A Sub-60- $\mu \text{A}$ Multimodal Smart Biosensing SoC With &gt;80-dB SNR, 35- $\mu \text{A}$ Photoplethysmography Signal Chain

Sharma, Ajit; Polley, A.; Lee, Seung Bae; Narayanan, Sriram; Li, Wen; Sculley, T.L.; Ramaswamy, S.

doi:10.1109/jssc.2016.2642205

Cited by 55 publications

(22 citation statements)

References 16 publications

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“…However, the slow frequency of updating the measured DC resulted in signal errors from motion artifacts and ambient light interference. [47] achieves one of the best power dissipation figures using aggressive duty cycling and input signal-aware adaptive sampling. However, the advantage of minimum input-referred noise is offset by lowest gain and highest high pass frequency.…”

Section: A Pulse Oximetersmentioning

confidence: 99%

Wearables for the Next Pandemic

Hedayatipour

McFarlane

2020

IEEE Access

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This paper reviews the current state of the art in wearable sensors, including current challenges, that can alleviate the loads on hospitals and medical centers. During the COVID-19 Pandemic in 2020, healthcare systems were overwhelmed by people with mild to severe symptoms needing care. A careful study of pandemics and their symptoms in the past 100 years reveals common traits that should be monitored for managing the health and economic costs. Cheap, low power, and portable multi-modalsensors that detect the common symptoms can be stockpiled and ready for the next pandemic. These sensors include temperature sensors for fever monitoring, pulse oximetry sensors for blood oxygen levels, impedance sensors for thoracic impedance, and other state sensors that can be integrated into a single system and connected to a smartphone or data center. Both research and commercial medically approved devices are reviewed with an emphasis on the electronics required to realize the sensing. The performance characteristics, such as accuracy, power, resolution, and size of each sensor modality are critically examined. A discussion of the characteristics, research challenges, and features of an ideal integrated wearable system is also presented.

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Section: A Pulse Oximetersmentioning

confidence: 99%

Wearables for the Next Pandemic

Hedayatipour

McFarlane

2020

IEEE Access

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“…Those are about ten times as strong as the ECG signal, severely affecting the system operation. The other technique is a high-accuracy heartbeat and heartbeat variation estimation technique using different modalities [25], [26].…”

Section: Figure 3 Portrays a Block Diagram Of A Typicalmentioning

confidence: 99%

“…A trans-impedance amplifier (TIA, Fig. 7) is commonly used in recent PPG sensors [26], [34], [35]. The TIA converts the minute current I in generated by a photodiode into a voltage with transimpedance R f .…”

Section: Photoplethysmogram (Ppg)mentioning

confidence: 99%

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Recent Progress of Biomedical Processor SoC for Wearable Healthcare Application: A Review

Yoshimoto

Izumi

2019

IEICE Trans. Electron.

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This paper surveys advances in biomedical processor SoC technology for healthcare application and reviews state-of-the-art architecture and circuits used in SoC integration. Particularly, this paper categorizes and describes techniques for improving power efficiency in communication, computation, and sensing. Additionally, it surveys accuracy enhancement techniques for bio-signal measurement and recognition. Finally, we have discussed the potential new directions for development as well as research.

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“…In recent past, many state-of-arts were dedicated to develop a wearable sensor that can measure long-time, continuous and comfortable HR and BP. Most of them employed either electrocardiogram (ECG) and/or photoplethysmography (PPG) sensors (Ahmad et al 2012 ; Forouzanfar et al 2013 ; Huang et al 2014 , Cohen et al 2017 ; Sommermeyer et al 2016 ; Zheng et al 2014 ; Tang et al 2017 ; Sharma et al 2017 ; Yan et al 2019 ). The usage of the ECG devices is limited for the long-time-continuous monitoring of the BP-HR because the ECG device needs a skin preparation and close loop before the measurement.…”

Section: Introductionmentioning

confidence: 99%

External temperature sensor assisted a new low power photoplethysmography readout system for accurate measurement of the bio-signs

Pandey

Chao

2020

Microsyst Technol

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This study presents an external temperature sensor assisted a new low power, time-interleave, wide dynamic range, and low DC drift photoplethysmography (PPG) signal acquisition system to obtain the accurate measurement of various bio signs in real-time. The designed chip incorporates a 2-bit control programmable transimpedance amplifier (TIA), a high order filter, a 3:8 programmable gain amplifier (PGA) and 2 9 2 organic light-emitting diode (OLED) driver. Temperature sensor is used herein to compensate the adverse effect of low-skin-temperature on the PPG signal quality. The analog front-end circuit is implemented in the integrated chip with chip area of 2008 lm 9 1377 lm and fabricated via TSMC T18 process. With the standard 1.8 V, the experimental result shows that the measured current sensing range is 20 nA-100 uA. The measured dynamic range of the designed readout circuit is 80 dB. The estimated signal to noise ratio is 60 dB@1 uA, and the measured input referred noise is 60.2 pA/Hz. The total power consumption of the designed chip is 31.32 lW (readout) ? 1.62 mW (OLED driver@100% duty cycle). The non-invasive PPG sensor is applied to the wrist artery of the 40 healthy subjects for sensing the pulsation of the blood vessel. The experimental results show that for every 1°C decrease in mean ambient temperature tends to 0.06 beats/min, 0.125 mmHg and 0.063 mmHg increase in hear rate (HR), systolic (SBP) and diastolic (DBP), respectively. Similarly, for every 1°C increase in mean ambient temperature tends to 0.13 beats/min, 0.601 mmHg and 0.121 mmHg increase in HR, SBP and DBP, respectively. The measured accuracy and standard error for the HR estimation are 96%, and-0.022 ± 2.589 beats/minute, respectively. The oxygen stauration (S p O 2) measurement results shows that the mean absolute percentage error is less than 5%. The resultant errors for the SBP and DBP measurement are-0.318 ± 5.19 mmHg and-0.5 ± 1.91 mmHg, respectively.

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A Sub-60- $\mu \text{A}$ Multimodal Smart Biosensing SoC With >80-dB SNR, 35- $\mu \text{A}$ Photoplethysmography Signal Chain

Cited by 55 publications

References 16 publications

Wearables for the Next Pandemic

Wearables for the Next Pandemic

Recent Progress of Biomedical Processor SoC for Wearable Healthcare Application: A Review

External temperature sensor assisted a new low power photoplethysmography readout system for accurate measurement of the bio-signs

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