Carry select adder is a square-root time high-speed adder. In this paper, FPGA-based synthesis of conventional and hybrid carry select adders are described with a focus on high speed. Conventionally, carry select adders are realized using the following: (i) full adders and 2 : 1 multiplexers, (ii) full adders, binary to excess 1 code converters, and 2 : 1 multiplexers, and (iii) sharing of common Boolean logic. On the other hand, hybrid carry select adders involve a combination of carry select and carry lookahead adders with/without the use of binary to excess 1 code converters. In this work, two new hybrid carry select adders are proposed involving the carry select and section-carry based carry lookahead subadders with/without binary to excess 1 converters. Seven different carry select adders were implemented in Verilog HDL and their performances were analyzed under two scenarios, dual-operand addition and multioperand addition, where individual operands are of sizes 32 and 64-bits. In the case of dual-operand additions, the hybrid carry select adder comprising the proposed carry select and section-carry based carry lookahead configurations is the fastest. With respect to multioperand additions, the hybrid carry select adder containing the carry select and conventional carry lookahead or section-carry based carry lookahead structures produce similar optimized performance.
The revolution of Internet of Things (IoT) technology has paved the way for designing modern health care systems. Among the various applications of IoT, health care monitoring is need of the hour. This paper deals with the design of a Handheld Pregnancy Monitoring Device (HPMD) that comprises of a wearable abdominal patch and mobile application (Pregnancy Health Monitoring app) interfaced with the analytical Health-Internet of Things (H-IoT) platform. This aids in non invasive measurement of the pregnant woman’s uterine contractions, the Fetal Heart Rate (FHR) and the fetal presentation to detect true labor and to ensure fetal safety. Here, the abdominal patch includes the Electromyography (EMG) electrodes that capture the uterine contractile activity and the Fetal Electrocardiogram (FECG) electrodes that capture the fetal electrical activity for monitoring FHR and fetal presentation. Now, the data captured from these electrodes are analyzed using the H-IoT platform by using various methods. A Level crossing rate method is used in H-IoT to differentiate true labor from Braxton-Hicks (false labor). In addition, FHR is retrieved using Discrete Wavelet Transform (DWT) and fetal position is determined by cross correlating the obtained FECG with the existing FECG template. Further, decisions from the analyzed parameters are displayed in the Pregnancy Health Monitoring (PHM) mobile app which includes the live visualization plots of the EMG and FECG signals for monitoring the mother and fetus health condition in the free-living settings.
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