Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems

Fujii, T.; Yamashita, Ken; Konishi, Tadataka; Izumi, Shintaro; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

doi:10.1109/embc.2013.6611251

Cited by 15 publications

(8 citation statements)

References 14 publications

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“…As shown in Fig. 12 (b), the proposed heart rate extractor has higher noise tolerance and minimum power overhead compared with previous noise tolerant hardware [4][5][6]. …”

Section: Implementation Resultsmentioning

confidence: 99%

“…7 and 8 show the algorithm of the IHR extractor. In the first stage, the template data of QRS complex are generated autonomously using the extended version of a coarse-fine short-term autocorrelation (STAC) [4]. Next, template matching is conducted to extract QRS complexes.…”

Section: Noise Tolerant Heart Rate Extractormentioning

confidence: 99%

“…9. In this simulation, the simple implementation of QSW [5], Quad Level Vector (QLV) [6], Continuous Wavelet Transform (CWT) [6], and our previous STAC [4] are modeled using MATLAB. The simulation result shows the proposed method has state-of-theart noise tolerance.…”

Section: Noise Tolerant Heart Rate Extractormentioning

confidence: 99%

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A 6.14µA normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

Izumi

Yamashita

Nakagawa

et al. 2014

2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings

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This paper describes an electrocardiograph (ECG) monitoring SoC using a non-volatile MCU (NVMCU) and a noise tolerant instantaneous heart rate (IHR) monitor. The novelty of this work is the combination of the non-volatile MCU for normally-off computing and a noise-tolerant-QRS (heart beat) detection algorithm to achieve both low-power and noise tolerance. To minimize the stand-by current of MCU, a nonvolatile flip-flop and a 6T-4C NVRAM are employed. Proposed plate-line charge-share and bit-line non-precharge techniques also contribute to mitigate the active power overhead of 6T-4C NVRAM. The proposed accurate heart beat detector employs a coarse-fine autocorrelation and a template matching technique. Accurate heart beat detection also contributes system level power reduction because the active ratio of ADC and digital block can be reduced using a heart beat prediction. Then, at least 25% active time can be reduced. Measurement results show the fully integrated ECG-SoC consumes 6.14A including 1.28-A nonvolatile MCU and 0.7-A heart rate extractor. 

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“…As shown in Fig. 12 (b), the proposed heart rate extractor has higher noise tolerance and minimum power overhead compared with previous noise tolerant hardware [4][5][6]. …”

Section: Implementation Resultsmentioning

confidence: 99%

Section: Noise Tolerant Heart Rate Extractormentioning

confidence: 99%

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A 6.14µA normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

Izumi

Yamashita

Nakagawa

et al. 2014

2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings

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“…Where signal data is lower quality, it may be necessary to use alternative detection methods that can reliably distinguish R-peaks from high amplitude noises (see e.g. [66][67][68][69]).…”

Section: Visualisation Designmentioning

confidence: 99%

Pseudo-colouring an ECG enables lay people to detect QT-interval prolongation regardless of heart rate

et al. 2020

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Drug-induced long QT syndrome (diLQTS), characterized by a prolongation of the QT-interval on the electrocardiogram (ECG), is a serious adverse drug reaction that can cause the life-threatening arrhythmia Torsade de Points (TdP). Self-monitoring for diLQTS could therefore save lives, but detecting it on the ECG is difficult, particularly at high and low heart rates. In this paper, we evaluate whether using a pseudo-colouring visualisation technique and changing the coordinate system (Cartesian vs. Polar) can support lay people in identifying QT-prolongation at varying heart rates. Four visualisation techniques were evaluated using a counterbalanced repeated measures design including Cartesian no-colouring, Cartesian pseudo-colouring, Polar no-colouring and Polar pseudo-colouring. We used a multireader, multi-case (MRMC) receiver operating characteristic (ROC) study design within a psychophysical paradigm, along with eye-tracking technology. Forty-three lay participants read forty ECGs (TdP risk n = 20, no risk n = 20), classifying each QT-interval as normal/ abnormal, and rating their confidence on a 6-point scale. The results show that introducing pseudo-colouring to the ECG significantly increased accurate detection of QT-interval prolongation regardless of heart rate, T-wave morphology and coordinate system. Pseudocolour also helped to reduce reaction times and increased satisfaction when reading the ECGs. Eye movement analysis indicated that pseudo-colour helped to focus visual attention on the areas of the ECG crucial to detecting QT-prolongation. The study indicates that pseudo-colouring enables lay people to visually identify drug-induced QT-prolongation regardless of heart rate, with implications for the more rapid identification and management of diLQTS.

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“…As a design example, the proposed NVFF is applied to 32bit CPU implemented in a vital sensor LSI, which is used for an Instantaneous Heart Rate (IHR) monitoring on the human body [7] as shown in Fig.II. The 32bit CPU performs an onnode vital signal processing using measured IHR data came from a peripheral block.…”

Section: B 32bit Non-volatile Microprocessormentioning

confidence: 99%

A 2.4 pJ ferroelectric-based non-volatile flip-flop with 10-year data retention capability

Kimura

Fuchikami

Maramoto

et al. 2014

2014 IEEE Asian Solid-State Circuits Conference (A-Sscc)

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A ferroelectric-based (FE-based) non-volatile flipflop (NVFF) is proposed for low-power LSI. Since leakage current in a logic circuit can be cut off by non-volatile storage capability of NVFFs, the standby power is reduced to zero. The use of complementarily stored data in coupled FE capacitors makes it possible to achieve 88% reduction of FE capacitor size while maintaining a wide read voltage margin of 240mV (minimum) at 1.5V, which results in 2.4pJ low access energy with 10-year, 85°C data retention capability. An access speed of FE capacitors can be adaptively changed according to required retention time, which becomes 1.6fLs for 10-year data retention, and 170ns for 10-hour data retention. Especially, short-term data retention is suitable for power gating implementation. Applying the proposed circuitry in 32bit CPU of a vital sensor LSI, its power consumption becomes 13% of that of conventional one with area overhead of 64% using 130nm CMOS with Pb(Zr,Ti)03(PZT) thin films.

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Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems

Cited by 15 publications

References 14 publications

A 6.14µA normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

A 6.14µA normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

Pseudo-colouring an ECG enables lay people to detect QT-interval prolongation regardless of heart rate

A 2.4 pJ ferroelectric-based non-volatile flip-flop with 10-year data retention capability

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Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems

Cited by 15 publications

References 14 publications

A 6.14&#x00B5;A normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

A 6.14&#x00B5;A normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

Pseudo-colouring an ECG enables lay people to detect QT-interval prolongation regardless of heart rate

A 2.4 pJ ferroelectric-based non-volatile flip-flop with 10-year data retention capability

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A 6.14µA normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems

A 6.14µA normally-off ECG-SoC with noise tolerant heart rate extractor for wearable healthcare systems