In this paper, we present an unobtrusive cuffless blood pressure (BP) monitoring system based on pulse arrival time (PAT) for facilitating long-term home BP monitoring. The proposed system consists of an electrocardiograph (ECG), a photoplethysmograph (PPG), and a control circuit with a Bluetooth module, all of which are mounted on a common armchair to measure ECG and PPG signals from users while sitting on the armchair in order to calculate continuous PAT. Considering the good linear correlation of systolic BP (SBP) and the nonlinear correlation of diastolic BP (DBP) with PAT, a new BP estimation method was proposed. Ten subjects underwent BP monitoring experiments involving stationary sitting on a chair, lying on a bed, and pedaling using an ergometer in order to assess the accuracy of the estimated BP. A cuff-type BP monitor was used as reference in the experiments. Results showed that the mean difference of the estimated SBP and DBP was within 0.2 ± 5.8 mmHg ( p < 0.00001) and 0.4 ± 5.7 mmHg ( p < 0.00001), respectively, and the mean absolute difference of the estimated SBP and DBP were 4.4 and 4.6 mmHg, respectively, compared to references. Additionally, five subjects participated in data collections consisting of sitting on a chair twice a day for one month. Compared to the reference, the difference did not obviously increase along with time, even though individualized calibration was executed only once at the beginning. These results suggest that the proposed system has quite the potential for long-term home BP monitoring.

Wearable thermometers are popular devices for measuring body temperature during fever, as well as for monitoring basal temperature in women. They are easy to handle, inexpensive, accurate and provide continuous recordings. Most wearable thermometers are connected to a smart phone or tablet to display data. Many types of wearable thermometer are available, such as touch, patch and invisible (radiometric) types. In this review, we describe and discuss currently available wearable thermometers.

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.

A wearable thermometry for core body temperature (CBT) measurement has both healthcare and clinical applications. On the basis of the mechanism of bioheat transfer, we earlier designed and improved a wearable thermometry using the dual-heat-flux method for CBT measurement. In this study, this thermometry is examined experimentally. We studied a fast-changing CBT measurement (FCCM, 55 min, 12 subjects) inside a thermostatic chamber and performed long-term monitoring of CBT (LTM, 24 h, six subjects). When compared with a reference, the CoreTemp CM-210 by Terumo, FCCM shows 0.07 °C average difference and a 95% CI of [-0.27, 0.12] °C. LTM shows no significant difference in parameters for the inference of circadian rhythm. The FCCM and LTM both simulated scenarios in which this thermometry could be used for intensive monitoring and daily healthcare, respectively. The results suggest that because of its convenient design, this thermometry may be an ideal choice for conventional CBT measurements.

No abstract