An Energy Consumption Benchmark for a Low-Power RISC-V Core Aimed at Implantable Medical Devices

Molina-Robles, Roberto; Arnaud, Alfredo; Miguez, Matías; Gak, Joel; Chacón-Rodríguez, Alfonso; García-Ramírez, Ronny

doi:10.1109/les.2022.3190063

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…Therefore, reducing power consumption in these devices is crucial for extending the battery's lifespan. One promising approach to reduce power usage is by optimizing computational requirements using specialized "algorithms" [65][66][67] or designing special chips that can process medical data efficiently while minimizing energy consumption [68][69][70]. Furthermore, this cluster also investigates keywords related to "IoT."…”

Section: Most Important Abstract (Rq7)mentioning

confidence: 99%

Analyzing Emerging Trends in Wireless Implantable Medical Devices (IMDs): A Bibliometric Study

Syifaul Fuada,

Mariella Särestöniemi,

Marcos Katz

2024

Int. J. Onl. Eng.

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In the present era of advanced medical technology, there has been a significant increase in the utilization of wireless-based implantable medical devices (IMDs) in various biomedical applications, including health diagnosis, monitoring, recording, treatment, and other clinical concerns. It is essential to closely examine the research trends in wireless IMD topics to understand their growth trajectory. This can be achieved through the utilization of bibliometric reviews. While there are numerous experimental studies and survey papers on the topic, there is a dearth of review papers that utilize a bibliometric approach. Therefore, this study aims to conduct a bibliometric analysis to identify emerging research trends in wireless IMDs for biomedical applications for the first time. An analysis was conducted on 1,650 articles retrieved from the Scopus database from its inception until September 2023. The study used tools such as VOS Viewer to measure performance and science map parameters, and Tableau Cloud to visually enhance the analysis process. This research endeavor allowed us to analyze historical trends, influential papers, top journals, institutions, countries, and authors within this field. The top three influential journals in this field are IEEE Transactions on Biomedical Circuits and Systems, IEEE Transactions on Antenna and Propagation, and IEEE access. The National University of Singapore is the most productive institution in terms of overall publications. The United States, China, and India make significant contributions to overall publications. Finally, we also examined the most significant keywords and current research areas within this field.

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Section: Most Important Abstract (Rq7)mentioning

confidence: 99%

Analyzing Emerging Trends in Wireless Implantable Medical Devices (IMDs): A Bibliometric Study

Syifaul Fuada,

Mariella Särestöniemi,

Marcos Katz

2024

Int. J. Onl. Eng.

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“…The traditional x86 architecture and ARM instruction sets have become extremely complex after years of development, and contain an increasing number of instruction sets, which significantly increases the difficulty of learning and use. In contrast, the RISC-V architecture has the advantages of instruction set reduction, modularity, open source, scalability, and arbitrary portability of calling soft cores [6], resulting in low cost and a low technical threshold to meet user customization needs [7], which meets the processor requirements of the Internet of Things (IOT) [8] and embedded systems [9].…”

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confidence: 99%

A Custom RISC-V Based SOC Chip for Commodity Barcode Identification

Lin,

Wang,

Cai

et al. 2024

IEEE Access

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The Internet of Things (IoT) is a crucial component of the contemporary information industry and represents a significant advancement in information technology aimed at enhancing both human productivity and daily existence. Their applications are extensive and far-reaching. However, the present state of research on the design of low-cost IoT SoC chips leveraging open-source instruction set architectures lacks the requisite depth and breadth. To meet the requirements of lowcost Internet of Things (IoT) system-on-chip (SoC) development, this study presents a commodity code recognition SoC chip based on the RISC-V instruction set architecture, which is capable of performing image acquisition and barcode recognition. The proposed system comprises two main components: a low-power RISC-V processor and an image recognition module. This study initially enhanced the speed, accuracy, and area efficiency of the hardware design of a commodity barcode imagerecognition module. Subsequently, the image recognition control module was developed using the RISC-V processor and CMOS image sensor OV7670, and the outcomes of image recognition were accessed through interrupts. The processing speed for collecting and identifying 640×480 images on the FPGA board was 11.4FPS, and the image recognition rate was 99.5%. The chip was taped-out using the UMC55n process, which successfully decoded the barcodes and output the results at a working frequency of 40 MHz.

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