Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs.

Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or sudden death at home has increased. Therefore, herein, we aimed to develop a monitoring system that utilizes piezoelectric sensors for the non-invasive and non-restrictive monitoring of vital signs, including the heart rate and respiration, to detect changes in the health status of several elderly individuals. A ballistocardiogram with a piezoelectric sensor was tested using seven individuals. The frequency spectra of the biosignals acquired from the piezoelectric sensors exhibited multiple peaks corresponding to the harmonics originating from the heartbeat. We aimed for individual identification based on the shapes of these peaks as the recognition criteria. The results of individual identification using deep learning techniques revealed good identification proficiency. Altogether, the monitoring system integrated with piezoelectric sensors showed good potential as a personal identification system for identifying individuals with abnormal biological signals.

Efficacy of ultraviolet light-emitting diodes (UV-LED) at four different peak wavelengths against Cryptosporidium parvum oocysts by inactivation assay using immunodeficient mice.

As an alternative to using ultraviolet (UV) lamps, which are made with mercury that is toxic to the environment and human health, UV light-emitting diodes (UV-LEDs) are expected to be effective for inactivating microorganisms in water. Although UV-LEDs have been reported to be effective against bacteria and viruses, the effectiveness of UV-LEDs against Cryptosporidium parasites has not been fully evaluated. As we report here, we have developed an in vivo quantitative inactivation assay for C. parvum oocysts using immunodeficient mice. Using the assay, we evaluated the effectiveness of treatment by UV lamp (254 nm) at approximately 1000 µJ/cm2 (for 3 s at a distance of 95 mm) compared to inactivation by commercially available UV-LEDs (with peak wavelengths of 268, 275, 284, and 289 nm). The shed patterns of oocysts after treatment with 284- and 289-nm wavelength UV-LEDs were significantly delayed compared to that after treatment with a UV lamp. These findings provide the first suggestion that UV-LEDs are effective against these parasites, as assessed using commercially available 350-mA UV-LEDs under conditions of fixed exposure distance and time.