Analysis for calibration pre-post difference in BP estimation of Galaxy Watch.

The use of smartwatches has become increasingly common with the release of major products such as the Galaxy Watch by Samsung and the Apple Watch by Apple. The common aim of smartwatches is to target the healthcare market with a wearable, physically-attached device, with blood pressure at the core. As blood pressure is an important biomarker for cardiovascular-related diseases, it is a necessary index to inspect in hospitals when checking an individual's health state. Smartwatches are expected to provide a cuff-less, non-invasive method of estimating blood pressure. However, not many experiments have been conducted on blood pressure datasets obtained from smartwatches. Smartwatches are unique compared to other devices because they require "calibration" to sustain their accuracy.In this paper, we investigate the difference between before and after calibration to better understand the calibration pattern. Not only do we seek to understand the demographic differences in calibration, but we also analyze the possible variables that influence calibration differences. Our results show that hypertensive patients are more prone to high calibration differences, which implies that the calibration period should be adjusted by considering the average blood pressure of users.Clinical Relevance- This paper investigates the possibility for daily BP measurement to be used as clinical data while suggesting proper method to sustain its validity.

Surface Activity-Tuned Metal Oxide Chemiresistor: Toward Direct and Quantitative Halitosis Diagnosis.

Continuous monitoring of hydrogen sulfide (H2S) in human breath for early stage diagnosis of halitosis is of great significance for prevention of dental diseases. However, fabrication of a highly selective and sensitive H2S gas sensor material still remains a challenge, and direct analysis of real breath samples has not been properly attempted, to the best of our knowledge. To address the issue, herein, we introduce facile cofunctionalization of WO3 nanofibers with alkaline metal (Na) and noble metal (Pt) catalysts via the simple addition of sodium chloride (NaCl) and Pt nanoparticles (NPs), followed by electrospinning process. The Na-doping and Pt NPs decoration in WO3 grains induces the partial evolution of the Na2W4O13 phase, causing the buildup of Pt/Na2W4O13/WO3 multi-interface heterojunctions that selectively interacts with sulfur-containing species. As a result, we achieved the highest-ranked sensing performances, that is, response (Rair/Rgas) = 780 @ 1 ppm and selectivity (RH2S/REtOH) = 277 against 1 ppm ethanol, among the chemiresistor-based H2S sensors, owing to the synergistic chemical and electronic sensitization effects of the Pt NP/Na compound cocatalysts. The as-prepared sensing layer was proven to be practically effective for direct, and quantitative halitosis analysis based on the correlation (accuracy = 86.3%) between the H2S concentration measured using the direct breath signals obtained by our test device (80 cases) and gas chromatography. This study offers possibilities for direct, highly reliable and rapid detection of H2S in real human breath without the need of any collection or filtering equipment.

Wrist-wearable bioelectrical impedance analyzer with miniature electrodes for daily obesity management.

Bioelectrical impedance analysis (BIA) is used to analyze human body composition by applying a small alternating current through the body and measuring the impedance. The smaller the electrode of a BIA device, the larger the impedance measurement error due to the contact resistance between the electrode and human skin. Therefore, most commercial BIA devices utilize electrodes that are large enough (i.e., 4 × 1400 mm2) to counteract the contact resistance effect. We propose a novel method of compensating for contact resistance by performing 4-point and 2-point measurements alternately such that body impedance can be accurately estimated even with considerably smaller electrodes (outer electrodes: 68 mm2; inner electrodes: 128 mm2). Additionally, we report the use of a wrist-wearable BIA device with single-finger contact measurement and clinical test results from 203 participants at Seoul St. Mary's Hospital. The correlation coefficient and standard error of estimate of percentage body fat were 0.899 and 3.76%, respectively, in comparison with dual-energy X-ray absorptiometry. This result exceeds the performance level of the commercial upper-body portable body fat analyzer (Omron HBF-306). With a measurement time of 7 s, this sensor technology is expected to provide a new possibility of a wearable bioelectrical impedance analyzer, toward obesity management.

Temperature Correction to Enhance Blood Glucose Monitoring Accuracy Using Electrical Impedance Spectroscopy.

Electrical methods are among the primarily studied non-invasive glucose measurement techniques; however, various factors affect the accuracy of the sensors used. Of these, the temperature is a critical factor; hence, the effects of temperature on the electrical properties of blood components are investigated in this study. Furthermore, the changes in the electrical properties of blood according to the glucose level are corrected by considering the effects of temperature on the electrical properties. An impedance sensor is developed and used to measure whole blood impedance in 10 healthy participants at various temperatures and glucose levels. Subsequently, the conductivities of the plasma and cytoplasm were extracted. Changes in the electrical properties of the blood components are then analyzed using linear regression and repeated measures ANOVA. The electrical conductivities of plasma and cytoplasm increased with increasing temperatures (plasma: 0.0397 (slope), 0.7814 (R2), cytoplasm: 0.014 (slope), 0.694 (R2)). At three values of increasing glucose levels (85.4, 158.1, and 271.8 mg/dL), the electrical conductivities of the plasma and cytoplasm decreased. These tendencies are more significant upon temperature corrections (p-values; plasma: 0.001, 0.001, cytoplasm: 0.003, 0.002). The relationships between temperature and electrical conductivity changes can thus be used for temperature corrections in blood glucose measurement.

Direct observation of glucose fingerprint using in vivo Raman spectroscopy.

Noninvasive blood glucose monitoring has been a long-standing dream in diabetes management. The use of Raman spectroscopy, with its molecular specificity, has been investigated in this regard over the past decade. Previous studies reported on glucose sensing based on indirect evidence such as statistical correlation to the reference glucose concentration. However, these claims fail to demonstrate glucose Raman peaks, which has raised questions regarding the effectiveness of Raman spectroscopy for glucose sensing. Here, we demonstrate the first direct observation of glucose Raman peaks from in vivo skin. The signal intensities varied proportional to the reference glucose concentrations in three live swine glucose clamping experiments. Tracking spectral intensity based on linearity enabled accurate prospective prediction in within-subject and intersubject models. Our direct demonstration of glucose signal may quiet the long debate about whether glucose Raman spectra can be measured in vivo in transcutaneous glucose sensing.

Cuff-Less Blood Pressure Estimation Using Pulse Waveform Analysis and Pulse Arrival Time.

Using the massive MIMIC physiological database, we tried to validate pulse wave analysis (PWA) based on multiparameters model whether it can continuously estimate blood pressure (BP) values on single site of one hand. In addition, to consider the limitation of insufficient data acquirement for home user, we used pulse arrival time (PAT) driven BP information to determine the individual scale factors of the PWA-BP estimation model. Experimental results indicate that the accuracy of the average regression model has error standard deviations of  mmHg (PAT),  mmHg (PWA) for SBP and  mmHg (PAT),  mmHg (PWA) for DBP on 23 subjects over a 1 day period. We defined a local-model which is extracted regression model from sparsely selected small dataset, contrast to full dataset for 24h (average-model). The limit of BP estimation accuracy from the local-model of PWA is lower than that of PAT-BP average-model. Whereas the error of the BP estimation local-model was reduced using more data for scaling, it required more than four times the 1 min data extracted over the 12 h calibration period to predict BP for 1 day. This study shows that PWA has possibility to estimate BP value and PAT-driven BP information could be used to determine the individual scale factors of the PWA-BP estimation model for home users.