A Configurable and Low-Power Mixed Signal SoC for Portable ECG Monitoring Applications

Kim, Hye-Jung; Yazıcıoğlu, Refet Fırat; Kim, Sun‐Young; Helleputte, Nick Van; Artes, Antonio; Konijnenburg, Mario; Huisken, Jos; Penders, Julien; Hoof, Chris Van

doi:10.1109/tbcas.2013.2260159

Cited by 174 publications

(80 citation statements)

References 26 publications

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“…reducing power consumption in the standby mode to 20µW, an active WiFi transmission consumes around 600mW [Gainspan, CC3100MOD]. Nevertheless, in recent years, there has been significant enhancement with integrated ULP System on Chip (SoC) and duty-cycled radio whose power consumption is nowadays in the order of 10-100µW using custom protocols supporting 10-200kbps [Zhang:2013, Kim:2011, Verma:2010, Pandey:2011. The use of passive WiFi is also an alternative to generate 802.11b transmission over distances of 10-30m (in line-of-sight and through walls) while only consuming 10 and 60µW for 1 and 11 Mbps transmissions, respectively (3 to 4 orders of magnitude lower than existing WiFi chipsets) [Kellogg:2016].…”

Section: Power Requirements and Consumption Of Sensors And Devicesmentioning

confidence: 99%

Toward 1G Mobile Power Networks: RF, Signal, and System Designs to Make Smart Objects Autonomous

et al. 2018

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Thanks to the quality of the technology and the existence of international standards, wireless communication networks (based on radio-frequency RF radiation) nowadays underpin the global functioning of our societies. The pursuit towards higher spectral efficiency has been around for about 4 decades, with 5G expected in 2020. 5G and beyond will see the emergence of trillions of low-power autonomous wireless devices for applications such as ubiquitous sensing through an Internet of Things (IoT).Wireless is however more than just communications. For very short range, wireless power via Inductive Power Transfer is a reality with available products and standards (Wireless Power Consortium, Power Matters Alliance, Alliance for Wireless Power, Rezence). Wireless Power via RF (as in wireless communication) on the other hand could be used for longer range via two different ways, commonly referred to as wireless energy harvesting (WEH) and (farfield or radiative) wireless power transfer/transmission (WPT). While WEH assumes RF transmitters are exclusively designed for communication purposes whose ambient signals can be harvested, WPT relies on dedicated sources designed exclusively for wireless power delivery. Wireless Power via RF has long been regarded as a possibility for energising lowpower devices, but it is only recently that it has become recognised as feasible. Indeed, according to , at a fixed computing load, the amount of requested energy falls by a factor of two every year and a half due to the evolution of the electrical efficiency of computer technology. This explains why relying on wireless power to perform meaningful computation tasks at reasonable distances only became feasible in the last few years and justifies this recent interest in wireless power.Recent research advocates that the future of wireless networking goes beyond conventional communication-centric transmission. In the same way as wireless (via RF) has disrupted mobile communications for the last 40 years, wireless (via RF) will disrupt the delivery of mobile power. However, current wireless networks have been designed for communication purposes only. While mobile communication has become a relatively mature technology, currently evolving towards its fifth generation, the development of mobile power is in its infancy and has not even reached its first generation. Not a single standard on mobile power and far-field WPT exists.Despite being subject to regulations on exposure to electromagnetic fields as wireless communication, wireless power brings numerous new opportunities. It enables proactive and controllable energy replenishment of devices for genuine mobility so that they no longer depend on centralised power sources. Hence, no wires, no contact, no (or at least reduced) batteries (and therefore smaller, lighter and compact devices), an ecological solution with no production/maintenance/disposal of trillions of batteries, a prolonged lifetime and a perpetual, predictable and reliable energy supply as opposed to ambient energy-harvesting tec...

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Section: Power Requirements and Consumption Of Sensors And Devicesmentioning

confidence: 99%

Toward 1G Mobile Power Networks: RF, Signal, and System Designs to Make Smart Objects Autonomous

et al. 2018

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“…It also proposes a high integration and high-reliability portable device with ADS129X analog front-end (AFE) for ECG signal acquisition and CC254X Bluetooth low energy (BLE) for wireless communication. Currently, the low power Bluetooth (BT) application is widely used because of its high penetration rate in cellular phones [10]. The hinted handoff mechanism algorithm is the one of novel technique proposed to reduce the wireless transmission loss, furthermore, added MPU as the master controller to decrease the BLE controller operation loading and to regulate the transmission data to achieve the low power consumption and low packet loss rate.…”

Section: Introductionmentioning

confidence: 99%

Low-power low-data-loss bio-signal acquisition system for intelligent electrocardiogram detection

Wang

Dong

Chen

et al. 2017

IEICE Electron. Express

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Abstract:The research describes an intelligent electrocardiogram (ECG) acquisition system with low power and low data loss features. The system is constructed with ADS129X, MSP430X, CC254X Bluetooth low energy (BLE) with low power wireless communication protocol and smart phone for the ECG display. Two architectures, namely, with and without the microprocessor (MPU) and hinted handoff mechanism algorithm, are used to verify the data transmission loss between the BLE and the smart phone. The system not only employed low-power solution but also added full handshake and hinted handoff to achieve complete synchronization and accurate transmission reliability. The MPU method definitely enhanced the ECG packet loss rate and power saving rate to 0.63% and 49.78%, respectively.

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“…But these QRS detection methods have little concern about noise interference which should be taken good care of, as wearable device are sensitive to various noises. [5] used a modified pilot algorithm to deal with different signal distortion and [6] applied the continuous wavelet transform (CWT) for noise filtering. [7] proposed a noise tolerant detector combining short-term autocorrelation and template matching.…”

Section: Introductionmentioning

confidence: 99%

A dual-mode ECG processor with difference-insensitive QRS detection and lossless compression

Luo

Chen

Xiang

et al. 2017

IEICE Electron. Express

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This work presents a low power dual-mode electrocardiogram (ECG) processor with QRS detection and ECG signal lossless compression. An adaptive difference-insensitive filter is proposed to eliminate redundant information in signal for QRS detection, which helps minimize calculation power. It is also adopted as a noise estimator and used to improve the noise tolerance of the detector. Furthermore, in compression mode, linear predictor with a novel adaptive length encoder is applied to the ECG data lossless compression, achieving a compression ratio (CR) of 2.42 with 1.06 K gate count. Implemented in 40 nm CMOS technology, the processor has a total core area of 6806 µm 2 , with 36 nW power consumption in detection mode and 7.3 nW in compression mode under a supply voltage of 0.5 V.

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A Configurable and Low-Power Mixed Signal SoC for Portable ECG Monitoring Applications

Cited by 174 publications

References 26 publications

Toward 1G Mobile Power Networks: RF, Signal, and System Designs to Make Smart Objects Autonomous

Toward 1G Mobile Power Networks: RF, Signal, and System Designs to Make Smart Objects Autonomous

Low-power low-data-loss bio-signal acquisition system for intelligent electrocardiogram detection

A dual-mode ECG processor with difference-insensitive QRS detection and lossless compression

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