A low power respiratory sound diagnosis processing unit based on LSTM for wearable health monitoring.

Early prevention and detection of respiratory disease have attracted extensive attention due to the significant increase in people with respiratory issues. Restraining the spread and relieving the symptom of this disease is essential. However, the traditional auscultation technique demands a high-level medical skill, and computational respiratory sound analysis approaches have limits in constrained locations. A wearable auscultation device is required to real-time monitor respiratory system health and provides consumers with ease. In this work, we developed a Respiratory Sound Diagnosis Processor Unit (RSDPU) based on Long Short-Term Memory (LSTM). The experiments and analyses were conducted on feature extraction and abnormality diagnosis algorithm of respiratory sound, and Dynamic Normalization Mapping (DNM) was proposed to better utilize quantization bits and lessen overfitting. Furthermore, we developed the hardware implementation of RSDPU including a corrector to filter diagnosis noise. We presented the FPGA prototyping verification and layout of the RSDPU for power and area evaluation. Experimental results demonstrated that RSDPU achieved an abnormality diagnosis accuracy of 81.4 %, an area of 1.57 × 1.76 mm under the SMIC 130 nm process, and power consumption of 381.8 µW, which met the requirements of high accuracy, low power consumption, and small area.

Design of plasmonic enhanced all-optical phase-change memory for secondary storage applications.

Phase-change optical device has recently gained tremendous interest due to its ultra-fast transmitting speed, multiplexing and large bandwidth. However, majority of phase-change optical devices are only devoted to on-chip components such as optical tensor core and optical main memory, while developing a secondary storage memory in an optical manner is rarely reported. To address this issue, we propose a novel phase-change optical memory based on plasmonic resonance effects for secondary storage applications. Such design makes use of the plasmonic dimer nanoantenna to generate plasmonic resonance inside the chalcogenide alloy, and thus enables the performance improvements in terms of energy consumption and switching speed. It is found that choosing height, radius, and separation of the plasmonic nanoantenna as 10 nm, 150 nm, and 10 nm, respectively, allows for a write/erase energies of 100 and 240 pJ and a write/erase speed of 10 ns for crystallization and amorphization processes, respectively. Such performance merits encouragingly prevail conventional secondary storage memories and thus pave a route towards the advent of all-optical computer in near future.