Inexpensive Home Infrared Living/Environment Sensor with Regional Thermal Information for Infant Physical and Psychological Development

Fabrication of Temperature Sensors with High-Performance Uniformity through Thermal Annealing

It is considered to be of great significance to monitor human health and track the effect of drugs by measuring human temperature mapping through flexible temperature sensors. In this work, we found that the thermal annealing of flexible temperature sensors based on graphite-acrylate copolymer composites can not only improve the temperature coefficient of resistance (TCR) values of the devices, but also greatly improve the uniformity of the performance of the devices prepared in parallel. The best results were obtained when the devices were annealed at 100 °C, which is believed to be due to the rearrangement of graphite particles to generate more uniform and numerous conductive channels within the conductive composite. We believe this finding might promote the practical development of flexible temperature sensors in body temperature sensing for health maintenance and medical applications.

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review

Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers.

A Susceptible Period of Photic Day-Night Rhythm Loss in Common Marmoset Social Behavior Development

The prevalence of neurodevelopmental psychiatric disorders such as pervasive developmental disorders is rapidly increasing worldwide. Although these developmental disorders are known to be influenced by an individual’s genetic background, the potential biological responses to early life’s environmental exposure to both physical and psychological factors must also be considered. Many studies have acknowledged the influence of shorter time for rest at night and the simultaneous occurrence of various kinds of complications involving developmental disorders. In a prior study, we examined how a common marmoset’s (Callithrix jacchus) psychosocial development was affected when it was reared under constant daylight from birth and then reared individually by humans nursing them under constant light (LL) during their juvenile development stages. The behaviors of these marmosets were compared with those of normal day-night cycle (LD) marmosets using a multivariate analysis based on principal component analysis (PCA). That study found that LL marmosets relatively elicited egg-like calls (Ecall) and side-to-side shakes of the upper body with rapid head rotation through adulthood frequently. Based on the PCA, these behaviors were interpreted as “alert” or “hyperactive” states. However, we did not clarify susceptible periods of the photic rhythm loss experience and the psychological development output. In this study we summarize the following studies in our model animal colonies involving 30 animals (11 female, 19 males) to further explore critical age states of inquiry about each social behavior profiling. We compared social behaviors of three age stages, juvenile, adolescent and young adult equivalent to one another in four LL experience conditions, LL (postnatal day (P) 0 to around 150), Middle (P60–149, 90 days), Late (P150–239, 90 days), and LD (no experience). In the most representative 1st and 2nd principal component scores, the shifting to higher frequency of alert behaviors developed at the adult stage in LL, Middle, then Late in turn. The no LL experience group, LD, generally featured higher frequency of local preference of high position compared to LL experience present groups, in adulthood. This limited model primate study might inspire different developmental age sensitive mechanisms of neuronal network to control socio-emotional functions by utilizing the multivariate visualization method, BOUQUET. This study could potentially contribute to nurturing educational designs for social developmental disorders.