    title = {Increasing the {{Energy-Efficiency}} of {{Wearables Using Low-Precision Posit Arithmetic}} with {{PHEE}}},
    author = {Mallas{\'e}n, David and Schiavone, Pasquale Davide and Barrio, Alberto A. Del and {Prieto-Matias}, Manuel and Atienza, David},
    year = 2025,
    month = jan,
    number = {arXiv:2501.18253},
    eprint = {2501.18253},
    primaryclass = {cs},
    publisher = {arXiv},
    doi = {10.48550/arXiv.2501.18253},
    urldate = {2025-01-31},
    archiveprefix = {arXiv}
}