Background The cardiac parameters, such as heart rate (HR) and heart rate variability (HRV), are very important physiological data for daily healthcare. Recently, the camera-based photoplethysmography techniques have been proposed for HR measurement. These techniques allow us to estimate the HR contactlessly with low-cost camera. However, the previous works showed limit success for estimating HRV because the R–R intervals, the primary data for HRV calculation, are sensitive to noise and artifacts. Methods This paper proposed a non-contact method to extract the blood volume pulse signal using a chrominance-based method followed by a proposed CWT-based denoising technique. The R–R intervals can then be obtained by finding the peaks in the denoised signal. In this paper, we taped 12 video clips using the frontal camera of a smart phone with different scenarios to make comparisons among our method and the other alternatives using the absolute errors between the estimated HRV metrics and the ones obtained by an ECG-accurate chest band. Results As shown in experiments, our algorithm can greatly reduce absolute errors of HRV metrics comparing with the related works using RGB color signals. The mean of absolute errors of HRV metrics from our method is only 3.53 ms for the static-subject video clips. Conclusions The proposed camera-based method is able to produce reliable HRV metrics which are close to the ones measured by contact devices under different conditions. Thus, our method can be used for remote health monitoring in a convenient and comfortable way.

Background: Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam.

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This paper presents an offline state-of-health (SoH) estimation based on charge transfer resistance for high power lithium-ion batteries, such as lithium iron phosphate or LFP batteries. As shown in the experimental results, the charge transfer resistance has a great aging change with battery degradation and good abilities against the state-of-charge (SoC) drift and external resistance variation in the impedance parameter set of a single-time-constant equivalent circuit model (ECM) including ohmic resistance, charge transfer resistance, doublelayer capacitance, and time constant, for SoH estimation. A fast and efficient three-point (TP) impedance extraction method is also proposed in this paper for accurately extracting the charge transfer resistance in offline SoH estimation. The results of longterm cycling test demonstrate that the TP impedance extraction method can successfully indicate the SoH of LFP batteries with low estimation error of 6.1%.Index Terms-Lithium battery, state-of-health (SoH), impedance estimation, offline battery measurement, battery second-use.

This paper presents a dual-mode capsule gastrointestinal endoscope device. An endoscope combined with a narrowband image (NBI), has been shown to be a superior diagnostic tool for early stage tissue neoplasms detection. Nevertheless, a wireless capsule endoscope with the narrowband imaging technology has not been presented in the market up to now. The narrowband image acquisition and power dissipation reduction are the main challenges of NBI capsule endoscope. In this paper, we present the first narrowband imaging capsule endoscope that can assist clinical doctors to effectively diagnose early gastrointestinal cancers, profited from our dedicated dual-mode complementary metal-oxide semiconductor (CMOS) sensor. The dedicated dual-mode CMOS sensor can offer white-light and narrowband images. Implementation results show that the proposed 512 × 512 CMOS sensor consumes only 2 mA at a 3-V power supply. The average current of the NBI capsule with an 8-Mb/s RF transmitter is nearly 7 ~ 8 mA that can continuously work for 6 ~ 8 h with two 1.5-V 80-mAh button batteries while the frame rate is 2 fps. Experimental results on backside mucosa of a human tongue and pig's small intestine showed that the wireless NBI capsule endoscope can significantly improve the image quality, compared with a commercial-of-the-shelf capsule endoscope for gastrointestinal tract diagnosis.