Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?

Gait is a characteristic that has been utilized for identifying individuals. As human gait information is now able to be captured by several types of devices, many studies have proposed biometric identification methods using gait information. As research continues, the performance of this technology in terms of identification accuracy has been improved by gathering information from multi-modal sensors.

User Identification from Gait Analysis Using Multi-Modal Sensors in Smart Insole.

Recent studies indicate that individuals can be identified by their gait pattern. A number of sensors including vision, acceleration, and pressure have been used to capture humans' gait patterns, and a number of methods have been developed to recognize individuals from their gait pattern data. This study proposes a novel method of identifying individuals using null-space linear discriminant analysis on humans' gait pattern data.

Decreases in CD8+ T, naive (CD4+CD45RA+) T, and B (CD19+) lymphocytes by exposure to manganese fume.

To examine the effects of exposure to manganese (Mn) on the cellular and humoral immune system in men, T lymphocyte subpopulations, B (CD19+) lymphocytes, natural killer (NK) cells, and serum immunoglobulins (i.e., IgG, IgA and IgM) together with total T (CD3+) lymphocytes and total lymphocytes were measured in blood samples from 21 welders mainly exposed to Mn fume with blood Mn (BMn) concentrations of 0.

Increase of olfactory threshold in plating factory workers exposed to chromium in Korea.

To disclose the effects of chromium (Cr) on olfactory function, olfactory threshold tests were conducted on 27 male plating workers (Cr workers) with signs and symptoms of olfactory irritation but without nasal septum perforation or ulcer and on 34 male control subjects in Korean plating factories. The Cr workers had been exposed to Cr fume for 0.9 to 18.